@Preamble{"\input bibnames.sty"}
@String{ack-nhfb = "Nelson H. F. Beebe,
University of Utah,
Department of Mathematics, 110 LCB,
155 S 1400 E RM 233,
Salt Lake City, UT 84112-0090, USA,
Tel: +1 801 581 5254,
FAX: +1 801 581 4148,
e-mail: \path|beebe@math.utah.edu|,
\path|beebe@acm.org|,
\path|beebe@computer.org| (Internet),
URL: \path|http://www.math.utah.edu/~beebe/|"}
@String{j-TSLP = "ACM Transactions on Speech and Language
Processing (TSLP)"}
@Article{Higashinaka:2004:EDU,
author = "Ryuichiro Higashinaka and Noboru Miyazaki and Mikio
Nakano and Kiyoaki Aikawa",
title = "Evaluating discourse understanding in spoken dialogue
systems",
journal = j-TSLP,
volume = "1",
number = "1",
pages = "1--20",
month = nov,
year = "2004",
CODEN = "????",
DOI = "https://doi.org/10.1145/1035112.1035113",
ISSN = "1550-4875",
bibdate = "Mon Nov 22 07:30:52 MST 2004",
bibsource = "http://portal.acm.org/;
http://www.math.utah.edu/pub/tex/bib/tslp.bib",
acknowledgement = ack-nhfb,
fjournal = "ACM Transactions on Speech and Language Processing
(TSLP)",
journal-URL = "https://dl.acm.org/loi/tslp",
}
@Article{Verma:2005:VFI,
author = "Ashish Verma and Arun Kumar",
title = "Voice fonts for individuality representation and
transformation",
journal = j-TSLP,
volume = "2",
number = "1",
pages = "1--19",
month = feb,
year = "2005",
CODEN = "????",
ISSN = "1550-4875",
bibdate = "Fri Nov 18 08:15:59 MST 2005",
bibsource = "http://portal.acm.org/;
http://www.math.utah.edu/pub/tex/bib/tslp.bib",
acknowledgement = ack-nhfb,
fjournal = "ACM Transactions on Speech and Language Processing
(TSLP)",
journal-URL = "https://dl.acm.org/loi/tslp",
}
@Article{Koumpis:2005:ASV,
author = "Konstantinos Koumpis and Steve Renals",
title = "Automatic summarization of voicemail messages using
lexical and prosodic features",
journal = j-TSLP,
volume = "2",
number = "1",
pages = "1--24",
month = feb,
year = "2005",
CODEN = "????",
ISSN = "1550-4875",
bibdate = "Fri Nov 18 08:15:59 MST 2005",
bibsource = "http://portal.acm.org/;
http://www.math.utah.edu/pub/tex/bib/tslp.bib",
acknowledgement = ack-nhfb,
fjournal = "ACM Transactions on Speech and Language Processing
(TSLP)",
journal-URL = "https://dl.acm.org/loi/tslp",
}
@Article{Tomko:2005:TEH,
author = "Stefanie Tomko and Thomas K. Harris and Arthur Toth
and James Sanders and Alexander Rudnicky and Roni
Rosenfeld",
title = "Towards efficient human machine speech communication:
{The} speech graffiti project",
journal = j-TSLP,
volume = "2",
number = "1",
pages = "1--27",
month = feb,
year = "2005",
CODEN = "????",
ISSN = "1550-4875",
bibdate = "Fri Nov 18 08:15:59 MST 2005",
bibsource = "http://portal.acm.org/;
http://www.math.utah.edu/pub/tex/bib/tslp.bib",
acknowledgement = ack-nhfb,
fjournal = "ACM Transactions on Speech and Language Processing
(TSLP)",
journal-URL = "https://dl.acm.org/loi/tslp",
}
@Article{Lapata:2005:WBM,
author = "Mirella Lapata and Frank Keller",
title = "{Web}-based models for natural language processing",
journal = j-TSLP,
volume = "2",
number = "1",
pages = "1--31",
month = feb,
year = "2005",
CODEN = "????",
ISSN = "1550-4875",
bibdate = "Fri Nov 18 08:15:59 MST 2005",
bibsource = "http://portal.acm.org/;
http://www.math.utah.edu/pub/tex/bib/tslp.bib",
acknowledgement = ack-nhfb,
fjournal = "ACM Transactions on Speech and Language Processing
(TSLP)",
journal-URL = "https://dl.acm.org/loi/tslp",
}
@Article{Federico:2005:WPS,
author = "Marcello Federico and Nicola Bertoldi",
title = "A word-to-phrase statistical translation model",
journal = j-TSLP,
volume = "2",
number = "2",
pages = "1--24",
month = dec,
year = "2005",
CODEN = "????",
ISSN = "1550-4875",
bibdate = "Thu Feb 16 11:43:49 MST 2006",
bibsource = "http://portal.acm.org/;
http://www.math.utah.edu/pub/tex/bib/tslp.bib",
acknowledgement = ack-nhfb,
fjournal = "ACM Transactions on Speech and Language Processing
(TSLP)",
journal-URL = "https://dl.acm.org/loi/tslp",
}
@Article{Avancini:2006:AED,
author = "Henri Avancini and Alberto Lavelli and Fabrizio
Sebastiani and Roberto Zanoli",
title = "Automatic expansion of domain-specific lexicons by
term categorization",
journal = j-TSLP,
volume = "3",
number = "1",
pages = "1--30",
month = may,
year = "2006",
CODEN = "????",
ISSN = "1550-4875",
bibdate = "Wed Jun 14 10:17:29 MDT 2006",
bibsource = "http://portal.acm.org/;
http://www.math.utah.edu/pub/tex/bib/tslp.bib",
acknowledgement = ack-nhfb,
fjournal = "ACM Transactions on Speech and Language Processing
(TSLP)",
journal-URL = "https://dl.acm.org/loi/tslp",
}
@Article{Fung:2006:OSO,
author = "Pascale Fung and Grace Ngai",
title = "One story, one flow: {Hidden Markov Story Models} for
multilingual multidocument summarization",
journal = j-TSLP,
volume = "3",
number = "2",
pages = "1--16",
month = jul,
year = "2006",
CODEN = "????",
ISSN = "1550-4875",
bibdate = "Wed Nov 15 06:40:22 MST 2006",
bibsource = "http://portal.acm.org/;
http://www.math.utah.edu/pub/tex/bib/tslp.bib",
acknowledgement = ack-nhfb,
fjournal = "ACM Transactions on Speech and Language Processing
(TSLP)",
journal-URL = "https://dl.acm.org/loi/tslp",
}
@Article{Wang:2006:HQS,
author = "Chao Wang and Stephanie Seneff",
title = "High-quality speech-to-speech translation for
computer-aided language learning",
journal = j-TSLP,
volume = "3",
number = "2",
pages = "1--21",
month = jul,
year = "2006",
CODEN = "????",
ISSN = "1550-4875",
bibdate = "Wed Nov 15 06:40:22 MST 2006",
bibsource = "http://portal.acm.org/;
http://www.math.utah.edu/pub/tex/bib/tslp.bib",
acknowledgement = ack-nhfb,
fjournal = "ACM Transactions on Speech and Language Processing
(TSLP)",
journal-URL = "https://dl.acm.org/loi/tslp",
}
@Article{Ma:2006:AEC,
author = "Ling Ma and Ben Milner and Dan Smith",
title = "Acoustic environment classification",
journal = j-TSLP,
volume = "3",
number = "2",
pages = "1--22",
month = jul,
year = "2006",
CODEN = "????",
ISSN = "1550-4875",
bibdate = "Wed Nov 15 06:40:22 MST 2006",
bibsource = "http://portal.acm.org/;
http://www.math.utah.edu/pub/tex/bib/tslp.bib",
acknowledgement = ack-nhfb,
fjournal = "ACM Transactions on Speech and Language Processing
(TSLP)",
journal-URL = "https://dl.acm.org/loi/tslp",
}
@Article{Sporleder:2006:BCP,
author = "Caroline Sporleder and Mirella Lapata",
title = "Broad coverage paragraph segmentation across languages
and domains",
journal = j-TSLP,
volume = "3",
number = "2",
pages = "1--35",
month = jul,
year = "2006",
CODEN = "????",
ISSN = "1550-4875",
bibdate = "Wed Nov 15 06:40:22 MST 2006",
bibsource = "http://portal.acm.org/;
http://www.math.utah.edu/pub/tex/bib/tslp.bib",
acknowledgement = ack-nhfb,
fjournal = "ACM Transactions on Speech and Language Processing
(TSLP)",
journal-URL = "https://dl.acm.org/loi/tslp",
}
@Article{Gandrabur:2006:CEN,
author = "Simona Gandrabur and George Foster and Guy Lapalme",
title = "Confidence estimation for {NLP} applications",
journal = j-TSLP,
volume = "3",
number = "3",
pages = "1--29",
month = oct,
year = "2006",
CODEN = "????",
ISSN = "1550-4875",
bibdate = "Wed Nov 15 06:39:00 MST 2006",
bibsource = "http://portal.acm.org/;
http://www.math.utah.edu/pub/tex/bib/tslp.bib",
acknowledgement = ack-nhfb,
fjournal = "ACM Transactions on Speech and Language Processing
(TSLP)",
journal-URL = "https://dl.acm.org/loi/tslp",
}
@Article{Hakkani-Tur:2006:AAS,
author = "Dilek Hakkani-T{\"u}r and Giuseppe Riccardi and Gokhan
Tur",
title = "An active approach to spoken language processing",
journal = j-TSLP,
volume = "3",
number = "3",
pages = "1--31",
month = oct,
year = "2006",
CODEN = "????",
ISSN = "1550-4875",
bibdate = "Wed Nov 15 06:39:00 MST 2006",
bibsource = "http://portal.acm.org/;
http://www.math.utah.edu/pub/tex/bib/tslp.bib",
acknowledgement = ack-nhfb,
fjournal = "ACM Transactions on Speech and Language Processing
(TSLP)",
journal-URL = "https://dl.acm.org/loi/tslp",
}
@Article{VanHalteren:2007:AVL,
author = "Hans {Van Halteren}",
title = "Author verification by linguistic profiling: {An}
exploration of the parameter space",
journal = j-TSLP,
volume = "4",
number = "1",
pages = "1:1--1:??",
month = jan,
year = "2007",
CODEN = "????",
ISSN = "1550-4875",
bibdate = "Mon Jun 16 11:22:59 MDT 2008",
bibsource = "http://portal.acm.org/;
http://www.math.utah.edu/pub/tex/bib/tslp.bib",
abstract = "This article explores the effects of parameter
settings in linguistic profiling, a technique in which
large numbers of counts of linguistic features are used
as a text profile which can then be compared to average
profiles for groups of texts. Although the technique
proves to be quite effective for authorship
verification, with the best overall parameter settings
yielding an equal error rate of 3\% on a test corpus of
student essays, the optimal parameters vary greatly
depending on author and evaluation criterion.",
acknowledgement = ack-nhfb,
articleno = "1",
fjournal = "ACM Transactions on Speech and Language Processing
(TSLP)",
journal-URL = "https://dl.acm.org/loi/tslp",
keywords = "Authorship attribution; authorship recognition;
authorship verification; machine learning",
}
@Article{Inkpen:2007:SMN,
author = "Diana Inkpen",
title = "A statistical model for near-synonym choice",
journal = j-TSLP,
volume = "4",
number = "1",
pages = "2:1--2:??",
month = jan,
year = "2007",
CODEN = "????",
ISSN = "1550-4875",
bibdate = "Mon Jun 16 11:22:59 MDT 2008",
bibsource = "http://portal.acm.org/;
http://www.math.utah.edu/pub/tex/bib/tslp.bib",
abstract = "We present an unsupervised statistical method for
automatic choice of near-synonyms when the context is
given. The method uses the Web as a corpus to compute
scores based on mutual information. Our evaluation
experiments show that this method performs better than
two previous methods on the same task. We also describe
experiments in using supervised learning for this task.
We present an application to an intelligent thesaurus.
This work is also useful in machine translation and
natural language generation.",
acknowledgement = ack-nhfb,
articleno = "2",
fjournal = "ACM Transactions on Speech and Language Processing
(TSLP)",
journal-URL = "https://dl.acm.org/loi/tslp",
keywords = "intelligent thesaurus; Lexical choice; near-synonyms;
semantic similarity; Web as a corpus",
}
@Article{Creutz:2007:UMM,
author = "Mathias Creutz and Krista Lagus",
title = "Unsupervised models for morpheme segmentation and
morphology learning",
journal = j-TSLP,
volume = "4",
number = "1",
pages = "3:1--3:??",
month = jan,
year = "2007",
CODEN = "????",
ISSN = "1550-4875",
bibdate = "Mon Jun 16 11:22:59 MDT 2008",
bibsource = "http://portal.acm.org/;
http://www.math.utah.edu/pub/tex/bib/tslp.bib",
abstract = "We present a model family called Morfessor for the
unsupervised induction of a simple morphology from raw
text data. The model is formulated in a probabilistic
maximum a posteriori framework. Morfessor can handle
highly inflecting and compounding languages where words
can consist of lengthy sequences of morphemes. A
lexicon of word segments, called morphs, is induced
from the data. The lexicon stores information about
both the usage and form of the morphs. Several
instances of the model are evaluated quantitatively in
a morpheme segmentation task on different sized sets of
Finnish as well as English data. Morfessor is shown to
perform very well compared to a widely known benchmark
algorithm, in particular on Finnish data.",
acknowledgement = ack-nhfb,
articleno = "3",
fjournal = "ACM Transactions on Speech and Language Processing
(TSLP)",
journal-URL = "https://dl.acm.org/loi/tslp",
keywords = "Efficient storage; highly inflecting and compounding
languages; language independent methods; maximum a
posteriori (MAP) estimation; morpheme lexicon and
segmentation; unsupervised learning",
}
@Article{Nenkova:2007:PMI,
author = "Ani Nenkova and Rebecca Passonneau and Kathleen
McKeown",
title = "The {Pyramid Method}: {Incorporating} human content
selection variation in summarization evaluation",
journal = j-TSLP,
volume = "4",
number = "2",
pages = "4:1--4:??",
month = may,
year = "2007",
CODEN = "????",
DOI = "https://doi.org/10.1145/1233912.1233913",
ISSN = "1550-4875",
bibdate = "Mon Jun 16 11:23:08 MDT 2008",
bibsource = "http://portal.acm.org/;
http://www.math.utah.edu/pub/tex/bib/tslp.bib",
abstract = "Human variation in content selection in summarization
has given rise to some fundamental research questions:
How can one incorporate the observed variation in
suitable evaluation measures? How can such measures
reflect the fact that summaries conveying different
content can be equally good and informative? In this
article, we address these very questions by proposing a
method for analysis of multiple human abstracts into
semantic content units. Such analysis allows us not
only to quantify human variation in content selection,
but also to assign empirical importance weight to
different content units. It serves as the basis for an
evaluation method, the Pyramid Method, that
incorporates the observed variation and is predictive
of different equally informative summaries. We discuss
the reliability of content unit annotation, the
properties of Pyramid scores, and their correlation
with other evaluation methods.",
acknowledgement = ack-nhfb,
articleno = "4",
fjournal = "ACM Transactions on Speech and Language Processing
(TSLP)",
journal-URL = "https://dl.acm.org/loi/tslp",
keywords = "Evaluation; semantic analysis; summarization",
}
@Article{Yan:2007:CSD,
author = "Jiajun Yan and David B. Bracewell and Shingo Kuroiwa
and Fuji Ren",
title = "{Chinese} semantic dependency analysis: {Construction}
of a treebank and its use in classification",
journal = j-TSLP,
volume = "4",
number = "2",
pages = "5:1--5:??",
month = may,
year = "2007",
CODEN = "????",
DOI = "https://doi.org/10.1145/1233912.1233914",
ISSN = "1550-4875",
bibdate = "Mon Jun 16 11:23:08 MDT 2008",
bibsource = "http://portal.acm.org/;
http://www.math.utah.edu/pub/tex/bib/tslp.bib",
abstract = "Semantic analysis is a standard tool in the Natural
Language Processing (NLP) toolbox with widespread
applications. In this article, we look at tagging part
of the Penn Chinese Treebank with semantic dependency.
Then we take this tagged data to train a maximum
entropy classifier to label the semantic relations
between headwords and dependents to perform semantic
analysis on Chinese sentences. The classifier was able
to achieve an accuracy of over 84\%. We then analyze
the errors in classification to determine the problems
and possible solutions for this type of semantic
analysis.",
acknowledgement = ack-nhfb,
articleno = "5",
fjournal = "ACM Transactions on Speech and Language Processing
(TSLP)",
journal-URL = "https://dl.acm.org/loi/tslp",
keywords = "Chinese; maximum entropy classification; Natural
language processing; semantic dependency analysis",
}
@Article{Tillmann:2007:BBP,
author = "Christoph Tillmann and Tong Zhang",
title = "A block bigram prediction model for statistical
machine translation",
journal = j-TSLP,
volume = "4",
number = "3",
pages = "6:1--6:??",
month = jul,
year = "2007",
CODEN = "????",
DOI = "https://doi.org/10.1145/1255171.1255172",
ISSN = "1550-4875",
bibdate = "Mon Jun 16 11:23:14 MDT 2008",
bibsource = "http://portal.acm.org/;
http://www.math.utah.edu/pub/tex/bib/tslp.bib",
abstract = "In this article, we present a novel training method
for a localized phrase-based prediction model for
statistical machine translation (SMT). The model
predicts block neighbors to carry out a phrase-based
translation that explicitly handles local phrase
reordering. We use a maximum likelihood criterion to
train a log-linear block bigram model which uses
real-valued features (e.g., a language model score) as
well as binary features based on the block identities
themselves (e.g., block bigram features). The model
training relies on an efficient enumeration of local
block neighbors in parallel training data. A novel
stochastic gradient descent (SGD) training algorithm is
presented that can easily handle millions of features.
Moreover, when viewing SMT as a block generation
process, it becomes quite similar to sequential natural
language annotation problems such as part-of-speech
tagging, phrase chunking, or shallow parsing. Our novel
approach is successfully tested on a standard
Arabic-English translation task using two different
phrase reordering models: a block orientation model and
a phrase-distortion model.",
acknowledgement = ack-nhfb,
articleno = "6",
fjournal = "ACM Transactions on Speech and Language Processing
(TSLP)",
journal-URL = "https://dl.acm.org/loi/tslp",
keywords = "machine learning; maximum entropy; Statistical machine
translation; stochastic gradient descent",
}
@Article{Hanna:2007:PER,
author = "Philip Hanna and Ian O'Neill and Craig Wootton and
Michael Mctear",
title = "Promoting extension and reuse in a spoken dialog
manager: {An} evaluation of the queen's communicator",
journal = j-TSLP,
volume = "4",
number = "3",
pages = "7:1--7:??",
month = jul,
year = "2007",
CODEN = "????",
DOI = "https://doi.org/10.1145/1255171.1255173",
ISSN = "1550-4875",
bibdate = "Mon Jun 16 11:23:14 MDT 2008",
bibsource = "http://portal.acm.org/;
http://www.math.utah.edu/pub/tex/bib/tslp.bib",
abstract = "This article describes how an object-oriented approach
can be applied to the architectural design of a spoken
language dialog system with the aim of facilitating the
modification, extension, and reuse of discourse-related
expertise. The architecture of the developed system is
described and a functionally similar VoiceXML system is
used to provide a comparative baseline across a range
of modification and reuse scenarios. It is shown that
the use of an object-oriented dialog manager can
provide a capable means of reusing existing discourse
expertise in a manner that limits the degree of
structural decay associated with system change.",
acknowledgement = ack-nhfb,
articleno = "7",
fjournal = "ACM Transactions on Speech and Language Processing
(TSLP)",
journal-URL = "https://dl.acm.org/loi/tslp",
keywords = "dialog management; Human-computer interaction; speech
and language processing; spoken dialog systems",
}
@Article{Higashinaka:2007:UML,
author = "Ryuichiro Higashinaka and Marilyn A. Walker and Rashmi
Prasad",
title = "An unsupervised method for learning generation
dictionaries for spoken dialogue systems by mining user
reviews",
journal = j-TSLP,
volume = "4",
number = "4",
pages = "8:1--8:??",
month = oct,
year = "2007",
CODEN = "????",
DOI = "https://doi.org/10.1145/1289600.1289601",
ISSN = "1550-4875",
bibdate = "Mon Jun 16 11:23:20 MDT 2008",
bibsource = "http://portal.acm.org/;
http://www.math.utah.edu/pub/tex/bib/tslp.bib",
abstract = "Spoken language generation for dialogue systems
requires a dictionary of mappings between the semantic
representations of concepts that the system wants to
express and the realizations of those concepts.
Dictionary creation is a costly process; it is
currently done by hand for each dialogue domain. We
propose a novel unsupervised method for learning such
mappings from user reviews in the target domain and
test it in the restaurant and hotel domains.
Experimental results show that the acquired mappings
achieve high consistency between the semantic
representation and the realization and that the
naturalness of the realization is significantly higher
than the baseline.",
acknowledgement = ack-nhfb,
articleno = "8",
fjournal = "ACM Transactions on Speech and Language Processing
(TSLP)",
journal-URL = "https://dl.acm.org/loi/tslp",
keywords = "generation dictionary; Natural language generation;
spoken dialogue systems; user reviews",
}
@Article{Ringlstetter:2007:ATC,
author = "Christoph Ringlstetter and Klaus U. Schulz and Stoyan
Mihov",
title = "Adaptive text correction with {Web}-crawled
domain-dependent dictionaries",
journal = j-TSLP,
volume = "4",
number = "4",
pages = "9:1--9:??",
month = oct,
year = "2007",
CODEN = "????",
DOI = "https://doi.org/10.1145/1289600.1289602",
ISSN = "1550-4875",
bibdate = "Mon Jun 16 11:23:20 MDT 2008",
bibsource = "http://portal.acm.org/;
http://www.math.utah.edu/pub/tex/bib/tslp.bib",
abstract = "For the success of lexical text correction, high
coverage of the underlying background dictionary is
crucial. Still, most correction tools are built on top
of static dictionaries that represent fixed collections
of expressions of a given language. When treating texts
from specific domains and areas, often a significant
part of the vocabulary is missed. In this situation,
both automated and interactive correction systems
produce suboptimal results. In this article, we
describe strategies for crawling Web pages that fit the
thematic domain of the given input text. Special
filtering techniques are introduced to avoid pages with
many orthographic errors. Collecting the vocabulary of
filtered pages that meet the vocabulary of the input
text, dynamic dictionaries of modest size are obtained
that reach excellent coverage values. A tool has been
developed that automatically crawls dictionaries in the
indicated way. Our correction experiments with crawled
dictionaries, which address English and German document
collections from a variety of thematic fields, show
that with these dictionaries even the error rate of
highly accurate texts can be reduced, using completely
automated correction methods. For interactive text
correction, more sensible candidate sets for correcting
erroneous words are obtained and the manual effort is
reduced in a significant way. To complete this picture,
we study the effect when using word trigram models for
correction. Again, trigram models from crawled corpora
outperform those obtained from static corpora.",
acknowledgement = ack-nhfb,
articleno = "9",
fjournal = "ACM Transactions on Speech and Language Processing
(TSLP)",
journal-URL = "https://dl.acm.org/loi/tslp",
keywords = "Adaptive techniques; dictionaries; domains; error
correction; Web crawling",
}
@Article{Bulyko:2007:WRL,
author = "Ivan Bulyko and Mari Ostendorf and Manhung Siu and Tim
Ng and Andreas Stolcke and {\"O}zg{\"u}r {\c{C}}etin",
title = "{Web} resources for language modeling in
conversational speech recognition",
journal = j-TSLP,
volume = "5",
number = "1",
pages = "1:1--1:25",
month = dec,
year = "2007",
CODEN = "????",
DOI = "https://doi.org/10.1145/1322391.1322392",
ISSN = "1550-4875",
bibdate = "Mon Jun 16 11:23:25 MDT 2008",
bibsource = "http://portal.acm.org/;
http://www.math.utah.edu/pub/tex/bib/tslp.bib",
abstract = "This article describes a methodology for collecting
text from the Web to match a target sublanguage both in
style (register) and topic. Unlike other work that
estimates n-gram statistics from page counts, the
approach here is to select and filter documents, which
provides more control over the type of material
contributing to the n-gram counts. The data can be used
in a variety of ways; here, the different sources are
combined in two types of mixture models. Focusing on
conversational speech where data collection can be
quite costly, experiments demonstrate the positive
impact of Web collections on several tasks with varying
amounts of data, including Mandarin and English
telephone conversations and English meetings and
lectures.",
acknowledgement = ack-nhfb,
fjournal = "ACM Transactions on Speech and Language Processing
(TSLP)",
journal-URL = "https://dl.acm.org/loi/tslp",
keywords = "Conversational speech; language modeling; Web data",
}
@Article{Giuliano:2007:REI,
author = "Claudio Giuliano and Alberto Lavelli and Lorenza
Romano",
title = "Relation extraction and the influence of automatic
named-entity recognition",
journal = j-TSLP,
volume = "5",
number = "1",
pages = "2:1--2:26",
month = dec,
year = "2007",
CODEN = "????",
DOI = "https://doi.org/10.1145/1322391.1322393",
ISSN = "1550-4875",
bibdate = "Mon Jun 16 11:23:25 MDT 2008",
bibsource = "http://portal.acm.org/;
http://www.math.utah.edu/pub/tex/bib/tslp.bib",
abstract = "We present an approach for extracting relations
between named entities from natural language documents.
The approach is based solely on shallow linguistic
processing, such as tokenization, sentence splitting,
part-of-speech tagging, and lemmatization. It uses a
combination of kernel functions to integrate two
different information sources: (i) the whole sentence
where the relation appears, and (ii) the local contexts
around the interacting entities. We present the results
of experiments on extracting five different types of
relations from a dataset of newswire documents and show
that each information source provides a useful
contribution to the recognition task. Usually the
combined kernel significantly increases the precision
with respect to the basic kernels, sometimes at the
cost of a slightly lower recall. Moreover, we performed
a set of experiments to assess the influence of the
accuracy of named-entity recognition on the performance
of the relation-extraction algorithm. Such experiments
were performed using both the correct named entities
(i.e., those manually annotated in the corpus) and the
noisy named entities (i.e., those produced by a machine
learning-based named-entity recognizer). The results
show that our approach significantly improves the
previous results obtained on the same dataset.",
acknowledgement = ack-nhfb,
fjournal = "ACM Transactions on Speech and Language Processing
(TSLP)",
journal-URL = "https://dl.acm.org/loi/tslp",
keywords = "Information extraction; kernel methods; named-entity
recognition; relation extraction",
}
@Article{Creutz:2007:MBS,
author = "Mathias Creutz and Teemu Hirsim{\"a}ki and Mikko
Kurimo and Antti Puurula and Janne Pylkk{\"o}nen and
Vesa Siivola and Matti Varjokallio and Ebru Arisoy and
Murat Sara{\c{c}}lar and Andreas Stolcke",
title = "Morph-based speech recognition and modeling of
out-of-vocabulary words across languages",
journal = j-TSLP,
volume = "5",
number = "1",
pages = "3:1--3:29",
month = dec,
year = "2007",
CODEN = "????",
DOI = "https://doi.org/10.1145/1322391.1322394",
ISSN = "1550-4875",
bibdate = "Mon Jun 16 11:23:25 MDT 2008",
bibsource = "http://portal.acm.org/;
http://www.math.utah.edu/pub/tex/bib/tslp.bib",
abstract = "We explore the use of morph-based language models in
large-vocabulary continuous-speech recognition systems
across four so-called morphologically rich languages:
Finnish, Estonian, Turkish, and Egyptian Colloquial
Arabic. The morphs are subword units discovered in an
unsupervised, data-driven way using the Morfessor
algorithm. By estimating n -gram language models over
sequences of morphs instead of words, the quality of
the language model is improved through better
vocabulary coverage and reduced data sparsity. Standard
word models suffer from high out-of-vocabulary (OOV)
rates, whereas the morph models can recognize
previously unseen word forms by concatenating morphs.
It is shown that the morph models do perform fairly
well on OOVs without compromising the recognition
accuracy on in-vocabulary words. The Arabic experiment
constitutes the only exception since here the standard
word model outperforms the morph model. Differences in
the datasets and the amount of data are discussed as a
plausible explanation.",
acknowledgement = ack-nhfb,
fjournal = "ACM Transactions on Speech and Language Processing
(TSLP)",
journal-URL = "https://dl.acm.org/loi/tslp",
keywords = "Egyptian Colloquial Arabic; Estonian; Finnish; Highly
inflecting and compounding languages; LVCSR; Morfessor;
morpheme; morphologically rich languages; n -gram
models; subword-based language modeling; Turkish",
}
@Article{Zhang:2008:CWS,
author = "Ruiqiang Zhang and Keiji Yasuda and Eiichiro Sumita",
title = "{Chinese} word segmentation and statistical machine
translation",
journal = j-TSLP,
volume = "5",
number = "2",
pages = "4:1--4:??",
month = may,
year = "2008",
CODEN = "????",
DOI = "https://doi.org/10.1145/1363108.1363109",
ISSN = "1550-4875",
bibdate = "Mon Jun 16 11:23:34 MDT 2008",
bibsource = "http://portal.acm.org/;
http://www.math.utah.edu/pub/tex/bib/tslp.bib",
abstract = "Chinese word segmentation (CWS) is a necessary step in
Chinese--English statistical machine translation (SMT)
and its performance has an impact on the results of
SMT. However, there are many choices involved in
creating a CWS system such as various specifications
and CWS methods. The choices made will create a new CWS
scheme, but whether it will produce a superior or
inferior translation has remained unknown to date. This
article examines the relationship between CWS and SMT.
The effects of CWS on SMT were investigated using
different specifications and CWS methods. Four
specifications were selected for investigation: Beijing
University (PKU), Hong Kong City University (CITYU),
Microsoft Research (MSR), and Academia SINICA (AS). We
created 16 CWS schemes under different settings to
examine the relationship between CWS and SMT. Our
experimental results showed that the MSR's
specifications produced the lowest quality
translations. In examining the effects of CWS methods,
we tested dictionary-based and CRF-based approaches and
found there was no significant difference between the
two in the quality of the resulting translations. We
also found the correlation between the CWS F-score and
SMT BLEU score was very weak. We analyzed CWS errors
and their effect on SMT by evaluating systems trained
with and without these errors. This article also
proposes two methods for combining advantages of
different specifications: a simple concatenation of
training data and a feature interpolation approach in
which the same types of features of translation models
from various CWS schemes are linearly interpolated. We
found these approaches were very effective in improving
the quality of translations.",
acknowledgement = ack-nhfb,
articleno = "4",
fjournal = "ACM Transactions on Speech and Language Processing
(TSLP)",
journal-URL = "https://dl.acm.org/loi/tslp",
keywords = "Chinese word segmentation; linear integration;
statistical machine translation; translation model",
}
@Article{Giannakopoulos:2008:SSE,
author = "George Giannakopoulos and Vangelis Karkaletsis and
George Vouros and Panagiotis Stamatopoulos",
title = "Summarization system evaluation revisited: {$N$}-gram
graphs",
journal = j-TSLP,
volume = "5",
number = "3",
pages = "5:1--5:??",
month = oct,
year = "2008",
CODEN = "????",
DOI = "https://doi.org/10.1145/1410358.1410359",
ISSN = "1550-4875",
bibdate = "Fri Oct 10 13:04:55 MDT 2008",
bibsource = "http://portal.acm.org/;
http://www.math.utah.edu/pub/tex/bib/tslp.bib",
abstract = "This article presents a novel automatic method
(AutoSummENG) for the evaluation of summarization
systems, based on comparing the character n-gram graphs
representation of the extracted summaries and a number
of model summaries. The presented approach is language
neutral, due to its statistical nature, and appears to
hold a level of evaluation performance that matches and
even exceeds other contemporary evaluation methods.
Within this study, we measure the effectiveness of
different representation methods, namely, word and
character n-gram graph and histogram, different n-gram
neighborhood indication methods as well as different
comparison methods between the supplied
representations. A theory for the a priori
determination of the methods' parameters along with
supporting experiments concludes the study to provide a
complete alternative to existing methods concerning the
automatic summary system evaluation process.",
acknowledgement = ack-nhfb,
articleno = "5",
fjournal = "ACM Transactions on Speech and Language Processing
(TSLP)",
journal-URL = "https://dl.acm.org/loi/tslp",
keywords = "automatic summarization; n-gram graph; summarization
evaluation",
}
@Article{Shiramatsu:2008:GTM,
author = "Shun Shiramatsu and Kazunori Komatani and K{\^o}iti
Hasida and Tetsuya Ogata and Hiroshi G. Okuno",
title = "A game-theoretic model of referential coherence and
its empirical verification using large {Japanese} and
{English} corpora",
journal = j-TSLP,
volume = "5",
number = "3",
pages = "6:1--6:??",
month = oct,
year = "2008",
CODEN = "????",
DOI = "https://doi.org/10.1145/1410358.1410360",
ISSN = "1550-4875",
bibdate = "Fri Oct 10 13:04:55 MDT 2008",
bibsource = "http://portal.acm.org/;
http://www.math.utah.edu/pub/tex/bib/tslp.bib",
abstract = "Referential coherence represents the smoothness of
discourse resulting from topic continuity and
pronominalization. Rational individuals prefer a
referentially coherent structure of discourse when they
select a language expression and its interpretation.
This is a preference for cooperation in communication.
By what principle do they share coherent expressions
and interpretations? Centering theory is the standard
theory of referential coherence [Grosz et al. 1995].
Although it is well designed on the bases of
first-order inference rules [Joshi and Kuhn 1979], it
does not embody a behavioral principle for the
cooperation evident in communication. Hasida [1996]
proposed a game-theoretic hypothesis in relation to
this issue. We aim to empirically verify Hasida's
hypothesis by using corpora of multiple languages. We
statistically design language-dependent parameters by
using a corpus of the target language. This statistical
design enables us to objectively absorb
language-specific differences and to verify the
universality of Hasida's hypothesis by using corpora.
We empirically verified our model by using large
Japanese and English corpora. The result proves the
language universality of the hypothesis.",
acknowledgement = ack-nhfb,
articleno = "6",
fjournal = "ACM Transactions on Speech and Language Processing
(TSLP)",
journal-URL = "https://dl.acm.org/loi/tslp",
keywords = "centering theory; corpus statistics; discourse
analysis; discourse salience; game theory;
game-theoretic pragmatics; meaning game; perceptual
utility; pronominalization; reference probability;
referential coherence",
}
@Article{Gliozzo:2009:ITC,
author = "Alfio Gliozzo and Carlo Strapparava and Ido Dagan",
title = "Improving text categorization bootstrapping via
unsupervised learning",
journal = j-TSLP,
volume = "6",
number = "1",
pages = "1:1--1:??",
month = oct,
year = "2009",
CODEN = "????",
DOI = "https://doi.org/10.1145/1596515.1596516",
ISSN = "1550-4875",
bibdate = "Fri Oct 9 20:48:21 MDT 2009",
bibsource = "http://portal.acm.org/;
http://www.math.utah.edu/pub/tex/bib/tslp.bib",
abstract = "We propose a text-categorization bootstrapping
algorithm in which categories are described by relevant
seed words. Our method introduces two unsupervised
techniques to improve the initial categorization step
of the bootstrapping scheme: (i) using latent semantic
spaces to estimate the similarity among documents and
words, and (ii) the Gaussian mixture algorithm, which
differentiates relevant and nonrelevant category
information using statistics from unlabeled examples.
In particular, this second step maps the similarity
scores to class posterior probabilities, and therefore
reduces sensitivity to keyword-dependent variations in
scores. The algorithm was evaluated on two text
categorization tasks, and obtained good performance
using only the category names as initial seeds. In
particular, the performance of the proposed method
proved to be equivalent to a pure supervised approach
trained on 70--160 labeled documents per category.",
acknowledgement = ack-nhfb,
articleno = "1",
fjournal = "ACM Transactions on Speech and Language Processing
(TSLP)",
journal-URL = "https://dl.acm.org/loi/tslp",
keywords = "bootstrapping; Text categorization; unsupervised
machine learning",
}
@Article{Murray:2009:ESE,
author = "Gabriel Murray and Thomas Kleinbauer and Peter Poller
and Tilman Becker and Steve Renals and Jonathan Kilgour",
title = "Extrinsic summarization evaluation: {A} decision audit
task",
journal = j-TSLP,
volume = "6",
number = "2",
pages = "2:1--2:??",
month = oct,
year = "2009",
CODEN = "????",
DOI = "https://doi.org/10.1145/1596517.1596518",
ISSN = "1550-4875",
bibdate = "Fri Oct 9 20:49:17 MDT 2009",
bibsource = "http://portal.acm.org/;
http://www.math.utah.edu/pub/tex/bib/tslp.bib",
abstract = "In this work we describe a large-scale extrinsic
evaluation of automatic speech summarization
technologies for meeting speech. The particular task is
a decision audit, wherein a user must satisfy a complex
information need, navigating several meetings in order
to gain an understanding of how and why a given
decision was made. We compare the usefulness of
extractive and abstractive technologies in satisfying
this information need, and assess the impact of
automatic speech recognition (ASR) errors on user
performance. We employ several evaluation methods for
participant performance, including post-questionnaire
data, human subjective and objective judgments, and a
detailed analysis of participant browsing behavior. We
find that while ASR errors affect user satisfaction on
an information retrieval task, users can adapt their
browsing behavior to complete the task satisfactorily.
Results also indicate that users consider extractive
summaries to be intuitive and useful tools for browsing
multimodal meeting data. We discuss areas in which
automatic summarization techniques can be improved in
comparison with gold-standard meeting abstracts.",
acknowledgement = ack-nhfb,
articleno = "2",
fjournal = "ACM Transactions on Speech and Language Processing
(TSLP)",
journal-URL = "https://dl.acm.org/loi/tslp",
keywords = "abstraction; browsing; evaluation; extraction;
interfaces; Summarization",
}
@Article{Zhu:2010:CBS,
author = "Jingbo Zhu and Huizhen Wang and Eduard Hovy and
Matthew Ma",
title = "Confidence-based stopping criteria for active learning
for data annotation",
journal = j-TSLP,
volume = "6",
number = "3",
pages = "3:1--3:??",
month = apr,
year = "2010",
CODEN = "????",
DOI = "https://doi.org/10.1145/1753783.1753784",
ISSN = "1550-4875",
bibdate = "Mon Apr 26 14:46:47 MDT 2010",
bibsource = "http://portal.acm.org/;
http://www.math.utah.edu/pub/tex/bib/tslp.bib",
abstract = "The labor-intensive task of labeling data is a serious
bottleneck for many supervised learning approaches for
natural language processing applications. Active
learning aims to reduce the human labeling cost for
supervised learning methods. Determining when to stop
the active learning process is a very important
practical issue in real-world applications. This
article addresses the stopping criterion issue of
active learning, and presents four simple stopping
criteria based on confidence estimation over the
unlabeled data pool, including {\em maximum
uncertainty}, {\em overall uncertainty}, {\em selected
accuracy,\/} and {\em minimum expected error\/}
methods. Further, to obtain a proper threshold for a
stopping criterion in a specific task, this article
presents a strategy by considering the label change
factor to dynamically update the predefined threshold
of a stopping criterion during the active learning
process. To empirically analyze the effectiveness of
each stopping criterion for active learning, we design
several comparison experiments on seven real-world
datasets for three representative natural language
processing applications such as word sense
disambiguation, text classification and opinion
analysis.",
acknowledgement = ack-nhfb,
articleno = "3",
fjournal = "ACM Transactions on Speech and Language Processing
(TSLP)",
journal-URL = "https://dl.acm.org/loi/tslp",
keywords = "active learning; confidence estimation; stopping
criterion; text classification; uncertainty sampling;
word sense disambiguation",
}
@Article{Uzeda:2010:CCE,
author = "Vin{\'\i}cius Rodrigues Uz{\^e}da and Thiago Alexandre
Salgueiro Pardo and Maria Das Gra{\c{c}}as Volpe Nunes",
title = "A comprehensive comparative evaluation of {RST}-based
summarization methods",
journal = j-TSLP,
volume = "6",
number = "4",
pages = "4:1--4:??",
month = may,
year = "2010",
CODEN = "????",
DOI = "https://doi.org/10.1145/1767756.1767757",
ISSN = "1550-4875",
bibdate = "Fri May 14 15:32:31 MDT 2010",
bibsource = "http://portal.acm.org/;
http://www.math.utah.edu/pub/tex/bib/tslp.bib",
abstract = "Motivated by governmental, commercial and academic
interests, and due to the growing amount of
information, mainly online, automatic text
summarization area has experienced an increasing number
of researches and products, which led to a countless
number of summarization methods. In this paper, we
present a comprehensive comparative evaluation of the
main automatic text summarization methods based on
Rhetorical Structure Theory (RST), claimed to be among
the best ones. We compare our results to superficial
summarizers, which belong to a paradigm with severe
limitations, and to hybrid methods, combining RST and
superficial methods. We also test voting systems and
machine learning techniques trained on RST features. We
run experiments for English and Brazilian Portuguese
languages and compare the results obtained by using
manually and automatically parsed texts. Our results
systematically show that all RST methods have
comparable overall performance and that they outperform
most of the superficial methods. Machine learning
techniques achieved high accuracy in the classification
of text segments worth of being in the summary, but
were not able to produce more informative summaries
than the regular RST methods.",
acknowledgement = ack-nhfb,
articleno = "4",
fjournal = "ACM Transactions on Speech and Language Processing
(TSLP)",
journal-URL = "https://dl.acm.org/loi/tslp",
keywords = "rhetorical structure theory; text summarization",
}
@Article{Morin:2010:BBU,
author = "Emmanuel Morin and B{\'e}atrice Daille and Koichi
Takeuchi and Kyo Kageura",
title = "Brains, not brawn: {The} use of ``smart'' comparable
corpora in bilingual terminology mining",
journal = j-TSLP,
volume = "7",
number = "1",
pages = "1:1--1:??",
month = aug,
year = "2010",
CODEN = "????",
DOI = "https://doi.org/10.1145/1839478.1839479",
ISSN = "1550-4875",
bibdate = "Thu Sep 30 09:11:51 MDT 2010",
bibsource = "http://portal.acm.org/;
http://www.math.utah.edu/pub/tex/bib/tslp.bib",
abstract = "Current research in text mining favors the quantity of
texts over their representativeness. But for bilingual
terminology mining, and for many language pairs, large
comparable corpora are not available. More importantly,
as terms are defined vis-{\`a}-vis a specific domain
with a restricted register, it is expected that the
representativeness rather than the quantity of the
corpus matters more in terminology mining. Our
hypothesis, therefore, is that the representativeness
of the corpus is more important than the quantity and
ensures the quality of the acquired terminological
resources. This article tests this hypothesis on a
French--Japanese bilingual term extraction task. To
demonstrate how important the type of discourse is as a
characteristic of the comparable corpora, we used a
state-of-the-art multilingual terminology mining chain
composed of two extraction programs, one in each
language, and an alignment program. We evaluated the
candidate translations using a reference list, and
found that taking discourse type into account resulted
in candidate translations of a better quality even when
the corpus size was reduced by half.",
acknowledgement = ack-nhfb,
articleno = "1",
fjournal = "ACM Transactions on Speech and Language Processing
(TSLP)",
journal-URL = "https://dl.acm.org/loi/tslp",
keywords = "comparable corpora; lexical alignment; Terminology
mining",
}
@Article{El-Beltagy:2011:AEL,
author = "Samhaa R. El-Beltagy and Ahmed Rafea",
title = "An accuracy-enhanced light stemmer for {Arabic} text",
journal = j-TSLP,
volume = "7",
number = "2",
pages = "2:1--2:??",
month = feb,
year = "2011",
CODEN = "????",
DOI = "https://doi.org/10.1145/1921656.1921657",
ISSN = "1550-4875",
bibdate = "Tue Feb 22 16:47:19 MST 2011",
bibsource = "http://portal.acm.org/;
http://www.math.utah.edu/pub/tex/bib/tslp.bib",
abstract = "Stemming is a key step in most text mining and
information retrieval applications. Information
extraction, semantic annotation, as well as ontology
learning are but a few examples where using a stemmer
is a must. While the use of light stemmers in Arabic
texts has proven highly effective for the task of
information retrieval, this class of stemmers falls
short of providing the accuracy required by many text
mining applications. This can be attributed to the fact
that light stemmers employ a set of rules that they
apply indiscriminately and that they do not address
stemming of broken plurals at all, even though this
class of plurals is very commonly used in Arabic
texts.",
acknowledgement = ack-nhfb,
articleno = "2",
fjournal = "ACM Transactions on Speech and Language Processing
(TSLP)",
journal-URL = "https://dl.acm.org/loi/tslp",
}
@Article{Lemon:2011:ISI,
author = "Oliver Lemon and Olivier Pietquin",
title = "Introduction to special issue on machine learning for
adaptivity in spoken dialogue systems",
journal = j-TSLP,
volume = "7",
number = "3",
pages = "3:1--3:??",
month = may,
year = "2011",
CODEN = "????",
DOI = "https://doi.org/10.1145/1966407.1966408",
ISSN = "1550-4875",
bibdate = "Thu Jun 2 07:47:26 MDT 2011",
bibsource = "http://portal.acm.org/;
http://www.math.utah.edu/pub/tex/bib/tslp.bib",
acknowledgement = ack-nhfb,
articleno = "3",
fjournal = "ACM Transactions on Speech and Language Processing
(TSLP)",
journal-URL = "https://dl.acm.org/loi/tslp",
}
@Article{Gavsic:2011:EHD,
author = "Milica Gav{\v{s}}i{\'c} and Steve Young",
title = "Effective handling of dialogue state in the hidden
information state {POMDP}-based dialogue manager",
journal = j-TSLP,
volume = "7",
number = "3",
pages = "4:1--4:??",
month = may,
year = "2011",
CODEN = "????",
DOI = "https://doi.org/10.1145/1966407.1966409",
ISSN = "1550-4875",
bibdate = "Thu Jun 2 07:47:26 MDT 2011",
bibsource = "http://portal.acm.org/;
http://www.math.utah.edu/pub/tex/bib/tslp.bib",
abstract = "Effective dialogue management is critically dependent
on the information that is encoded in the dialogue
state. In order to deploy reinforcement learning for
policy optimization, dialogue must be modeled as a
Markov Decision Process. This requires that the
dialogue state must encode all relevent information
obtained during the dialogue prior to that state. This
can be achieved by combining the user goal, the
dialogue history, and the last user action to form the
dialogue state. In addition, to gain robustness to
input errors, dialogue must be modeled as a Partially
Observable Markov Decision Process (POMDP) and hence, a
distribution over all possible states must be
maintained at every dialogue turn.",
acknowledgement = ack-nhfb,
articleno = "4",
fjournal = "ACM Transactions on Speech and Language Processing
(TSLP)",
journal-URL = "https://dl.acm.org/loi/tslp",
}
@Article{Cuayahuitl:2011:SAD,
author = "Heriberto Cuay{\'a}huitl and Nina Dethlefs",
title = "Spatially-aware dialogue control using hierarchical
reinforcement learning",
journal = j-TSLP,
volume = "7",
number = "3",
pages = "5:1--5:??",
month = may,
year = "2011",
CODEN = "????",
DOI = "https://doi.org/10.1145/1966407.1966410",
ISSN = "1550-4875",
bibdate = "Thu Jun 2 07:47:26 MDT 2011",
bibsource = "http://portal.acm.org/;
http://www.math.utah.edu/pub/tex/bib/tslp.bib",
abstract = "This article addresses the problem of scalable
optimization for spatially-aware dialogue systems.
These kinds of systems must perceive, reason, and act
about the spatial environment where they are embedded.
We formulate the problem in terms of Semi-Markov
Decision Processes and propose a hierarchical
reinforcement learning approach to optimize
subbehaviors rather than full behaviors. Because of the
vast number of policies that are required to control
the interaction in a dynamic environment (e.g., a
dialogue system assisting a user to navigate in a
building from one location to another), our learning
approach is based on two stages: (a) the first stage
learns low-level behavior, in advance; and (b) the
second stage learns high-level behavior, in real
time.",
acknowledgement = ack-nhfb,
articleno = "5",
fjournal = "ACM Transactions on Speech and Language Processing
(TSLP)",
journal-URL = "https://dl.acm.org/loi/tslp",
}
@Article{Jurvcicek:2011:NAB,
author = "Filip Jurv{\v{c}}{\'\i}{\v{c}}ek and Blaise Thomson
and Steve Young",
title = "Natural actor and belief critic: Reinforcement
algorithm for learning parameters of dialogue systems
modelled as {POMDPs}",
journal = j-TSLP,
volume = "7",
number = "3",
pages = "6:1--6:??",
month = may,
year = "2011",
CODEN = "????",
DOI = "https://doi.org/10.1145/1966407.1966411",
ISSN = "1550-4875",
bibdate = "Thu Jun 2 07:47:26 MDT 2011",
bibsource = "http://portal.acm.org/;
http://www.math.utah.edu/pub/tex/bib/tslp.bib",
abstract = "This article presents a novel algorithm for learning
parameters in statistical dialogue systems which are
modeled as Partially Observable Markov Decision
Processes (POMDPs). The three main components of a
POMDP dialogue manager are a dialogue model
representing dialogue state information; a policy that
selects the system's responses based on the inferred
state; and a reward function that specifies the desired
behavior of the system. Ideally both the model
parameters and the policy would be designed to maximize
the cumulative reward. However, while there are many
techniques available for learning the optimal policy,
no good ways of learning the optimal model parameters
that scale to real-world dialogue systems have been
found yet.",
acknowledgement = ack-nhfb,
articleno = "6",
fjournal = "ACM Transactions on Speech and Language Processing
(TSLP)",
journal-URL = "https://dl.acm.org/loi/tslp",
}
@Article{Pietquin:2011:SEB,
author = "Olivier Pietquin and Matthieu Geist and Senthilkumar
Chandramohan and Herv{\'e} Frezza-Buet",
title = "Sample-efficient batch reinforcement learning for
dialogue management optimization",
journal = j-TSLP,
volume = "7",
number = "3",
pages = "7:1--7:??",
month = may,
year = "2011",
CODEN = "????",
DOI = "https://doi.org/10.1145/1966407.1966412",
ISSN = "1550-4875",
bibdate = "Thu Jun 2 07:47:26 MDT 2011",
bibsource = "http://portal.acm.org/;
http://www.math.utah.edu/pub/tex/bib/tslp.bib",
abstract = "Spoken Dialogue Systems (SDS) are systems which have
the ability to interact with human beings using natural
language as the medium of interaction. A dialogue
policy plays a crucial role in determining the
functioning of the dialogue management module.
Handcrafting the dialogue policy is not always an
option, considering the complexity of the dialogue task
and the stochastic behavior of users. In recent years
approaches based on Reinforcement Learning (RL) for
policy optimization in dialogue management have been
proved to be an efficient approach for dialogue policy
optimization. Yet most of the conventional RL
algorithms are data intensive and demand techniques
such as user simulation.",
acknowledgement = ack-nhfb,
articleno = "7",
fjournal = "ACM Transactions on Speech and Language Processing
(TSLP)",
journal-URL = "https://dl.acm.org/loi/tslp",
}
@Article{Gonzalez-Brenes:2011:CDH,
author = "Jos{\'e} P. Gonz{\'a}lez-Brenes and Jack Mostow",
title = "Classifying dialogue in high-dimensional space",
journal = j-TSLP,
volume = "7",
number = "3",
pages = "8:1--8:??",
month = may,
year = "2011",
CODEN = "????",
DOI = "https://doi.org/10.1145/1966407.1966413",
ISSN = "1550-4875",
bibdate = "Thu Jun 2 07:47:26 MDT 2011",
bibsource = "http://portal.acm.org/;
http://www.math.utah.edu/pub/tex/bib/tslp.bib",
abstract = "The richness of multimodal dialogue makes the space of
possible features required to describe it very large
relative to the amount of training data. However,
conventional classifier learners require large amounts
of data to avoid overfitting, or do not generalize well
to unseen examples. To learn dialogue classifiers using
a rich feature set and fewer data points than features,
we apply a recent technique, $\ell_1$-regularized
logistic regression. We demonstrate this approach
empirically on real data from Project LISTEN's Reading
Tutor, which displays a story on a computer screen and
listens to a child read aloud. We train a classifier to
predict task completion (i.e., whether the student will
finish reading the story) with 71\% accuracy on a
balanced, unseen test set.",
acknowledgement = ack-nhfb,
articleno = "8",
fjournal = "ACM Transactions on Speech and Language Processing
(TSLP)",
journal-URL = "https://dl.acm.org/loi/tslp",
}
@Article{Ai:2011:CUS,
author = "Hua Ai and Diane Litman",
title = "Comparing user simulations for dialogue strategy
learning",
journal = j-TSLP,
volume = "7",
number = "3",
pages = "9:1--9:??",
month = may,
year = "2011",
CODEN = "????",
DOI = "https://doi.org/10.1145/1966407.1966414",
ISSN = "1550-4875",
bibdate = "Thu Jun 2 07:47:26 MDT 2011",
bibsource = "http://portal.acm.org/;
http://www.math.utah.edu/pub/tex/bib/tslp.bib",
abstract = "Recent studies show that user simulations can be used
to generate training corpora for learning dialogue
strategies automatically. However, it is unclear what
type of simulation is most suitable in a particular
task setting. We observe that a simulation which
generates random behaviors in a restricted way
outperforms simulations that mimic human user behaviors
in a statistical way. Our finding suggests that we do
not always need to construct a realistic user
simulation. Since constructing realistic user
simulations is not a trivial task, we can save
engineering cost by wisely choosing simulation models
that are appropriate for our task.",
acknowledgement = ack-nhfb,
articleno = "9",
fjournal = "ACM Transactions on Speech and Language Processing
(TSLP)",
journal-URL = "https://dl.acm.org/loi/tslp",
}
@Article{Misu:2011:MSD,
author = "Teruhisa Misu and Komei Sugiura and Tatsuya Kawahara
and Kiyonori Ohtake and Chiori Hori and Hideki Kashioka
and Hisashi Kawai and Satoshi Nakamura",
title = "Modeling spoken decision support dialogue and
optimization of its dialogue strategy",
journal = j-TSLP,
volume = "7",
number = "3",
pages = "10:1--10:??",
month = may,
year = "2011",
CODEN = "????",
DOI = "https://doi.org/10.1145/1966407.1966415",
ISSN = "1550-4875",
bibdate = "Thu Jun 2 07:47:26 MDT 2011",
bibsource = "http://portal.acm.org/;
http://www.math.utah.edu/pub/tex/bib/tslp.bib",
abstract = "This article presents a user model for user simulation
and a system state representation in spoken decision
support dialogue systems. When selecting from a group
of alternatives, users apply different decision-making
criteria with different priorities. At the beginning of
the dialogue, however, users often do not have a
definite goal or criteria in which they place value,
thus they can learn about new features while
interacting with the system and accordingly create new
criteria. In this article, we present a user model and
dialogue state representation that accommodate these
patterns by considering the user's knowledge and
preferences. To estimate the parameters used in the
user model, we implemented a trial sightseeing guidance
system, collected dialogue data, and trained a user
simulator.",
acknowledgement = ack-nhfb,
articleno = "10",
fjournal = "ACM Transactions on Speech and Language Processing
(TSLP)",
journal-URL = "https://dl.acm.org/loi/tslp",
}
@Article{Potamianos:2011:ISI,
author = "Alexandros Potamianos and Diego Giuliani and Shrikanth
S. Narayanan and Kay Berkling",
title = "Introduction to the special issue on speech and
language processing of children's speech for
child-machine interaction applications",
journal = j-TSLP,
volume = "7",
number = "4",
pages = "11:1--11:??",
month = aug,
year = "2011",
CODEN = "????",
DOI = "https://doi.org/10.1145/1998384.1998385",
ISSN = "1550-4875",
bibdate = "Wed Aug 17 09:52:06 MDT 2011",
bibsource = "http://portal.acm.org/;
http://www.math.utah.edu/pub/tex/bib/tslp.bib",
acknowledgement = ack-nhfb,
articleno = "11",
fjournal = "ACM Transactions on Speech and Language Processing
(TSLP)",
journal-URL = "https://dl.acm.org/loi/tslp",
}
@Article{Wollmer:2011:TDC,
author = "Martin W{\"o}llmer and Bj{\"o}rn Schuller and Anton
Batliner and Stefan Steidl and Dino Seppi",
title = "Tandem decoding of children's speech for keyword
detection in a child-robot interaction scenario",
journal = j-TSLP,
volume = "7",
number = "4",
pages = "12:1--12:??",
month = aug,
year = "2011",
CODEN = "????",
DOI = "https://doi.org/10.1145/1998384.1998386",
ISSN = "1550-4875",
bibdate = "Wed Aug 17 09:52:06 MDT 2011",
bibsource = "http://portal.acm.org/;
http://www.math.utah.edu/pub/tex/bib/tslp.bib",
abstract = "In this article, we focus on keyword detection in
children's speech as it is needed in voice command
systems. We use the FAU Aibo Emotion Corpus which
contains emotionally colored spontaneous children's
speech recorded in a child-robot interaction scenario
and investigate various recent keyword spotting
techniques. As the principle of bidirectional Long
Short-Term Memory (BLSTM) is known to be well-suited
for context-sensitive phoneme prediction, we
incorporate a BLSTM network into a Tandem model for
flexible coarticulation modeling in children's speech.
Our experiments reveal that the Tandem model prevails
over a triphone-based Hidden Markov Model approach.",
acknowledgement = ack-nhfb,
articleno = "12",
fjournal = "ACM Transactions on Speech and Language Processing
(TSLP)",
journal-URL = "https://dl.acm.org/loi/tslp",
}
@Article{Meinedo:2011:AGD,
author = "Hugo Meinedo and Isabel Trancoso",
title = "Age and gender detection in the {I-DASH} project",
journal = j-TSLP,
volume = "7",
number = "4",
pages = "13:1--13:??",
month = aug,
year = "2011",
CODEN = "????",
DOI = "https://doi.org/10.1145/1998384.1998387",
ISSN = "1550-4875",
bibdate = "Wed Aug 17 09:52:06 MDT 2011",
bibsource = "http://portal.acm.org/;
http://www.math.utah.edu/pub/tex/bib/tslp.bib",
abstract = "This article presents a description of the INESC-ID
Age and Gender classification systems which were
developed for aiding the detection of child abuse
material within the scope of the European project
I-DASH. The Age and Gender classification systems are
composed respectively by the fusion of four and six
individual subsystems trained with short- and long-term
acoustic and prosodic features, different
classification strategies, Gaussian Mixture
Models-Universal Background Model (GMM-UBM),
Multi-Layer Perceptrons (MLP) and Support Vector
Machines (SVM), trained over five different speech
corpus. The best results obtained by the calibration
and linear logistic regression fusion back-end show an
absolute improvement of 2\% on the unweighted accuracy
value for the Age and 1\% for the Gender when compared
to the best individual frontend systems in the
development set.",
acknowledgement = ack-nhfb,
articleno = "13",
fjournal = "ACM Transactions on Speech and Language Processing
(TSLP)",
journal-URL = "https://dl.acm.org/loi/tslp",
}
@Article{Duong:2011:TMA,
author = "Minh Duong and Jack Mostow and Sunayana Sitaram",
title = "Two methods for assessing oral reading prosody",
journal = j-TSLP,
volume = "7",
number = "4",
pages = "14:1--14:??",
month = aug,
year = "2011",
CODEN = "????",
DOI = "https://doi.org/10.1145/1998384.1998388",
ISSN = "1550-4875",
bibdate = "Wed Aug 17 09:52:06 MDT 2011",
bibsource = "http://portal.acm.org/;
http://www.math.utah.edu/pub/tex/bib/tslp.bib",
abstract = "We compare two types of models to assess the prosody
of children's oral reading. Template models measure how
well the child's prosodic contour in reading a given
sentence correlates in pitch, intensity, pauses, or
word reading times with an adult narration of the same
sentence. We evaluate template models directly against
a common rubric used to assess fluency by hand, and
indirectly by their ability to predict fluency and
comprehension test scores and gains of 10 children who
used Project LISTEN's Reading Tutor; the template
models outpredict the human assessment. We also use the
same set of adult narrations to train generalized
models for mapping text to prosody, and use them to
evaluate children's prosody.",
acknowledgement = ack-nhfb,
articleno = "14",
fjournal = "ACM Transactions on Speech and Language Processing
(TSLP)",
journal-URL = "https://dl.acm.org/loi/tslp",
}
@Article{Black:2011:AAA,
author = "Matthew P. Black and Abe Kazemzadeh and Joseph
Tepperman and Shrikanth S. Narayanan",
title = "Automatically assessing the {ABCs}: Verification of
children's spoken letter-names and letter-sounds",
journal = j-TSLP,
volume = "7",
number = "4",
pages = "15:1--15:??",
month = aug,
year = "2011",
CODEN = "????",
DOI = "https://doi.org/10.1145/1998384.1998389",
ISSN = "1550-4875",
bibdate = "Wed Aug 17 09:52:06 MDT 2011",
bibsource = "http://portal.acm.org/;
http://www.math.utah.edu/pub/tex/bib/tslp.bib",
abstract = "Automatic literacy assessment is an area of research
that has shown significant progress in recent years.
Technology can be used to automatically administer
reading tasks and analyze and interpret children's
reading skills. It has the potential to transform the
classroom dynamic by providing useful information to
teachers in a repeatable, consistent, and affordable
way. While most previous research has focused on
automatically assessing children reading words and
sentences, assessments of children's earlier
foundational skills is needed. We address this problem
in this research by automatically verifying preliterate
children's pronunciations of English letter-names and
the sounds each letter represents (``letter-sounds'').
The children analyzed in this study were from a diverse
bilingual background and were recorded in actual
kindergarten to second grade classrooms.",
acknowledgement = ack-nhfb,
articleno = "15",
fjournal = "ACM Transactions on Speech and Language Processing
(TSLP)",
journal-URL = "https://dl.acm.org/loi/tslp",
}
@Article{Bolanos:2011:FFO,
author = "Daniel Bola{\~n}os and Ronald A. Cole and Wayne Ward
and Eric Borts and Edward Svirsky",
title = "{FLORA}: Fluent oral reading assessment of children's
speech",
journal = j-TSLP,
volume = "7",
number = "4",
pages = "16:1--16:??",
month = aug,
year = "2011",
CODEN = "????",
DOI = "https://doi.org/10.1145/1998384.1998390",
ISSN = "1550-4875",
bibdate = "Wed Aug 17 09:52:06 MDT 2011",
bibsource = "http://portal.acm.org/;
http://www.math.utah.edu/pub/tex/bib/tslp.bib",
abstract = "We present initial results of FLORA, an accessible
computer program that uses speech recognition to
provide an accurate measure of children's oral reading
ability. FLORA presents grade-level text passages to
children, who read the passages out loud, and computes
the number of words correct per minute (WCPM), a
standard measure of oral reading fluency. We describe
the main components of the FLORA program, including the
system architecture and the speech recognition
subsystems. We compare results of FLORA to human
scoring on 783 recordings of grade level text passages
read aloud by first through fourth grade students in
classroom settings.",
acknowledgement = ack-nhfb,
articleno = "16",
fjournal = "ACM Transactions on Speech and Language Processing
(TSLP)",
journal-URL = "https://dl.acm.org/loi/tslp",
}
@Article{Maier:2011:AVR,
author = "Andreas Maier and Flonan H{\"o}nig and Stefan Steidl
and Elmar N{\"o}th and Stefanie Horndasch and Elisabeth
Sauerh{\"o}fer and Oliver Kratz and Gunther Moll",
title = "An automatic version of a reading disorder test",
journal = j-TSLP,
volume = "7",
number = "4",
pages = "17:1--17:??",
month = aug,
year = "2011",
CODEN = "????",
DOI = "https://doi.org/10.1145/1998384.1998391",
ISSN = "1550-4875",
bibdate = "Wed Aug 17 09:52:06 MDT 2011",
bibsource = "http://portal.acm.org/;
http://www.math.utah.edu/pub/tex/bib/tslp.bib",
abstract = "We present a novel system to automatically diagnose
reading disorders. The system is based on a speech
recognition engine with a module for prosodic analysis.
The reading disorder test is based on eight different
subtests. In each of the subtests, the system achieves
a recognition accuracy of at least 95\%. As in the
perceptual version of the test, the results of the
subtests are then joined into a final test result to
determine whether the child has a reading disorder. In
the final classification stage, the system identifies
98.3\% of the 120 children correctly.",
acknowledgement = ack-nhfb,
articleno = "17",
fjournal = "ACM Transactions on Speech and Language Processing
(TSLP)",
journal-URL = "https://dl.acm.org/loi/tslp",
}
@Article{Ward:2011:MST,
author = "Wayne Ward and Ronald Cole and Daniel Bola{\~n}os and
Cindy Buchenroth-Martin and Edward Svirsky and Sarel
{Van Vuuren} and Timothy Weston and Jing Zheng and Lee
Becker",
title = "My science tutor: {A} conversational multimedia
virtual tutor for elementary school science",
journal = j-TSLP,
volume = "7",
number = "4",
pages = "18:1--18:??",
month = aug,
year = "2011",
CODEN = "????",
DOI = "https://doi.org/10.1145/1998384.1998392",
ISSN = "1550-4875",
bibdate = "Wed Aug 17 09:52:06 MDT 2011",
bibsource = "http://portal.acm.org/;
http://www.math.utah.edu/pub/tex/bib/tslp.bib",
abstract = "This article describes My Science Tutor (MyST), an
intelligent tutoring system designed to improve science
learning by students in 3rd, 4th, and 5th grades (7 to
11 years old) through conversational dialogs with a
virtual science tutor. In our study, individual
students engage in spoken dialogs with the virtual
tutor Marni during 15 to 20 minute sessions following
classroom science investigations to discuss and extend
concepts embedded in the investigations. The spoken
dialogs in MyST are designed to scaffold learning by
presenting open-ended questions accompanied by
illustrations or animations related to the classroom
investigations and the science concepts being learned.
The focus of the interactions is to elicit
self-expression from students.",
acknowledgement = ack-nhfb,
articleno = "18",
fjournal = "ACM Transactions on Speech and Language Processing
(TSLP)",
journal-URL = "https://dl.acm.org/loi/tslp",
}
@Article{Turunen:2011:SRU,
author = "Ville T. Turunen and Mikko Kurimo",
title = "Speech retrieval from unsegmented {Finnish} audio
using statistical morpheme-like units for segmentation,
recognition, and retrieval",
journal = j-TSLP,
volume = "8",
number = "1",
pages = "1:1--1:??",
month = oct,
year = "2011",
CODEN = "????",
DOI = "https://doi.org/10.1145/2036916.2036917",
ISSN = "1550-4875",
bibdate = "Thu Dec 15 08:44:09 MST 2011",
bibsource = "http://portal.acm.org/;
http://www.math.utah.edu/pub/tex/bib/tslp.bib",
acknowledgement = ack-nhfb,
articleno = "1",
fjournal = "ACM Transactions on Speech and Language Processing
(TSLP)",
journal-URL = "https://dl.acm.org/loi/tslp",
}
@Article{Hassan:2011:LIE,
author = "Samer Hassan and Rada Mihalcea",
title = "Learning to identify educational materials",
journal = j-TSLP,
volume = "8",
number = "2",
pages = "2:1--2:??",
month = nov,
year = "2011",
CODEN = "????",
DOI = "https://doi.org/10.1145/2050100.2050101",
ISSN = "1550-4875",
bibdate = "Thu Dec 15 08:44:09 MST 2011",
bibsource = "http://portal.acm.org/;
http://www.math.utah.edu/pub/tex/bib/tslp.bib",
acknowledgement = ack-nhfb,
articleno = "2",
fjournal = "ACM Transactions on Speech and Language Processing
(TSLP)",
journal-URL = "https://dl.acm.org/loi/tslp",
}
@Article{Peirsman:2011:SRB,
author = "Yves Peirsman and Sebastian Pad{\'o}",
title = "Semantic relations in bilingual lexicons",
journal = j-TSLP,
volume = "8",
number = "2",
pages = "3:1--3:??",
month = nov,
year = "2011",
CODEN = "????",
DOI = "https://doi.org/10.1145/2050100.2050102",
ISSN = "1550-4875",
bibdate = "Thu Dec 15 08:44:09 MST 2011",
bibsource = "http://portal.acm.org/;
http://www.math.utah.edu/pub/tex/bib/tslp.bib",
acknowledgement = ack-nhfb,
articleno = "3",
fjournal = "ACM Transactions on Speech and Language Processing
(TSLP)",
journal-URL = "https://dl.acm.org/loi/tslp",
}
@Article{Kordjamshidi:2011:SRL,
author = "Parisa Kordjamshidi and Martijn {Van Otterlo} and
Marie-Francine Moens",
title = "Spatial role labeling: {Towards} extraction of spatial
relations from natural language",
journal = j-TSLP,
volume = "8",
number = "3",
pages = "4:1--4:??",
month = dec,
year = "2011",
CODEN = "????",
DOI = "https://doi.org/10.1145/2050104.2050105",
ISSN = "1550-4875",
bibdate = "Thu Dec 15 08:44:09 MST 2011",
bibsource = "http://portal.acm.org/;
http://www.math.utah.edu/pub/tex/bib/tslp.bib",
abstract = "This article reports on the novel task of spatial role
labeling in natural language text. It proposes machine
learning methods to extract spatial roles and their
relations. This work experiments with both a step-wise
approach, where spatial prepositions are found and the
related trajectors, and landmarks are then extracted,
and a joint learning approach, where a spatial relation
and its composing indicator, trajector, and landmark
are classified collectively. Context-dependent learning
techniques, such as a skip-chain conditional random
field, yield good results on the GUM-evaluation
(Maptask) data and CLEF-IAPR TC-12 Image Benchmark.",
acknowledgement = ack-nhfb,
articleno = "4",
fjournal = "ACM Transactions on Speech and Language Processing
(TSLP)",
journal-URL = "https://dl.acm.org/loi/tslp",
}
@Article{Zhu:2012:UBA,
author = "Jingbo Zhu and Matthew Ma",
title = "Uncertainty-based active learning with instability
estimation for text classification",
journal = j-TSLP,
volume = "8",
number = "4",
pages = "5:1--5:??",
month = feb,
year = "2012",
CODEN = "????",
DOI = "https://doi.org/10.1145/2093153.2093154",
ISSN = "1550-4875",
bibdate = "Wed Feb 15 18:13:35 MST 2012",
bibsource = "http://portal.acm.org/;
http://www.math.utah.edu/pub/tex/bib/tslp.bib",
abstract = "This article deals with pool-based active learning
with uncertainty sampling. While existing uncertainty
sampling methods emphasize selection of instances near
the decision boundary to increase the likelihood of
selecting informative examples, our position is that
this heuristic is a surrogate for selecting examples
for which the current learning algorithm iteration is
likely to misclassify. To more directly model this
intuition, this article augments such uncertainty
sampling methods and proposes a simple
instability-based selective sampling approach to
improving uncertainty-based active learning, in which
the instability degree of each unlabeled example is
estimated during the learning process. Experiments on
seven evaluation datasets show that instability-based
sampling methods can achieve significant improvements
over the traditional uncertainty sampling method.",
acknowledgement = ack-nhfb,
articleno = "5",
fjournal = "ACM Transactions on Speech and Language Processing
(TSLP)",
journal-URL = "https://dl.acm.org/loi/tslp",
}
@Article{Zhang:2012:ALS,
author = "Justin Jian Zhang and Pascale Fung",
title = "Active learning with semi-automatic annotation for
extractive speech summarization",
journal = j-TSLP,
volume = "8",
number = "4",
pages = "6:1--6:??",
month = feb,
year = "2012",
CODEN = "????",
DOI = "https://doi.org/10.1145/2093153.2093155",
ISSN = "1550-4875",
bibdate = "Wed Feb 15 18:13:35 MST 2012",
bibsource = "http://portal.acm.org/;
http://www.math.utah.edu/pub/tex/bib/tslp.bib",
abstract = "We propose using active learning for extractive speech
summarization in order to reduce human effort in
generating reference summaries. Active learning chooses
a selective set of samples to be labeled. We propose a
combination of informativeness and representativeness
criteria for selection. We further propose a
semi-automatic method to generate reference summaries
for presentation speech by using Relaxed Dynamic Time
Warping (RDTW) alignment between presentation speech
and its accompanied slides. Our summarization results
show that the amount of labeled data needed for a given
summarization accuracy can be reduced by more than
23\% compared to random sampling.",
acknowledgement = ack-nhfb,
articleno = "6",
fjournal = "ACM Transactions on Speech and Language Processing
(TSLP)",
journal-URL = "https://dl.acm.org/loi/tslp",
}
@Article{Raux:2012:OTT,
author = "Antoine Raux and Maxine Eskenazi",
title = "Optimizing the turn-taking behavior of task-oriented
spoken dialog systems",
journal = j-TSLP,
volume = "9",
number = "1",
pages = "1:1--1:??",
month = may,
year = "2012",
CODEN = "????",
DOI = "https://doi.org/10.1145/2168748.2168749",
ISSN = "1550-4875",
bibdate = "Tue May 15 16:57:47 MDT 2012",
bibsource = "http://portal.acm.org/;
http://www.math.utah.edu/pub/tex/bib/tslp.bib",
abstract = "Even as progress in speech technologies and task and
dialog modeling has allowed the development of advanced
spoken dialog systems, the low-level interaction
behavior of those systems often remains rigid and
inefficient. Based on an analysis of human-human and
human-computer turn-taking in naturally occurring
task-oriented dialogs, we define a set of features that
can be automatically extracted and show that they can
be used to inform efficient end-of-turn detection. We
then frame turn-taking as decision making under
uncertainty and describe the Finite-State Turn-Taking
Machine (FSTTM), a decision-theoretic model that
combines data-driven machine learning methods and a
cost structure derived from Conversation Analysis to
control the turn-taking behavior of dialog systems.
Evaluation results on CMU Let's Go, a publicly deployed
bus information system, confirm that the FSTTM
significantly improves the responsiveness of the system
compared to a standard threshold-based approach, as
well as previous data-driven methods.",
acknowledgement = ack-nhfb,
articleno = "1",
fjournal = "ACM Transactions on Speech and Language Processing
(TSLP)",
journal-URL = "https://dl.acm.org/loi/tslp",
}
@Article{Abdalgader:2012:USB,
author = "Khaled Abdalgader and Andrew Skabar",
title = "Unsupervised similarity-based word sense
disambiguation using context vectors and sentential
word importance",
journal = j-TSLP,
volume = "9",
number = "1",
pages = "2:1--2:??",
month = may,
year = "2012",
CODEN = "????",
DOI = "https://doi.org/10.1145/2168748.2168750",
ISSN = "1550-4875",
bibdate = "Tue May 15 16:57:47 MDT 2012",
bibsource = "http://portal.acm.org/;
http://www.math.utah.edu/pub/tex/bib/tslp.bib",
abstract = "The process of identifying the actual meanings of
words in a given text fragment has a long history in
the field of computational linguistics. Due to its
importance in understanding the semantics of natural
language, it is considered one of the most challenging
problems facing this field. In this article we propose
a new unsupervised similarity-based word sense
disambiguation (WSD) algorithm that operates by
computing the semantic similarity between glosses of
the target word and a context vector. The sense of the
target word is determined as that for which the
similarity between gloss and context vector is
greatest. Thus, whereas conventional unsupervised WSD
methods are based on measuring pairwise similarity
between words, our approach is based on measuring
semantic similarity between sentences. This enables it
to utilize a higher degree of semantic information, and
is more consistent with the way that human beings
disambiguate; that is, by considering the greater
context in which the word appears. We also show how
performance can be further improved by incorporating a
preliminary step in which the relative importance of
words within the original text fragment is estimated,
thereby providing an ordering that can be used to
determine the sequence in which words should be
disambiguated. We provide empirical results that show
that our method performs favorably against the
state-of-the-art unsupervised word sense disambiguation
methods, as evaluated on several benchmark datasets
through different models of evaluation.",
acknowledgement = ack-nhfb,
articleno = "2",
fjournal = "ACM Transactions on Speech and Language Processing
(TSLP)",
journal-URL = "https://dl.acm.org/loi/tslp",
}
@Article{Bouayad-Agha:2012:POG,
author = "Nadjet Bouayad-Agha and Gerard Casamayor and Simon
Mille and Leo Wanner",
title = "Perspective-oriented generation of football match
summaries: old tasks, new challenges",
journal = j-TSLP,
volume = "9",
number = "2",
pages = "3:1--3:??",
month = jul,
year = "2012",
CODEN = "????",
DOI = "https://doi.org/10.1145/2287710.2287711",
ISSN = "1550-4875",
bibdate = "Tue Jul 31 17:49:24 MDT 2012",
bibsource = "http://portal.acm.org/;
http://www.math.utah.edu/pub/tex/bib/tslp.bib",
abstract = "Team sports commentaries call for techniques that are
able to select content and generate wordings to reflect
the affinity of the targeted reader for one of the
teams. The existing works tend to have in common that
they either start from knowledge sources of limited
size to whose structures then different ways of
realization are explicitly assigned, or they work
directly with linguistic corpora, without the use of a
deep knowledge source. With the increasing availability
of large-scale ontologies this is no longer
satisfactory: techniques are needed that are applicable
to general purpose ontologies, but which still take
user preferences into account. We take the best of both
worlds in that we use a two-layer ontology. The first
layer is composed of raw domain data modelled in an
application-independent base OWL ontology. The second
layer contains a rich perspective generation-motivated
domain communication knowledge ontology, inferred from
the base ontology. The two-layer ontology allows us to
take into account user perspective-oriented criteria at
different stages of generation to generate
perspective-oriented commentaries. We show how content
selection, discourse structuring, information structure
determination, and lexicalization are driven by these
criteria and how stage after stage a truly user
perspective-tailored summary is generated. The
viability of our proposal has been evaluated for the
generation of football match summaries of the First
Spanish Football League. The reported outcome of the
evaluation demonstrates that we are on the right
track.",
acknowledgement = ack-nhfb,
articleno = "3",
fjournal = "ACM Transactions on Speech and Language Processing
(TSLP)",
journal-URL = "https://dl.acm.org/loi/tslp",
}
@Article{Sakti:2012:DST,
author = "Sakriani Sakti and Michael Paul and Andrew Finch and
Xinhui Hu and Jinfu Ni and Noriyuki Kimura and Shigeki
Matsuda and Chiori Hori and Yutaka Ashikari and Hisashi
Kawai and Hideki Kashioka and Eiichiro Sumita and
Satoshi Nakamura",
title = "Distributed speech translation technologies for
multiparty multilingual communication",
journal = j-TSLP,
volume = "9",
number = "2",
pages = "4:1--4:??",
month = jul,
year = "2012",
CODEN = "????",
DOI = "https://doi.org/10.1145/2287710.2287712",
ISSN = "1550-4875",
bibdate = "Tue Jul 31 17:49:24 MDT 2012",
bibsource = "http://portal.acm.org/;
http://www.math.utah.edu/pub/tex/bib/tslp.bib",
abstract = "Developing a multilingual speech translation system
requires efforts in constructing automatic speech
recognition (ASR), machine translation (MT), and
text-to-speech synthesis (TTS) components for all
possible source and target languages. If the numerous
ASR, MT, and TTS systems for different language pairs
developed independently in different parts of the world
could be connected, multilingual speech translation
systems for a multitude of language pairs could be
achieved. Yet, there is currently no common, flexible
framework that can provide an entire speech translation
process by bringing together heterogeneous speech
translation components. In this article we therefore
propose a distributed architecture framework for
multilingual speech translation in which all speech
translation components are provided on distributed
servers and cooperate over a network. This framework
can facilitate the connection of different components
and functions. To show the overall mechanism, we first
present our state-of-the-art technologies for
multilingual ASR, MT, and TTS components, and then
describe how to combine those systems into the proposed
network-based framework. The client applications are
implemented on a handheld mobile terminal device, and
all data exchanges among client users and spoken
language technology servers are managed through a Web
protocol. To support multiparty communication, an
additional communication server is provided for
simultaneously distributing the speech translation
results from one user to multiple users. Field testing
shows that the system is capable of realizing
multiparty multilingual speech translation for
real-time and location-independent communication.",
acknowledgement = ack-nhfb,
articleno = "4",
fjournal = "ACM Transactions on Speech and Language Processing
(TSLP)",
journal-URL = "https://dl.acm.org/loi/tslp",
}
@Article{Narendra:2012:SSU,
author = "N. P. Narendra and K. Sreenivasa Rao",
title = "Syllable Specific Unit Selection Cost Functions for
Text-to-Speech Synthesis",
journal = j-TSLP,
volume = "9",
number = "3",
pages = "5:1--5:??",
month = nov,
year = "2012",
CODEN = "????",
DOI = "https://doi.org/10.1145/2382434.2382435",
ISSN = "1550-4875",
bibdate = "Tue Nov 20 18:42:07 MST 2012",
bibsource = "http://portal.acm.org/;
http://www.math.utah.edu/pub/tex/bib/tslp.bib",
abstract = "This paper presents the design and development of
syllable specific unit selection cost functions for
improving the quality of text-to-speech synthesis.
Appropriate unit selection cost functions, namely
concatenation cost and target cost, are proposed for
syllable based synthesis. Concatenation costs are
defined based on the type of segments present at the
syllable joins. Proposed concatenation costs have shown
significant reduction in perceptual discontinuity at
syllable joins. Three-stage target cost formulation is
proposed for selecting appropriate units from database.
Subjective evaluation has shown improvement in the
quality of speech at each stage.",
acknowledgement = ack-nhfb,
articleno = "5",
fjournal = "ACM Transactions on Speech and Language Processing
(TSLP)",
journal-URL = "https://dl.acm.org/loi/tslp",
}
@Article{Rentoumi:2012:IML,
author = "Vassiliki Rentoumi and George A. Vouros and Vangelis
Karkaletsis and Amalia Moser",
title = "Investigating Metaphorical Language in Sentiment
Analysis: a Sense-to-Sentiment Perspective",
journal = j-TSLP,
volume = "9",
number = "3",
pages = "6:1--6:??",
month = nov,
year = "2012",
CODEN = "????",
DOI = "https://doi.org/10.1145/2382434.2382436",
ISSN = "1550-4875",
bibdate = "Tue Nov 20 18:42:07 MST 2012",
bibsource = "http://portal.acm.org/;
http://www.math.utah.edu/pub/tex/bib/tslp.bib",
abstract = "Intuition dictates that figurative language and
especially metaphorical expressions should convey
sentiment. It is the aim of this work to validate this
intuition by showing that figurative language
(metaphors) appearing in a sentence drive the polarity
of that sentence. Towards this target, the current
article proposes an approach for sentiment analysis of
sentences where figurative language plays a dominant
role. This approach applies Word Sense Disambiguation
aiming to assign polarity to word senses rather than
tokens. Sentence polarity is determined using the
individual polarities for metaphorical senses as well
as other contextual information. Experimental
evaluation shows that the proposed method achieves high
scores in comparison with other state-of-the-art
approaches tested on the same corpora. Finally,
experimental results provide supportive evidence that
this method is also well suited for corpora consisting
of literal and figurative language sentences.",
acknowledgement = ack-nhfb,
articleno = "6",
fjournal = "ACM Transactions on Speech and Language Processing
(TSLP)",
journal-URL = "https://dl.acm.org/loi/tslp",
}
@Article{Corazza:2013:ITM,
author = "Anna Corazza and Alberto Lavelli and Giorgio Satta",
title = "An information-theoretic measure to evaluate parsing
difficulty across treebanks",
journal = j-TSLP,
volume = "9",
number = "4",
pages = "7:1--7:??",
month = jan,
year = "2013",
CODEN = "????",
DOI = "https://doi.org/10.1145/2407736.2407737",
ISSN = "1550-4875",
bibdate = "Wed Mar 20 06:19:16 MDT 2013",
bibsource = "http://portal.acm.org/;
http://www.math.utah.edu/pub/tex/bib/tslp.bib",
abstract = "With the growing interest in statistical parsing,
special attention has recently been devoted to the
problem of comparing different treebanks to assess
which languages or domains are more difficult to parse
relative to a given model. A common methodology for
comparing parsing difficulty across treebanks is based
on the use of the standard labeled precision and recall
measures. As an alternative, in this article we propose
an information-theoretic measure, called the expected
conditional cross-entropy (ECC). One important
advantage with respect to standard performance measures
is that ECC can be directly expressed as a function of
the parameters of the model. We evaluate ECC across
several treebanks for English, French, German, and
Italian, and show that ECC is an effective measure of
parsing difficulty, with an increase in ECC always
accompanied by a degradation in parsing accuracy.",
acknowledgement = ack-nhfb,
articleno = "7",
fjournal = "ACM Transactions on Speech and Language Processing
(TSLP)",
journal-URL = "https://dl.acm.org/loi/tslp",
}
@Article{Zhang:2013:CAL,
author = "Li Zhang",
title = "Contextual and active learning-based affect-sensing
from virtual drama improvisation",
journal = j-TSLP,
volume = "9",
number = "4",
pages = "8:1--8:??",
month = jan,
year = "2013",
CODEN = "????",
DOI = "https://doi.org/10.1145/2407736.2407738",
ISSN = "1550-4875",
bibdate = "Wed Mar 20 06:19:16 MDT 2013",
bibsource = "http://portal.acm.org/;
http://www.math.utah.edu/pub/tex/bib/tslp.bib",
abstract = "Affect interpretation from open-ended drama
improvisation is a challenging task. This article
describes experiments in using latent semantic analysis
to identify discussion themes and potential target
audiences for those improvisational inputs without
strong affect indicators. A context-based
affect-detection is also implemented using a supervised
neural network with the consideration of emotional
contexts of most intended audiences, sentence types,
and interpersonal relationships. In order to go beyond
the constraints of predefined scenarios and improve the
system's robustness, min-margin-based active learning
is implemented. This active learning algorithm also
shows great potential in dealing with imbalanced affect
classifications. Evaluation results indicated that the
context-based affect detection achieved an averaged
precision of 0.826 and an averaged recall of 0.813 for
affect detection of the test inputs from the Crohn's
disease scenario using three emotion labels: positive,
negative, and neutral, and an averaged precision of
0.868 and an average recall of 0.876 for the test
inputs from the school bullying scenario. Moreover,
experimental evaluation on a benchmark data set for
active learning demonstrated that active learning was
able to greatly reduce human annotation efforts for the
training of affect detection, and also showed promising
robustness in dealing with open-ended example inputs
beyond the improvisation of the chosen scenarios.",
acknowledgement = ack-nhfb,
articleno = "8",
fjournal = "ACM Transactions on Speech and Language Processing
(TSLP)",
journal-URL = "https://dl.acm.org/loi/tslp",
}
@Article{Duh:2013:MID,
author = "Kevin Duh and Ching-Man Au Yeung and Tomoharu Iwata
and Masaaki Nagata",
title = "Managing information disparity in multilingual
document collections",
journal = j-TSLP,
volume = "10",
number = "1",
pages = "1:1--1:??",
month = mar,
year = "2013",
CODEN = "????",
ISSN = "1550-4875",
bibdate = "Wed Mar 20 06:19:18 MDT 2013",
bibsource = "http://portal.acm.org/;
http://www.math.utah.edu/pub/tex/bib/tslp.bib",
abstract = "Information disparity is a major challenge with
multilingual document collections. When documents are
dynamically updated in a distributed fashion,
information content among different language editions
may gradually diverge. We propose a framework for
assisting human editors to manage this information
disparity, using tools from machine translation and
machine learning. Given source and target documents in
two different languages, our system automatically
identifies information nuggets that are new with
respect to the target and suggests positions to place
their translations. We perform both real-world
experiments and large-scale simulations on Wikipedia
documents and conclude our system is effective in a
variety of scenarios.",
acknowledgement = ack-nhfb,
articleno = "1",
fjournal = "ACM Transactions on Speech and Language Processing
(TSLP)",
journal-URL = "https://dl.acm.org/loi/tslp",
}
@Article{Zhang:2013:TCL,
author = "Renxian Zhang and Wenjie Li and Dehong Gao",
title = "Towards content-level coherence with aspect-guided
summarization",
journal = j-TSLP,
volume = "10",
number = "1",
pages = "2:1--2:??",
month = mar,
year = "2013",
CODEN = "????",
ISSN = "1550-4875",
bibdate = "Wed Mar 20 06:19:18 MDT 2013",
bibsource = "http://portal.acm.org/;
http://www.math.utah.edu/pub/tex/bib/tslp.bib",
abstract = "The TAC 2010 summarization track initiated a new
task-aspect-guided summarization-that centers on
textual aspects embodied as particular kinds of
information of a text. We observe that aspect-guided
summaries not only address highly specific user need,
but also facilitate content-level coherence by using
aspect information. In this article, we present a
full-fledged approach to aspect-guided summarization
with a focus on summary coherence. Our summarization
approach depends on two prerequisite subtasks:
recognizing aspect-bearing sentences in order to do
sentence extraction, and modeling aspect-based
coherence with an HMM model in order to predict a
coherent sentence ordering. Using the manually
annotated TAC 2010 and 2010 datasets, we validated the
effectiveness of our proposed methods for those
subtasks. Drawing on the empirical results, we proceed
to develop an aspect-guided summarizer based on a
simple but robust base summarizer. With sentence
selection guided by aspect information, our system is
one of the best on TAC 2011. With sentence ordering
predicted by the aspect-based HMM model, the summaries
achieve good coherence.",
acknowledgement = ack-nhfb,
articleno = "2",
fjournal = "ACM Transactions on Speech and Language Processing
(TSLP)",
journal-URL = "https://dl.acm.org/loi/tslp",
}
@Article{Ramisch:2013:ISI,
author = "Carlos Ramisch and Aline Villavicencio and Valia
Kordoni",
title = "Introduction to the special issue on multiword
expressions: From theory to practice and use",
journal = j-TSLP,
volume = "10",
number = "2",
pages = "3:1--3:??",
month = jun,
year = "2013",
CODEN = "????",
DOI = "https://doi.org/10.1145/2483691.2483692",
ISSN = "1550-4875",
bibdate = "Mon Jul 1 18:16:29 MDT 2013",
bibsource = "http://portal.acm.org/;
http://www.math.utah.edu/pub/tex/bib/tslp.bib",
abstract = "We are in 2013, and multiword expressions have been
around for a while in the computational linguistics
research community. Since the first ACL workshop on
MWEs 12 years ago in Sapporo, Japan, much has been
discussed, proposed, experimented, evaluated and argued
about MWEs. And yet, they deserve the publication of a
whole special issue of the ACM Transactions on Speech
and Language Processing. But what is it about multiword
expressions that keeps them in fashion? Who are the
people and the institutions who perform and publish
groundbreaking fundamental and applied research in this
field? What is the place and the relevance of our
lively research community in the bigger picture of
computational linguistics? Where do we come from as a
community, and most importantly, where are we heading?
In this introductory article, we share our point of
view about the answers to these questions and introduce
the articles that compose the current special issue.",
acknowledgement = ack-nhfb,
articleno = "3",
fjournal = "ACM Transactions on Speech and Language Processing
(TSLP)",
journal-URL = "https://dl.acm.org/loi/tslp",
}
@Article{Church:2013:HMM,
author = "Kenneth Church",
title = "How many multiword expressions do people know?",
journal = j-TSLP,
volume = "10",
number = "2",
pages = "4:1--4:??",
month = jun,
year = "2013",
CODEN = "????",
DOI = "https://doi.org/10.1145/2483691.2483693",
ISSN = "1550-4875",
bibdate = "Mon Jul 1 18:16:29 MDT 2013",
bibsource = "http://portal.acm.org/;
http://www.math.utah.edu/pub/tex/bib/tslp.bib",
abstract = "What is a multiword expression (MWE) and how many are
there? Mark Liberman gave a great invited talk at
ACL-89, titled ``How Many Words Do People Know?'' where
he spent the entire hour questioning the question. Many
of the same questions apply to multiword expressions.
What is a word? An expression? What is many? What is a
person? What does it mean to know? Rather than answer
these questions, this article will use them as Liberman
did, as an excuse for surveying how such issues are
addressed in a variety of fields: computer science, Web
search, linguistics, lexicography, educational testing,
psychology, statistics, and so on.",
acknowledgement = ack-nhfb,
articleno = "4",
fjournal = "ACM Transactions on Speech and Language Processing
(TSLP)",
journal-URL = "https://dl.acm.org/loi/tslp",
}
@Article{Davis:2013:LSF,
author = "Anthony R. Davis and Leslie Barrett",
title = "Lexical semantic factors in the acceptability of
{English} support-verb-nominalization constructions",
journal = j-TSLP,
volume = "10",
number = "2",
pages = "5:1--5:??",
month = jun,
year = "2013",
CODEN = "????",
DOI = "https://doi.org/10.1145/2483691.2483694",
ISSN = "1550-4875",
bibdate = "Mon Jul 1 18:16:29 MDT 2013",
bibsource = "http://portal.acm.org/;
http://www.math.utah.edu/pub/tex/bib/tslp.bib",
abstract = "We explore the properties of support-verb and
nominalization (SVN) pairs in English, a type of
multiword expression in which a semantically
impoverished verb combines with a complement
nominalization sharing an unexpressed role with the
verb. This study follows others in seeking syntactic or
lexical semantic factors correlated with the
acceptability of these constructions. In particular,
following recent work showing certain semantic verb
class features to improve SVN classification [Tu and
Roth 2011], we explore the possibility that support
verbs and the verbal roots of nominalizations in
acceptable SVN pairs are clustered according to the
classes of Levin [1993]. We compare the compatibility
correlation of these results with those of the
Aktionsart-class-based proposal of Barrett and Davis
[2002]. We find the evidence that Levin classes are a
factor in the acceptability of SVN constructions to be
equivocal, and conclude with a discussion of the
reasons for this finding.",
acknowledgement = ack-nhfb,
articleno = "5",
fjournal = "ACM Transactions on Speech and Language Processing
(TSLP)",
journal-URL = "https://dl.acm.org/loi/tslp",
}
@Article{Vincze:2013:LDE,
author = "Veronika Vincze and Istv{\'a}n Nagy T. and J{\'a}nos
Zsibrita",
title = "Learning to detect {English} and {Hungarian} light
verb constructions",
journal = j-TSLP,
volume = "10",
number = "2",
pages = "6:1--6:??",
month = jun,
year = "2013",
CODEN = "????",
DOI = "https://doi.org/10.1145/2483691.2483695",
ISSN = "1550-4875",
bibdate = "Mon Jul 1 18:16:29 MDT 2013",
bibsource = "http://portal.acm.org/;
http://www.math.utah.edu/pub/tex/bib/tslp.bib",
abstract = "Light verb constructions consist of a verbal and a
nominal component, where the noun preserves its
original meaning while the verb has lost it (to some
degree). They are syntactically flexible and their
meaning can only be partially computed on the basis of
the meaning of their parts, thus they require special
treatment in natural language processing. For this
purpose, the first step is to identify light verb
constructions. In this study, we present our
conditional random fields-based tool-called
FXTagger-for identifying light verb constructions. The
flexibility of the tool is demonstrated on two,
typologically different, languages, namely, English and
Hungarian. As earlier studies labeled different
linguistic phenomena as light verb constructions, we
first present a linguistics-based classification of
light verb constructions and then show that FXTagger is
able to identify different classes of light verb
constructions in both languages. Different types of
texts may contain different types of light verb
constructions; moreover, the frequency of light verb
constructions may differ from domain to domain. Hence
we focus on the portability of models trained on
different corpora, and we also investigate the effect
of simple domain adaptation techniques to reduce the
gap between the domains. Our results show that in spite
of domain specificities, out-domain data can also
contribute to the successful LVC detection in all
domains.",
acknowledgement = ack-nhfb,
articleno = "6",
fjournal = "ACM Transactions on Speech and Language Processing
(TSLP)",
journal-URL = "https://dl.acm.org/loi/tslp",
}
@Article{Nissim:2013:MIV,
author = "Malvina Nissim and Andrea Zaninello",
title = "Modeling the internal variability of multiword
expressions through a pattern-based method",
journal = j-TSLP,
volume = "10",
number = "2",
pages = "7:1--7:??",
month = jun,
year = "2013",
CODEN = "????",
DOI = "https://doi.org/10.1145/2483691.2483696",
ISSN = "1550-4875",
bibdate = "Mon Jul 1 18:16:29 MDT 2013",
bibsource = "http://portal.acm.org/;
http://www.math.utah.edu/pub/tex/bib/tslp.bib",
abstract = "The issue of internal variability of multiword
expressions (MWEs) is crucial towards their
identification and extraction in running text. We
present a corpus-supported and computational study on
Italian MWEs, aimed at defining an automatic method for
modeling internal variation, exploiting frequency and
part-of-speech (POS) information. We do so by deriving
an XML-encoded lexicon of MWEs based on a manually
compiled dictionary, which is then projected onto a a
large corpus. Since a search for fixed forms suffers
from low recall, while an unconstrained flexible search
for lemmas yields a loss in precision, we suggest a
procedure aimed at maximizing precision in the
identification of MWEs within a flexible search. Our
method builds on the idea that internal variability can
be modelled via the novel introduction of variation
patterns, which work over POS patterns, and can be used
as working tools for controlling precision. We also
compare the performance of variation patterns to that
of association measures, and explore the possibility of
using variation patterns in MWE extraction in addition
to identification. Finally, we suggest that
corpus-derived, pattern-related information can be
included in the original MWE lexicon by means of an
enriched coding and the creation of an XML-based
repository of patterns.",
acknowledgement = ack-nhfb,
articleno = "7",
fjournal = "ACM Transactions on Speech and Language Processing
(TSLP)",
journal-URL = "https://dl.acm.org/loi/tslp",
}
@Article{Anonymous:2013:R,
author = "Anonymous",
title = "Reviewers",
journal = j-TSLP,
volume = "10",
number = "2",
pages = "8:1--8:??",
month = jun,
year = "2013",
CODEN = "????",
DOI = "https://doi.org/10.1145/2483691.2499382",
ISSN = "1550-4875",
bibdate = "Mon Jul 1 18:16:29 MDT 2013",
bibsource = "http://portal.acm.org/;
http://www.math.utah.edu/pub/tex/bib/tslp.bib",
acknowledgement = ack-nhfb,
articleno = "8",
fjournal = "ACM Transactions on Speech and Language Processing
(TSLP)",
journal-URL = "https://dl.acm.org/loi/tslp",
}
@Article{Constant:2013:CCR,
author = "Matthieu Constant and Joseph {Le Roux} and Anthony
Sigogne",
title = "Combining compound recognition and {PCFG--LA} parsing
with word lattices and conditional random fields",
journal = j-TSLP,
volume = "10",
number = "3",
pages = "8:1--8:??",
month = jul,
year = "2013",
CODEN = "????",
DOI = "https://doi.org/10.1145/2483969.2483970",
ISSN = "1550-4875",
bibdate = "Mon Jul 8 17:25:06 MDT 2013",
bibsource = "http://portal.acm.org/;
http://www.math.utah.edu/pub/tex/bib/tslp.bib",
abstract = "The integration of compounds in a parsing procedure
has been shown to improve accuracy in an artificial
context where such expressions have been perfectly
preidentified. This article evaluates two empirical
strategies to incorporate such multiword units in a
real PCFG-LA parsing context: (1) the use of a grammar
including compound recognition, thanks to specialized
annotation schemes for compounds; (2) the use of a
state-of-the-art discriminative compound prerecognizer
integrating endogenous and exogenous features. We show
how these two strategies can be combined with word
lattices representing possible lexical analyses
generated by the recognizer. The proposed systems
display significant gains in terms of multiword
recognition and often in terms of standard parsing
accuracy. Moreover, we show through an Oracle analysis
that this combined strategy opens promising new
research directions.",
acknowledgement = ack-nhfb,
articleno = "8",
fjournal = "ACM Transactions on Speech and Language Processing
(TSLP)",
journal-URL = "https://dl.acm.org/loi/tslp",
}
@Article{Kim:2013:WSS,
author = "Su Nam Kim and Timothy Baldwin",
title = "Word sense and semantic relations in noun compounds",
journal = j-TSLP,
volume = "10",
number = "3",
pages = "9:1--9:??",
month = jul,
year = "2013",
CODEN = "????",
DOI = "https://doi.org/10.1145/2483969.2483971",
ISSN = "1550-4875",
bibdate = "Mon Jul 8 17:25:06 MDT 2013",
bibsource = "http://portal.acm.org/;
http://www.math.utah.edu/pub/tex/bib/tslp.bib",
abstract = "In this article, we investigate word sense
distributions in noun compounds (NCs). Our primary goal
is to disambiguate the word sense of component words in
NCs, based on investigation of ``semantic collocation''
between them. We use sense collocation and lexical
substitution to build supervised and unsupervised word
sense disambiguation (WSD) classifiers, and show our
unsupervised learner to be superior to a benchmark WSD
system. Further, we develop a word sense-based approach
to interpreting the semantic relations in NCs.",
acknowledgement = ack-nhfb,
articleno = "9",
fjournal = "ACM Transactions on Speech and Language Processing
(TSLP)",
journal-URL = "https://dl.acm.org/loi/tslp",
}
@Article{Lau:2013:CTM,
author = "Jey Han Lau and Timothy Baldwin and David Newman",
title = "On collocations and topic models",
journal = j-TSLP,
volume = "10",
number = "3",
pages = "10:1--10:??",
month = jul,
year = "2013",
CODEN = "????",
DOI = "https://doi.org/10.1145/2483969.2483972",
ISSN = "1550-4875",
bibdate = "Mon Jul 8 17:25:06 MDT 2013",
bibsource = "http://portal.acm.org/;
http://www.math.utah.edu/pub/tex/bib/tslp.bib",
abstract = "We investigate the impact of preextracting and
tokenizing bigram collocations on topic models. Using
extensive experiments on four different corpora, we
show that incorporating bigram collocations in the
document representation creates more parsimonious
models and improves topic coherence. We point out some
problems in interpreting test likelihood and test
perplexity to compare model fit, and suggest an
alternate measure that penalizes model complexity. We
show how the Akaike information criterion is a more
appropriate measure, which suggests that using a modest
number (up to 1000) of top-ranked bigrams is the
optimal topic modelling configuration. Using these 1000
bigrams also results in improved topic quality over
unigram tokenization. Further increases in topic
quality can be achieved by using up to 10,000 bigrams,
but this is at the cost of a more complex model. We
also show that multiword (bigram and longer) named
entities give consistent results, indicating that they
should be represented as single tokens. This is the
first work to explicitly study the effect of n -gram
tokenization on LDA topic models, and the first work to
make empirical recommendations to topic modelling
practitioners, challenging the standard practice of
unigram-based tokenization.",
acknowledgement = ack-nhfb,
articleno = "10",
fjournal = "ACM Transactions on Speech and Language Processing
(TSLP)",
journal-URL = "https://dl.acm.org/loi/tslp",
}
@Article{Shutova:2013:CML,
author = "Ekaterina Shutova and Jakub Kaplan and Simone Teufel
and Anna Korhonen",
title = "A computational model of logical metonymy",
journal = j-TSLP,
volume = "10",
number = "3",
pages = "11:1--11:??",
month = jul,
year = "2013",
CODEN = "????",
DOI = "https://doi.org/10.1145/2483969.2483973",
ISSN = "1550-4875",
bibdate = "Mon Jul 8 17:25:06 MDT 2013",
bibsource = "http://portal.acm.org/;
http://www.math.utah.edu/pub/tex/bib/tslp.bib",
abstract = "The use of figurative language is ubiquitous in
natural language texts and it is a serious bottleneck
in automatic text understanding. A system capable of
interpreting figurative expressions would be an
invaluable addition to the real-world natural language
processing (NLP) applications that need to access
semantics, such as machine translation, opinion mining,
question answering and many others. In this article we
focus on one type of figurative language, logical
metonymy, and present a computational model of its
interpretation bringing together statistical techniques
and the insights from linguistic theory. Compared to
previous approaches this model is both more informative
and more accurate. The system produces sense-level
interpretations of metonymic phrases and then
automatically organizes them into conceptual classes,
or roles, discussed in the majority of linguistic
literature on the phenomenon.",
acknowledgement = ack-nhfb,
articleno = "11",
fjournal = "ACM Transactions on Speech and Language Processing
(TSLP)",
journal-URL = "https://dl.acm.org/loi/tslp",
}
@Article{Klebanov:2013:SPM,
author = "Beata Beigman Klebanov and Jill Burstein and Nitin
Madnani",
title = "Sentiment profiles of multiword expressions in
test-taker essays: The case of noun--noun compounds",
journal = j-TSLP,
volume = "10",
number = "3",
pages = "12:1--12:??",
month = jul,
year = "2013",
CODEN = "????",
DOI = "https://doi.org/10.1145/2483969.2483974",
ISSN = "1550-4875",
bibdate = "Mon Jul 8 17:25:06 MDT 2013",
bibsource = "http://portal.acm.org/;
http://www.math.utah.edu/pub/tex/bib/tslp.bib",
abstract = "The property of idiomaticity vs. compositionality of a
multiword expression traditionally pertains to the
semantic interpretation of the expression. In this
article, we consider this property as it applies to the
expression's sentiment profile (relative degree of
positivity, negativity, and neutrality). Thus, while
heart attack is idiomatic in terms of semantic
interpretation, the sentiment profile of the expression
(strongly negative) can, in fact, be determined from
the strongly negative profile of the head word. In this
article, we (1) propose a way to measure
compositionality of a multiword expression's sentiment
profile, and perform the measurement on noun-noun
compounds; (2) evaluate the utility of using sentiment
profiles of noun-noun compounds in a sentence-level
sentiment classification task. We find that the
sentiment profiles of noun-noun compounds in test-taker
essays tend to be highly compositional and that their
incorporation improves the performance of a sentiment
classification system.",
acknowledgement = ack-nhfb,
articleno = "12",
fjournal = "ACM Transactions on Speech and Language Processing
(TSLP)",
journal-URL = "https://dl.acm.org/loi/tslp",
}
@Article{Nakov:2013:SIN,
author = "Preslav I. Nakov and Marti A. Hearst",
title = "Semantic interpretation of noun compounds using verbal
and other paraphrases",
journal = j-TSLP,
volume = "10",
number = "3",
pages = "13:1--13:??",
month = jul,
year = "2013",
CODEN = "????",
DOI = "https://doi.org/10.1145/2483969.2483975",
ISSN = "1550-4875",
bibdate = "Mon Jul 8 17:25:06 MDT 2013",
bibsource = "http://portal.acm.org/;
http://www.math.utah.edu/pub/tex/bib/tslp.bib",
abstract = "We study the problem of semantic interpretation of
noun compounds such as bee honey, malaria mosquito,
apple cake, and stem cell. In particular, we explore
the potential of using predicates that make explicit
the hidden relation that holds between the nouns that
form the noun compound. For example, mosquito that
carries malaria is a paraphrase of the compound malaria
mosquito in which the verb explicitly states the
semantic relation between the two nouns. We study the
utility of using such paraphrasing verbs, with
associated weights, to build a representation of the
semantics of a noun compound, for example, malaria
mosquito can be represented as follows: carry (23),
spread (16), cause (12), transmit (9), and so on. We
also explore the potential of using multiple
paraphrasing verbs as features for predicting abstract
semantic relations such as CAUSE, and we demonstrate
that using explicit paraphrases can help improve
statistical machine translation.",
acknowledgement = ack-nhfb,
articleno = "13",
fjournal = "ACM Transactions on Speech and Language Processing
(TSLP)",
journal-URL = "https://dl.acm.org/loi/tslp",
}
@Article{Editors:2013:E,
author = "{The Editors}",
title = "Editorial",
journal = j-TSLP,
volume = "10",
number = "4",
pages = "14:1--14:??",
month = dec,
year = "2013",
CODEN = "????",
DOI = "https://doi.org/10.1145/2556529",
ISSN = "1550-4875",
bibdate = "Thu Jan 9 10:56:30 MST 2014",
bibsource = "http://portal.acm.org/;
http://www.math.utah.edu/pub/tex/bib/tslp.bib",
acknowledgement = ack-nhfb,
articleno = "14",
fjournal = "ACM Transactions on Speech and Language Processing
(TSLP)",
journal-URL = "https://dl.acm.org/loi/tslp",
}
@Article{Meguro:2013:LCL,
author = "Toyomi Meguro and Yasuhiro Minami and Ryuichiro
Higashinaka and Kohji Dohsaka",
title = "Learning to control listening-oriented dialogue using
partially observable {Markov} decision processes",
journal = j-TSLP,
volume = "10",
number = "4",
pages = "15:1--15:??",
month = dec,
year = "2013",
CODEN = "????",
DOI = "https://doi.org/10.1145/2513145",
ISSN = "1550-4875",
bibdate = "Thu Jan 9 10:56:30 MST 2014",
bibsource = "http://portal.acm.org/;
http://www.math.utah.edu/pub/tex/bib/tslp.bib",
abstract = "Our aim is to build listening agents that attentively
listen to their users and satisfy their desire to speak
and have themselves heard. This article investigates
how to automatically create a dialogue control
component of such a listening agent. We collected a
large number of listening-oriented dialogues with their
user satisfaction ratings and used them to create a
dialogue control component that satisfies users by
means of Partially Observable Markov Decision Processes
(POMDPs). Using a hybrid dialog controller where
high-level dialog acts are chosen with a statistical
policy and low-level slot values are populated by a
wizard, we evaluated our dialogue control method in a
Wizard-of-Oz experiment. The experimental results show
that our POMDP-based method achieves significantly
higher user satisfaction than other stochastic models,
confirming the validity of our approach. This article
is the first to verify, by using human users, the
usefulness of POMDP-based dialogue control for
improving user satisfaction in nontask-oriented
dialogue systems.",
acknowledgement = ack-nhfb,
articleno = "15",
fjournal = "ACM Transactions on Speech and Language Processing
(TSLP)",
journal-URL = "https://dl.acm.org/loi/tslp",
}
@Article{Cai:2013:CCC,
author = "Xiaoyan Cai and Wenjie Li and Renxian Zhang",
title = "Combining co-clustering with noise detection for
theme-based summarization",
journal = j-TSLP,
volume = "10",
number = "4",
pages = "16:1--16:??",
month = dec,
year = "2013",
CODEN = "????",
DOI = "https://doi.org/10.1145/2513563",
ISSN = "1550-4875",
bibdate = "Thu Jan 9 10:56:30 MST 2014",
bibsource = "http://portal.acm.org/;
http://www.math.utah.edu/pub/tex/bib/tslp.bib",
abstract = "To overcome the fact that the length of sentences is
short and their content is limited, we regard words as
independent text objects rather than features of
sentences in sentence clustering and develop two
co-clustering frameworks, namely integrated clustering
and interactive clustering, to cluster sentences and
words simultaneously. Since real-world datasets always
contain noise, we incorporate noise detection and
removal to enhance clustering of sentences and words.
Meanwhile, a semisupervised approach is explored to
incorporate the query information (and the sentence
information in early document sets) in theme-based
summarization. Thorough experimental studies are
conducted. When evaluated on the DUC2005-2007 datasets
and TAC 2008-2009 datasets, the performance of the two
noise-detecting co-clustering approaches is comparable
with that of the top three systems. The results also
demonstrate that the interactive with noise detection
algorithm is more effective than the noise-detecting
integrated algorithm.",
acknowledgement = ack-nhfb,
articleno = "16",
fjournal = "ACM Transactions on Speech and Language Processing
(TSLP)",
journal-URL = "https://dl.acm.org/loi/tslp",
}
@Article{Blanco:2013:CSR,
author = "Eduardo Blanco and Dan Moldovan",
title = "Composition of semantic relations: Theoretical
framework and case study",
journal = j-TSLP,
volume = "10",
number = "4",
pages = "17:1--17:??",
month = dec,
year = "2013",
CODEN = "????",
DOI = "https://doi.org/10.1145/2513146",
ISSN = "1550-4875",
bibdate = "Thu Jan 9 10:56:30 MST 2014",
bibsource = "http://portal.acm.org/;
http://www.math.utah.edu/pub/tex/bib/tslp.bib",
abstract = "Extracting semantic relations from text is a
preliminary step towards understanding the meaning of
text. The more semantic relations are extracted from a
sentence, the better the representation of the
knowledge encoded into that sentence. This article
introduces a framework for the Composition of Semantic
Relations (CSR). CSR aims to reveal more text semantics
than existing semantic parsers by composing new
relations out of previously extracted relations.
Semantic relations are defined using vectors of
semantic primitives, and an algebra is suggested to
manipulate these vectors according to a CSR algorithm.
Inference axioms that combine two relations and yield
another relation are generated automatically. CSR is a
language-agnostic, inventory-independent method to
extract semantic relations. The formalism has been
applied to a set of 26 well-known relations and results
are reported.",
acknowledgement = ack-nhfb,
articleno = "17",
fjournal = "ACM Transactions on Speech and Language Processing
(TSLP)",
journal-URL = "https://dl.acm.org/loi/tslp",
}
@Article{Sokolov:2013:LBO,
author = "Artem Sokolov and Guillaume Wisniewski and
Fran{\c{c}}ois Yvon",
title = "Lattice {BLEU} oracles in machine translation",
journal = j-TSLP,
volume = "10",
number = "4",
pages = "18:1--18:??",
month = dec,
year = "2013",
CODEN = "????",
DOI = "https://doi.org/10.1145/2513147",
ISSN = "1550-4875",
bibdate = "Thu Jan 9 10:56:30 MST 2014",
bibsource = "http://portal.acm.org/;
http://www.math.utah.edu/pub/tex/bib/tslp.bib",
abstract = "The search space of Phrase-Based Statistical Machine
Translation (PBSMT) systems can be represented as a
directed acyclic graph (lattice). By exploring this
search space, it is possible to analyze and understand
the failures of PBSMT systems. Indeed, useful diagnoses
can be obtained by computing the so-called oracle
hypotheses, which are hypotheses in the search space
that have the highest quality score. For standard SMT
metrics, this problem is, however, NP-hard and can only
be solved approximately. In this work, we present two
new methods for efficiently computing oracles on
lattices: the first one is based on a linear
approximation of the corpus bleu score and is solved
using generic shortest distance algorithms; the second
one relies on an Integer Linear Programming (ILP)
formulation of the oracle decoding that incorporates
count clipping constraints. It can either be solved
directly using a standard ILP solver or using
Lagrangian relaxation techniques. These new decoders
are evaluated and compared with several alternatives
from the literature for three language pairs, using
lattices produced by two PBSMT systems.",
acknowledgement = ack-nhfb,
articleno = "18",
fjournal = "ACM Transactions on Speech and Language Processing
(TSLP)",
journal-URL = "https://dl.acm.org/loi/tslp",
}
@Article{Oshea:2013:NBD,
author = "James O'shea and Zuhair Bandar and Keeley Crockett",
title = "A new benchmark dataset with production methodology
for short text semantic similarity algorithms",
journal = j-TSLP,
volume = "10",
number = "4",
pages = "19:1--19:??",
month = dec,
year = "2013",
CODEN = "????",
DOI = "https://doi.org/10.1145/2537046",
ISSN = "1550-4875",
bibdate = "Thu Jan 9 10:56:30 MST 2014",
bibsource = "http://portal.acm.org/;
http://www.math.utah.edu/pub/tex/bib/tslp.bib",
abstract = "This research presents a new benchmark dataset for
evaluating Short Text Semantic Similarity (STSS)
measurement algorithms and the methodology used for its
creation. The power of the dataset is evaluated by
using it to compare two established algorithms, STASIS
and Latent Semantic Analysis. This dataset focuses on
measures for use in Conversational Agents; other
potential applications include email processing and
data mining of social networks. Such applications
involve integrating the STSS algorithm in a complex
system, but STSS algorithms must be evaluated in their
own right and compared with others for their
effectiveness before systems integration. Semantic
similarity is an artifact of human perception;
therefore its evaluation is inherently empirical and
requires benchmark datasets derived from human
similarity ratings. The new dataset of 64 sentence
pairs, STSS-131, has been designed to meet these
requirements drawing on a range of resources from
traditional grammar to cognitive neuroscience. The
human ratings are obtained from a set of trials using
new and improved experimental methods, with validated
measures and statistics. The results illustrate the
increased challenge and the potential longevity of the
STSS-131 dataset as the Gold Standard for future STSS
algorithm evaluation.",
acknowledgement = ack-nhfb,
articleno = "19",
fjournal = "ACM Transactions on Speech and Language Processing
(TSLP)",
journal-URL = "https://dl.acm.org/loi/tslp",
}
@Article{Roy:2013:CCN,
author = "Suman Deb Roy and Wenjun Zeng",
title = "Cognitive canonicalization of natural language queries
using semantic strata",
journal = j-TSLP,
volume = "10",
number = "4",
pages = "20:1--20:??",
month = dec,
year = "2013",
CODEN = "????",
DOI = "https://doi.org/10.1145/2539053",
ISSN = "1550-4875",
bibdate = "Thu Jan 9 10:56:30 MST 2014",
bibsource = "http://portal.acm.org/;
http://www.math.utah.edu/pub/tex/bib/tslp.bib",
abstract = "Natural language search relies strongly on perceiving
semantics in a query sentence. Semantics is captured by
the relationship among the query words, represented as
a network (graph). Such a network of words can be fed
into larger ontologies, like DBpedia or Google
Knowledge Graph, where they appear as subgraphs-
fashioning the name subnetworks (subnets). Thus, subnet
is a canonical form for interfacing a natural language
query to a graph database and is an integral step for
graph-based searching. In this article, we present a
novel standalone NLP technique that leverages the
cognitive psychology notion of semantic strata for
semantic subnetwork extraction from natural language
queries. The cognitive model describes some of the
fundamental structures employed by the human cognition
to construct semantic information in the brain, called
semantic strata. We propose a computational model based
on conditional random fields to capture the cognitive
abstraction provided by semantic strata, facilitating
cognitive canonicalization of the query. Our results,
conducted on approximately 5000 queries, suggest that
the cognitive canonicals based on semantic strata are
capable of significantly improving parsing and role
labeling performance beyond pure lexical approaches,
such as parts-of-speech based techniques. We also find
that cognitive canonicalized subnets are more
semantically coherent compared to syntax trees when
explored in graph ontologies like DBpedia and improve
ranking of retrieved documents.",
acknowledgement = ack-nhfb,
articleno = "20",
fjournal = "ACM Transactions on Speech and Language Processing
(TSLP)",
journal-URL = "https://dl.acm.org/loi/tslp",
}
