Automatic language identification of telephone speech messages using phoneme recognition and n-gram modeling
MA Zissman... - ... , Speech, and Signal Processing, ..., 1994 - ieeexplore.ieee.org
Abstract The paper compares the performance of four approaches to automatic language
identification (LID) of telephone speech messages: Gaussian mixture model classification
(GMM), language-independent phoneme recognition followed by language-dependent ...
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A unified context-free grammar and n-gram model for spoken language processing
[PDF] from microsoft.comYY Wang, M Mahajan... - Acoustics, Speech, and ..., 2000 - ieeexplore.ieee.org
Abstract While context-free grammars (CFGs) remain as one of the most important
formalisms for interpreting natural language, word n-gram models are surprisingly powerful
for domain-independent applications. We propose to unify these two formalisms for both ...
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Variable n-grams and extensions for conversational speech language modeling
M Siu... - Speech and Audio Processing, IEEE ..., 2000 - ieeexplore.ieee.org
Abstract Recent progress in variable n-gram language modeling provides an efficient
representation of n-gram models and makes training of higher order n grams possible. We
apply the variable n-gram design algorithm to conversational speech, extending the ...
Cited by 75 - Related articles - BL Direct - All 6 versions - Import into BibTeX
A maximum entropy language model integrating n-grams and topic dependencies for conversational speech recognition
[PDF] from nthu.edu.twS Khudanpur... - ... , Speech, and Signal Processing, 1999. ..., 1999 - ieeexplore.ieee.org
Abstract A compact language model which incorporates local dependencies in the form of N-
grams and long distance dependencies through dynamic topic conditional constraints is
presented. These constraints are integrated using the maximum entropy principle. Issues ...
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[PDF] Interpolation of n-gram and mutual-information based trigger pair language models for Mandarin speech recognition
[PDF] from suda.edu.cnZ GuoDong... - Computer Speech and Language, 1999 - nlp.suda.edu.cn
Abstract While n-gram modeling is simple and dominant in speech recognition, it can only
capture the short-distance context dependency within an n-word window where currently the
largest practical n for natural language is three. However, many of the context ...
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Dialog-context dependent language modeling combining n-grams and stochastic context-free grammars
[PDF] from psu.eduK Hacioglu... - ... , Speech, and Signal Processing, 2001. ..., 2001 - ieeexplore.ieee.org
Abstract We present our research on dialog dependent language modeling. In accordance
with a speech (or sentence) production model in a discourse we split language modeling
into two components; namely, dialog dependent concept modeling and syntactic modeling ...
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Experiments in spoken document retrieval using phoneme n-grams
[PDF] from mu.oz.auC Ng, R Wilkinson... - Speech Communication, 2000 - Elsevier
In spoken document retrieval (SDR), speech recognition is applied to a collection to obtain
either words or subword units, such as phonemes, that can be matched against queries. We
have explored retrieval based on phoneme n-grams. The use of phonemes addresses the ...
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Improving email speech acts analysis via n-gram selection
[PDF] from upenn.eduVR Carvalho... - ... Conversations in Text and Speech, 2006 - dl.acm.org
Abstract In email conversational analysis, it is often useful to trace the the intents behind
each message exchange. In this paper, we consider classification of email messages as to
whether or not they contain certain intents or email-acts, such as" propose a meeting" or" ...
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A discriminative HMM/N-gram-based retrieval approach for Mandarin spoken documents
[PDF] from ntnu.edu.twB Chen, HM Wang... - ACM Transactions on Asian Language ..., 2004 - dl.acm.org
Abstract In recent years, statistical modeling approaches have steadily gained in popularity
in the field of information retrieval. This article presents an HMM/N-gram-based retrieval
approach for Mandarin spoken documents. The underlying characteristics and the various ...
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Dealing with out-of-vocabulary words and speech disfluencies in an n-gram based speech understanding system
[PDF] from nthu.edu.twA Kai, Y Hirose... - ... Conference on Spoken Language ..., 1998 - isca-speech.org
In this study, we investigate the effectiveness of an unknown word processing (UWP)
algorithm, which is incorporated into an N-gram language model based speech recognition
system for dealing with filled pauses and out-of-vocabulary (OOV) words. We have ...
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Backoff hierarchical class n-gram language models: effectiveness to model unseen events in speech recognition
I Zitouni - Computer Speech & Language, 2007 - Elsevier
In this paper, we introduce the backoff hierarchical class n-gram language models to better
estimate the likelihood of unseen n-gram events. This multi-level class hierarchy language
modeling approach generalizes the well-known backoff n-gram language modeling ...
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Method and apparatus for a speech recognition system language model that integrates a finite state grammar probability and an N-gram probability
JR Bellegarda - US Patent 6,154,722, 2000 - Google Patents
A method and an apparatus for a speech recognition system that uses a language model
based on an integrated finite state grammar probability and an n-gram probability are
provided. According to one aspect of the invention, speech signals are received into a ...
Cited by 24 - Related articles - All 2 versions - Import into BibTeX
Importance of high-order n-gram models in morph-based speech recognition
[PDF] from tkk.fiT Hirsimaki, J Pylkkonen... - Audio, Speech, and ..., 2009 - ieeexplore.ieee.org
Abstract Speech recognition systems trained for morphologically rich languages face the
problem of vocabulary growth caused by prefixes, suffixes, inflections, and compound
words. Solutions proposed in the literature include increasing the size of the vocabulary ...
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Multi-Class Composite N-gram language model for spoken language processing using multiple word clusters
[PDF] from upenn.eduH Yamamoto, S Isogai... - ... of the 39th Annual Meeting on ..., 2001 - dl.acm.org
Abstract In this paper, a new language model, the Multi-Class Composite N-gram, is
proposed to avoid a data sparseness problem for spoken language in that it is difficult to
collect training data. The Multi-Class Composite N-gram maintains an accurate word ...
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An HMM/N-gram-based linguistic processing approach for Mandarin spoken document retrieval
[PDF] from uni-hamburg.deB Chen, H Wang... - ... European Conference on Speech ..., 2001 - isca-speech.org
In this paper an HMM/N-gram-based linguistic processing approach for Mandarin spoken
document retrieval is presented. The underlying characteristics and different structures of
this approach were extensively investigated. The retrieval capabilities were verified by ...
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Hierarchical class n-gram language models: towards better estimation of unseen events in speech recognition
[PDF] from cmu.eduI Zitouni, O Siohan... - ... European Conference on Speech ..., 2003 - isca-speech.org
In this paper, we show how a multi-level class hierarchy can be used to better estimate the
likelihood of an unseen event. In classical backoff n-gram models, the (n-1)-gram model is
used to estimate the probability of an unseen n-gram. In the approach we propose, we use ...
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Variable n-gram language modeling and extensions for conversational speech
M Siu... - Fifth European Conference on Speech ..., 1997 - isca-speech.org
Recent progress in variable n-gram language modeling provides an efficient representation
of n-gram models and makes training of higher order n-grams possible. In this paper, we
apply the variable n-gram design algorithm to conversational speech, extending the ...
Cited by 11 - Related articles - All 3 versions - Import into BibTeX
Error-responsive modifications to speech recognizers: negative n-grams
L Chase, R Rosenfeld... - ... Conference on Spoken ..., 1994 - isca-speech.org
We describe an error analysis technique that facilitates blame assignment among the
various components of a speech recognizer and provides insight into their behavior. Tools
are presented that help clarify how each of the component models and their interactions ...
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Language modeling by string pattern N-gram for Japanese speech recognition
[PDF] from udel.eduA Ito... - Spoken Language, 1996. ICSLP 96. ..., 1996 - ieeexplore.ieee.org
Abstract This paper describes a new powerful statistical language model based on N-gram
model for Japanese speech recognition. In English, a sentence is written word-by-word. On
the other hand. A sentence in Japanese has no word boundary character. Therefore. A ...
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A fast and memory-efficient N-gram language model lookup method for large vocabulary continuous speech recognition
[PDF] from psu.eduX Li... - Computer Speech & Language, 2007 - Elsevier
Recently, minimum perfect hashing (MPH)-based language model (LM) lookup methods
have been proposed for fast access of N-gram LM scores in lexical-tree based LVCSR
(large vocabulary continuous speech recognition) decoding. Methods of node-based LM ...
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Dialog act classification using n-gram algorithms
[PDF] from gsu.eduMM Louwerse... - ... of the Florida Artificial Intelligence Research ..., 2006 - aaai.org
Abstract Speech act classification remains one of the challenges in natural language
processing. This paper evaluates a classification system that assigns one of twelve dialog
acts to an utterance from the Map Task Corpus. The dialog act classification system ...
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[CITATION] A study of an N-Gram Language Model for Speech Recognition
PL O'Boyle - 1993 - Queen's University of Belfast
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Speech recognition using particle N-grams and content-word N-grams
R Isotani... - Third European Conference on Speech ..., 1993 - isca-speech.org
This paper proposes a new stochastic language model for speech recognition based on
particle N-grams and content-word N-grams. The conventional word N-gram model is
considered as effective for speech recognition; however, it represents only local ...
Cited by 8 - Related articles - All 2 versions - Import into BibTeX
Backoff hierarchical class n-gram language modelling for automatic speech recognition systems
I Zitouni, O Siohan, HKJ Kuo... - ... Conference on Spoken ..., 2002 - isca-speech.org
In this paper, we propose an extension of the backoff word n-gram language model that
allows a better likelihood estimation of unseen events. Instead of using the (n-1)-gram to
estimate the probability of an unseen n-gram, the proposed approach uses a class ...
Cited by 8 - Related articles - All 2 versions - Import into BibTeX
N-gram language model adaptation using small corpus for spoken dialog recognition
A Ito, H Saitoh, M Katoh... - ... Conference on Speech ..., 1997 - isca-speech.org
This paper describes an N-gram language model adaptation technique. As an N-gram
model requires a large size sample corpus for probability estimation, it is difficult to utilize N-
gram model for a specific small task. In this paper, N-gram task adaptation is proposed ...
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[PDF] Combination of phone N-grams for a MPEG-7-based spoken document retrieval system
[PDF] from psu.eduN Moreau, HG Kim... - in EUSIPCO, 2004 - Citeseer
ABSTRACT In this paper, we present a phone-based approach of spoken document
retrieval (SDR), developed in the framework of the emerging MPEG-7 standard. The audio
part of MPEG-7 aims at standardizing the indexing of audio documents. It encloses a ...
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Improving unsegmented dialogue turns annotation with n-gram transducers.
CD Martínez-Hinarejos, V Tamarit... - 2009 - eprints.pascal-network.org
Abstract The statistical models used for dialogue systems need annotated data (dialogues)
to infer their statistical parameters. Dialogues are usually annotated in terms of Dialogue
Acts (DA). The annotation problem can be attacked with statistical models, that avoid ...
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Discriminative training of n-gram classifiers for speech and text routing
[PDF] from microsoft.comC Chelba... - Eighth European Conference on Speech ..., 2003 - isca-speech.org
We present a method for conditional maximum likelihood estimation of N-gram models used
for text or speech utterance classification. The method employs a well known technique
relying on a generalization of the Baum-Eagon inequality from polynomials to rational ...
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The use of word n-grams and parts of speech for hierarchical cluster language modeling
[PDF] from sri.comW Wang... - ... , Speech and Signal Processing, 2006. ..., 2006 - ieeexplore.ieee.org
Abstract We present extensions to the work of backoff hierarchical class n-gram language
modeling of Zitouni et al.(2003) by studying the efficacy of exploring the use of parts of
speech (POS) information in hierarchical word clustering. We propose two approaches. ...
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[CITATION] TPOST: A Template-based, N-gram Part-of-Speech TAGGER for Tagalog
V Rabo - MSCS Thesis, De la Salle University-Manila, ..., 2004
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[PDF] Estimation method of user satisfaction using N-gram-based dialog history model for spoken dialog system
[PDF] from lrec-conf.orgS Hara, N Kitaoka... - Proc. LREC, 2010 - lrec-conf.org
Abstract In this paper, we propose an estimation method of user satisfaction for a spoken
dialog system using an N-gram-based dialog history model. We have collected a large
amount of spoken dialog data accompanied by usability evaluation scores by users in real ...
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Rapid adaptation of n-gram language models using inter-word correlation for speech recognition
K Sasaki, H Jiang... - ... International Conference on Spoken ..., 2000 - isca-speech.org
In this paper, we study the fast adaptation problem of n-gram language model under the
MAP estimation framework. We have proposed a heuristic method to explore inter-word
correlation to accelerate MAP adaptation of n-gram model. According to their correlations, ...
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A new word clustering method for building n-gram language models in continuous speech recognition systems
[PDF] from uni-saarland.deM Bahrani, H Sameti, N Hafezi... - New Frontiers in Applied ..., 2008 - Springer
In this paper a new method for automatic word clustering is presented. We used this method
for building n-gram language models for Persian continuous speech recognition (CSR)
systems. In this method, each word is specified by a feature vector that represents the ...
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Discriminative training of n-gram language models for speech recognition via linear programming
[PDF] from yorku.caV Magdin... - ... Speech Recognition & Understanding, ..., 2009 - ieeexplore.ieee.org
Abstract This paper presents a novel discriminative training algorithm for n-gram language
models for use in large vocabulary continuous speech recognition. The algorithm uses
Maximum Mutual Information Estimation (MMIE) to build an objective function that involves ...
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Effectiveness of the backoff hierarchical class n-gram language models to model unseen events in speech recognition
[PDF] from pitt.eduI Zitouni... - ... Speech Recognition and Understanding, ..., 2003 - ieeexplore.ieee.org
Abstract Backoff hierarchical class n-gram language models use a class hierarchy to define
an appropriate context. Each node in the hierarchy is a class containing all the words of the
descendant nodes (classes). The closer a node is to the root, the more general the ...
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Part of speech n-grams and Information Retrieval
C Lioma, CJ van Rijsbergen - Revue française de linguistique ..., 2008 - cairn.info
Information Retrieval (IR) systems aim to locate and quantify information in data with respect
to some user query. A common example of IR systems is World Wide Web (Web) search
engines, in which a short keyword query is used to generate a ranked list from a pre- ...
Cited by 4 - Related articles - Library Search - All 3 versions - Import into BibTeX
[CITATION] An HMM/N-gram-based Linguistic Approach for Mandarin Spoken Document Retrieval
B Chen, H Wang... - ... of the 7th European Conference on Speech ..., 2001
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Integrating Layer Concept Inform ation into N-gram Modeling for Spoken Language Understanding
[PDF] from nthu.edu.twNJC Wang, JL Shen... - ... Conference on Spoken Language ..., 2004 - isca-speech.org
The paper presents a novel approach, integrating layer concept information into the trigram
language model, to improve the understanding accuracy for spoken dialogue systems. With
this approach, both the recognition accuracy and out-of-grammar problem can be largely ...
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Parse tree n-grams for spoken language modelling
A Wrigley - ... , Applications and Alternatives, IEE Colloquium on, 1993 - ieeexplore.ieee.org
Abstract A method is described for modelling natural language for speech recognition. Its
aim is to incorporate the advantages of two previous types of approach; the statistical
approach and the formal linguistic approach. The n-gram model (JK Baker, 1975), is a ...
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[PDF] Overcoming HMM time independence assumption using n-gram based modelling for continuous speech recognition
[PDF] from eurasip.orgM Casar... - European Signal Processing Conference. ..., 2008 - eurasip.org
ABSTRACT The development of new acoustical models that overcome traditional HMM
restrictions is an active field of research in automatic speech recognition. One possible
approach to achieve this goal is to work with N-gram based augmented HMM. In this ...
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[CITATION] Dialog-Context Dependent Language Modeling Using N-Grams and Stochastic Context-Free Grammars. 2001
K Hacioglu... - Proceedings of ICASSP
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Spontaneous speech understanding in train timetable inquiry processing based on n-gram language models and finite state transducers
L Jelinek... - ORLANDO, FL, USA, 2004 - kky.zcu.cz
Abstract The presented paper concerns the spoken language understanding in an
information retrieval dialogue system. There are described methods of use the finite state
transducers for conceptual semantic parsing and meaning extraction from speaker's ...
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[PDF] Reduction of the Temporal Complexity of N-gram Transducers for Dialogue Annotation
[PDF] from psu.eduV Tamarit, CD Martinez-Hinarejos... - ... of Spoken Dialog Systems ..., 2009 - Citeseer
Abstract. The annotation of dialogues with Dialogue Acts is important to develop dialogue
systems. One way to do this annotation is using a method called N-gram Transducer (NGT),
that has shown very good results in unsegmented turns compared with other models, but ...
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[PDF] Integrating multiple layers of concept information into n-gram modeling for spoken language understanding
[PDF] from korea.ac.krNJC Wang - Proc. ICASSP, 2005 - ispl.korea.ac.kr
Abstract The paper presents a novel approach, integrating multi-layer concept information
into the trigram language model, to improve the understanding accuracy for spoken
dialogue systems. With this approach, both the recognition accuracy and out-of-grammar ...
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Large margin estimation of n-gram language models for speech recognition via linear programming
[PDF] from yorku.caV Magdin... - Acoustics Speech and Signal Processing ( ..., 2010 - ieeexplore.ieee.org
Abstract We present a novel discriminative training algorithm for n-gram language models
for use in large vocabulary continuous speech recognition. The algorithm uses large margin
estimation (LME) to build an objective function for maximizing the minimum margin ...
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Jurilinguistic engineering in Cantonese Chinese: an N-gram-based speech to text transcription system
[PDF] from uni-hamburg.deBK T'sou, KK Sin, SWK Chan, TBY Lai... - Proceedings of the 18th ..., 2000 - dl.acm.org
Abstract A Cantonese Chinese transcription system to automatically convert stenograph
code to Chinese characters is reported. The major challenge in developing such a system is
the critical homocode problem because of homonymy. The statistical N-gram model is ...
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[PDF] Linearly interpolated hierarchical n-gram language models for speech recognition engines
[PDF] from intechopen.comI Zitouni... - ... Speech Recognition and Understanding, 2007 - intechopen.com
Language modeling is a crucial component in natural language continuous speech
recognition, due to the difficulty involved by continuous speech [1],[2]. Language modeling
attempts to capture regularities in natural language for the purpose of improving the ...
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[PDF] A n-gram approach to overcome time and parameter independence assumptions of HMM for speech recognition
[PDF] from eurasip.orgM Casar... - Proceedings of the ISCA European Signal ..., 2007 - eurasip.org
ABSTRACT There is significant interest in developing new acoustic models for speech
recognition that overcome traditional HMM restrictions. In this work, we propose to use a N-
gram based augmented HMM. Two approaches are presented. The first one consists on ...
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[CITATION] Combining N-grams and SCFGs in Speech Language Models
A Stolcke - Proc IEEE Automatic Speech Recognition Workshop, ..., 1995
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[CITATION] Characteristics of High Occurrence Frequency N-gram of Spoken Japanese Corpora
N Ueda... - Proc. Spring Meet. Acoust. Soc. Jpn
Cited by 2 - Related articles - Import into BibTeX
[CITATION] Detection of errors n part-of-speech tagged corpora by bootstrapping generalized negative n-grams
P Kveton... - Proceedings of 3rd International Conference on ..., 2002
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Speech Recognition Using Function-Word< I> N</I>-Grams and Content-Word< I> N</I>-Grams
R Isotani, S Matsunaga... - IEICE TRANSACTIONS on ..., 1995 - search.ieice.org
... Summary: This paper proposes a new stochastic language model for speech recognition based
on function-word N-grams and content-word N-grams. The conventional word N-gram models
are effective for speech recognition, but they represent only local constraints ...
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[CITATION] Conversational speech recognition using sentence style related multi N-grams
T Shimizu, S Kuroiwa... - Proc. ASRU, 1999
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Using extra n-gram counts for statistical language model adaptation in speech-driven question answering
T Akiba, K Itou, A Fujii... - IPSJ SIGNotes of Spoken ..., 2002 - sciencelinks.jp
Abstract; Aiming at speech-driven question answering, we propose two methods to produce
statistical language models for recognizing spoken questions with a high accuracy. Both
methods use a target collection (ie, a document set from which answers are derived) to ...
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Automatic detection of task-incompleted dialog for spoken dialog system based on dialog act N-gram
[PDF] from nagoya-u.ac.jpS Hara, N Kitaoka... - ... of the International Speech ..., 2010 - isca-speech.org
In this paper, we propose a method of detecting task-incompleted users for a spoken dialog
system using an N-gram-based dialog history model. We collected a large amount of spoken
dialog data accompanied by usability evaluation scores by users in real environments. ...
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An Integrated Language Modeling with n-gram model and WA model for Speech Recognition
[PDF] from mirlab.orgS Zhang... - Fifth European Conference on Speech ..., 1997 - isca-speech.org
As to traditional n-gram model, smaller n value is an inherent defect for estimating language
probabilities in speech recognition, simply because that estimation could not be executed
over farther word association but by means of short sequential word correlated information ...
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Combination of a hidden tag model and a traditional n-gram model: A case study in Czech speech recognition
[PDF] from cmu.eduP Krbec, P Podvesky... - ... European Conference on Speech ..., 2003 - isca-speech.org
A speech recognition system targeting high inflective languages is described that combines
the traditional trigram language model and an HMM tagger, obtaining results superior to the
trigram language model itself. An experiment in speech recognition of Czech has been ...
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Speech interface for name input based on combination of recognition methods using syllable-based N-gram and word dictionary
[PDF] from nthu.edu.twH Oshikawa, N Kitaoka... - ... Conference on Spoken ..., 2004 - isca-speech.org
We propose an interface for name input based on speech recognition using syllable-based
N-gram and word dictionary. Name utterance is hard to recognize accurately because of the
large vocabulary size, so the system uses continuous syllable recognition with syllable- ...
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[PDF] Development of an N-Gram Based Language Model for Continuous Speech Recognition
[PDF] from piconepress.comSP Given - ... , The Language Modeling Group, Department of ..., 1996 - isip.piconepress.com
ABSTRACT An essential element of any speech recognition system is the language model.
A language model attempts to identify and make use of the regularities in natural language
to better define language syntax for easier recognition. One major obstacle in speech ...
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[PDF] High speed spoken term detection by combination of n-gram array of a syllable lattice and LVCSR result for NTCIR-SpokenDoc
[PDF] from nii.ac.jpK Iwami... - ... of the Ninth NTCIR Workshop Meeting, 2011 - research.nii.ac.jp
ABSTRACT For spoken document retrieval, it is very important to consider Out-of-
Vocabulary (OOV) and mis-recognition of spoken words. Therefore, sub-word unit based
recognition and retrieval methods have been proposed. This paper describes a Japanese ...
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[PDF] NETWORK AND N-GRAM DECODING IN SPEECH RECOGNITION
[PDF] from piconepress.comJ Zhao - 2000 - isip.piconepress.com
I would like to thank Dr. Picone for his guidance through my work and study. I would also like
to thank every one in ISIP (Institute for signal and information processing) for their help. A lot
of work presented in this thesis is the result of team works. I am only one member of the ...
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[CITATION] ... Language Modeling Using N-Grams and Stochastic Context-Free Grammars", to appear in IEEE International Conference on Acoustics, Speech, and ...
K Hacioglu...
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[CITATION] Dialog-Context Dependent Modeling Combining N-Grams and Stochastic Context-Free Grammars
K Hacioglu... - 26th International Conference on Acoustics, Speech ...
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Task extension with fusion of N-gram and grammar in public speech dialogue system
T KITAMURA, T TODA, H KAWANAMI... - IEIC Technical Report ..., 2005 - sciencelinks.jp
Abstract; A suitable task domain for speech recognition and speech dialogue systems used
in a real environment is important. It is indispensable to popularize such systems so that its
technology can easily be applied or enhanced to a required task. When a new task is ...
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Detection of task-incomplete dialogs based on utterance-and-behavior tag N-gram for spoken dialog systems
K Takeda, N Kitaoka... - ... Conference of the International Speech ..., 2011 - ci.nii.ac.jp
... Detection of task-incomplete dialogs based on utterance-and-behavior tag N-gram for spoken
dialog systems. ... ?????/??. ?????????(??). ?????. 12th Annual Conference
of the International Speech Communication Association in Florence, Italy, on August 27 ...
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Speech Interface for name input using syllable N-gram and word dictionary.
H OSHIKAWA, N KITAOKA... - IEIC Technical Report ( ..., 2003 - sciencelinks.jp
Abstract; We propose an interface for a name input based on speech recognition using
syllable-based N-gram and a word dictionary. User first utters a name and then chooses the
correct word/syllables by pen touch from word/syllable candidates which were obtained ...
Cached - Import into BibTeX
Speech Recognition Algorithm Strengthening N-gram Probability with Task Grammar.
R TSURUMI, A RI, H SARUWATARI... - Joho Shori Gakkai ..., 2003 - sciencelinks.jp
Abstract; In speech dialogue systems, both word N-gram model and written network
grammar are mainly used as language models. Since a word N-gram model is a statistical
language model, it is practically feasible for various speech expressions and even for an ...
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Detecting errors in Chinese spoken dialog system using ngram and dependency parsing
W Zhou, B Yuan, Z Miao, W Zhu... - 2008 - link.aip.org
In this paper, a hybrid method of detecting ASR error in spoken turns is developed. The
erroneous text is locally analyzed first by neighbouring co-occurrence relations using ngram
model. Then the text is globally analyzed by long distance dependency relations using a ...
Import into BibTeX
Spoken Language Processing. Dealing with Out-of-vocabulary Words and Filled Pauses in Word N-gram Based Speech Recognition System.
A KAI, Y HIROSE... - Transactions, 1999 - sciencelinks.jp
Abstract; For practical use of spoken dialog systems and dictation systems, it is important to
cope with out-of-vocabulary words and filled pauses including the phenomena such as
interjection, restart and hesitation. To address these problems, this study tries to use an ...
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N-gram language models in JLASER neural network speech recognizer
M Konopi´k, I Habernal... - Applied Electronics (AE), ..., 2010 - ieeexplore.ieee.org
Abstract In our recent research we have discovered that neural networks can be more
efficient in speech recognition than the state of the art approach based on Gaussian
mixtures. This statement is valid only for small corpora, however, many applications do not ...
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Method and apparatus for a speech recognition system language model that integrates a finite state grammar probability and an N-gram probability
JR Bellegarda - The Journal of the Acoustical Society of America, 2001 - link.aip.org
Method and apparatus for a speech recognition system language model that integrates a finite
state grammar probability and an N-gram probability. [The Journal of the Acoustical Society of
America 110, 24 (2001)]. Jerome R. Bellegarda. Keywords. Acoustics. ...
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[PDF] Evaluation of the incremental dialogue annotation using N-gram Transducers
[PDF] from upm.esCD Martinez-Hinarejos, JMB Vicent Tamarit - lorien.die.upm.es
Abstract The annotation of dialogues in terms of Dialogue Acts (DA) is an important task in
the development of dialogue systems. Recently, the N-gram Transducers (NGT) technique
showed a better performance than other techniques in the annotation of unsegmented ...
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... on Importance SamplingA Measure of Dissimilarity for Evaluating Relational Structure of Learning TasksJapanese-English Bilingual Speech Recognition of Voice ...
K TAKAHASHI, M MIMURA, Y ISOBE... - search.ieice.org
... pp.979-990 PAPER Japanese-English Bilingual Speech Recognition of Voice Command in
Enroute Air Traffic Control Communication Atsunori ... pp.1011-1018 PAPER Character String
Recognition Based on Island-Driven Search Algorithm Using N-Gram Statistics Ryuji MINE ...
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Spoken Language Processing and Applications. Construction Method of Language Model Using Stochastic Switching n-gram.
T NAGANO, M SUZUKI... - Transactions, 2002 - sciencelinks.jp
Abstract; In traditional speech recognition systems, a single kind of n-gram is used for n-
gram language model. If a task can divide into more small sub tasks, utilization of several
kinds of n-gram gives better performance. In this paper, we propose a so-called SS ( ...
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[PDF] Louwerse, MM & Crossley, SA (2006). Dialog act classification using n-gram algorithms. In Proceedings of the 19th International Florida Artificial Intelligence ...
[PDF] from psu.eduM Louwerse - Citeseer
Abstract Speech act classification remains one of the challenges in natural language
processing. This paper evaluates a classification system that assigns one of twelve dialog
acts to an utterance from the Map Task Corpus. The dialog act classification system ...
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Spoken Language Understanding Using Layered N-gram Modeling
[PDF] from pitt.eduNJC Wang - Ninth European Conference on Speech ..., 2005 - isca-speech.org
This paper presents an approach which integrates layer concept information into the trigram
language model in order to improve the understanding accuracy for spoken dialogue
systems and to improve the portability of the language modeling materials among different ...
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On-line detection of task incompletion for spoken dialog systems using utterance and behavior tag N-gram vectors
S Hara, N Kitaoka... - ... and its Integration in Spoken Dialogue ..., 2011 - Springer
We propose a method of detecting the task incompletion in spoken dialog systems using N-
gram-based dialog features. We used a database created during a field test in which
inexperienced users used a client-server music retrieval system with a spoken dialog ...
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[CITATION] A Method to Detect the Syllable Strings of Self-repair in Spontaneous Speech Using N-gram Model
T Araki, S Ikehara... - MEMOIRS-FACULTY OF ..., 1998 - FUKUI UNIVERSITY
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Generating compound words with high order n-gram information in large vocabulary speech recognition systems
[PDF] from uiuc.eduJ Zhou, Q Shi... - ... , Speech and Signal Processing ( ..., 2011 - ieeexplore.ieee.org
Abstract In this work we concentrate on generating compound words with high order n-gram
information for speech recognition. In most existing compound words generation methods,
only bi-gram information is considered. They are successful for improving the performance ...
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Connectionist Models of Speech Segmentation and the Utterance Boundary Strategy: A Comparison of the SOM, SRN and N-GRAMS
JA Hammerton - PROGRESS IN NEURAL PROCESSING, 2004 - books.google.com
Some connectionist models of speech segmentation have exploited the utterance boundary
strategy, where the fact that utterance endings are also word endings is used to infer where
word boundaries are. In this paper, it is demonstrated that using a simple N-gram based ...
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On the Use of N-Gram Transducers for Dialogue Annotation
V Tamarit, CD Martínez-Hinarejos... - Spoken Dialogue Systems ..., 2011 - Springer
The implementation of dialogue systems is one of the most interesting applications of
language technologies. Statistical models can be used in this implementation, allowing for a
more flexible approach than when using rules defined by a human expert. However, ...
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Detection of task-incomplete dialogs based on utterance-and-behavior tag N-gram for spoken dialog systems
[PDF] from nagoya-u.ac.jpS Hara, N Kitaoka... - ... of the International Speech ..., 2011 - ir.nul.nagoya-u.ac.jp
We propose a method of detecting "task incomplete" dialogs in spoken dialog systems using
N-gram-based dialog models. We used a database created during a field test in which
inexperienced users used a client-server music retrieval system with a spoken dialog ...
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Spoken Language Processing and Applications. A Metric Based on Likelihood Difference for n-gram Language Model Evaluation.
A ITO... - Transactions, 2002 - sciencelinks.jp
Abstract; Perplexity and cross entropy have been widely used as an evaluation metric of
stochastic language model. Recently, several papers reported that correlation between
these metrics and word error rate was poor when complicated language models were ...
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An N-gram based Chinese syllable evaluation approach for speech recognition error detection
X Wang... - ... and Knowledge Engineering, 2009. NLP-KE ..., 2009 - ieeexplore.ieee.org
Abstract In order to find errors and correct words after Chinese speech recognition to
improve its accuracy rate, an N-gram based phonetic syllable evaluation approach is
proposed according to the conjunction rules in Chinese syllables. In this paper, Bigram ...
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[PDF] DEALING WITH OUT-OF-VOCABULARY WORDS AND SPEECH DISFLUENCIES IN AN N-GRAM BASED SPEECH UNDERSTANDING SYSTEM
[PDF] from uiuc.eduYH AtsuhikoKAI... - mickey.ifp.uiuc.edu
ABSTRACT In this study, we investigate the effectiveness of an unknown word processing
(UWP) algorithm, which is incorporated into an N-gram language model based speech
recognition system for dealing with filled pauses and outof-vocabulary (OOV) words. We ...
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[PDF] TPOST: A Template-Based, n-gram Part-Of-Speech Tagger for Tagalog
[PDF] from dlsu.edu.phCK Cheng... - dlsu.edu.ph
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Part-of-Speech N-gram and Word N-gram Fused Language Model
[PDF] from nthu.edu.twH Yamamoto... - ... European Conference on Speech ..., 1999 - isca-speech.org
In th is paper, an accurate and com pact language model is proposed to cope robustly with
data sparseness and task dependencies. This language model adopts new categories
which are generated by continuously interpolating POS word-class categories and word ...
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[CITATION] SPEECH-P6. 14: USE OF STATISTICAL N-GRAM MODELS IN NATURAL LANGUAGE GENERATION FOR MACHINE TRANSLATION
FH Liu, L Gu, Y Gao... - ... ON ACOUSTICS SPEECH AND ..., 2003 - IEEE; 1999
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[PDF] Modeling out-of-vocabulary words using multi class-based n-gram language model for automatic speech recognition
[PDF] from tut.ac.jpW Naptali, M Tsuchiya... - slp.ics.tut.ac.jp
Out-of-vocabulary (OOV) words cause a serious problem for automatic speech recognition
(ASR) system. Not only it will be miss-recognized as an invocabulary word with similar
phonetics, but the error will also affect nearby words to make errors. Language models ( ...
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[CITATION] Part VI-Cross-Language Spoken Document Retrieval-N-grams for Translation and Retrieval in CL-SDR
P McNamee, J Mayfield - Lecture Notes in ..., 2004 - Berlin: Springer-Verlag, 1973-
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[CITATION] SPEECH-P1. 10: SEMANTIC N-GRAM LANGUAGE MODELING WITH THE LATENT MAXIMUM ENTROPY PRINCIPLE
S Wang, D Schuurmans, F Peng... - ... ON ACOUSTICS SPEECH ..., 2003 - IEEE; 1999
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Part-of-Speech Class N-gram and Word N-gram Fused Language Model.
H YAMAMOTO... - Reports of the Meeting. the ..., 1999 - sciencelinks.jp
TOP > J-EAST > List of Journal Titles (R) > Reports of the Meeting. the Acoustical Society of
Japan(1999) > Part-of-Speech Class N-gram and Word N-gram Fused Language Model. ...
Part-of-Speech Class N-gram and Word N-gram Fused Language Model.
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Packet loss concealment based on statistical n-gram predictive models for use in voice-over-IP speech transmission
M Lee, Q Zhou... - US Patent 7,701,886, 2010 - Google Patents
A method for performing packet loss concealment of lost packets in Voice over IP (Internet
Protocol) speech transmission. Statistical n-gram models are initially created with use of a
training speech corpus, and then, packets lost during transmission are advantageously ...
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... on Saliency and Gradient IntensityDetection of Task Incomplete Dialogs Based on Utterance Sequences N-gram for Spoken Dialog SystemDetecting Side Oncoming ...
K TANABE - search.ieice.org
... Summary | Full Text(in Japanese):PDF (1.3MB). pp.497-500 LETTER Detection of Task Incomplete
Dialogs Based on Utterance Sequences N-gram for Spoken Dialog System Sunao HARA Norihide
KITAOKA Kazuya TAKEDA. Summary | Full Text(in Japanese):PDF (495KB). ...
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N-gram language models for Polish language. Basic concepts and applications in automatic speech recognition systems
[PDF] from imcsit.orgB Rapp - ... Science and Information Technology, 2008. IMCSIT ..., 2008 - ieeexplore.ieee.org
Abstract Usage of language models in automatic speech recognition systems usually give
significant quality and certainty improvement of recognition outcomes. On the other hand,
wrongly chosen or trained language models can result in serious degradation not only ...
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... of a Phonetically Rich Speech CorpusBi-Spectral Acoustic Features for Robust Speech RecognitionLocal Peak Enhancement for In-Car Speech Recognition in Noisy ...
C LANG, D XU... - search.ieice.org
... Model Compositions Using Multi-Pass Search with Multi-Label N-gram Models Takatoshi ...
PAPER-Acoustic Modeling Development of a Mandarin-English Bilingual Speech Recognition
System ... ASR System Architecture Selection of Optimum Vocabulary and Dialog Strategy for ...
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Packet loss concealment based on statistical n-gram predictive models for use in voice-over-IP speech transmission
M Lee, Q Zhou... - US Patent App. 20,050/276,235, 2004 - freepatentsonline.com
1. A method for performing packet loss concealment in a packet-based speech
communication system, the method comprising the steps of: receiving a sequence of one or
more speech packets each comprising a set of speech parameters representative of ...
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[CITATION] A comparison of N-grams in the spoken component of the" British National Corpus" and the" Longman Spoken American Corpus"
C Ruoss - 2001 - Ref.: Gunnel Tottie.
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A New Language Model by Using (n. GEQ. 4)-gram for Broadcast News Speech Transcription.
N KATO, N URATANI, T EHARA... - IEICE Transactions on ..., 2002 - sciencelinks.jp
... 2- or 3-gram under carrying out adoptation to the native RM by modeling such character with
n-gram (n is larger than or equal to 4). As when all of n-gram are simply ... As a result of an evaluation
test based on perplexity and speech recognition, a good result could be obtained. ...
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... Topic Transition ModelCooperative Spoken Dialogue Model Using Bayesian Network and Event HierarchyError Analysis of Field Trial Results of a Spoken Dialogue ...
Y WANG, JL XU, K INOUE... - search.ieice.org
... pp.636-641 PAPER Error Analysis of Field Trial Results of a Spoken Dialogue System for
Telecommunications Applications Shingo KUROIWA Kazuya ... pp.692-697 PAPER Speech
Recognition Using Function-Word N-Grams and Content-Word N-Grams Ryosuke ISOTANI ...
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