.. Utilisation-des-paramètres-linguistiques, 110 14.3 Utilisation des paramètres combinés

E. Annexe and E. Nouveaux-modèles-de-langage-le-tableau, 1 présente le taux d'erreur mot et le pourcentage de nouveaux mots correctement reconnus, obtenus avec les nouveaux modèles de langage. baseline+1-grammes 5 mS 10, p.61

A. , O. , A. Mohamed, H. Jiang, and G. Penn, Applying Convolutional Neural Networks concepts to hybrid NN-HMM model for speech recognition, Proceedings of the IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP), pp.4277-4280, 2012.

A. , A. , and J. Gauvain, Open Vocabulary ASR for Audiovisual Document Indexation, Proceedings of the IEEE International Conference on Acoustics , Speech and Signal Processing (ICASSP), pp.1013-1016, 2005.

A. , F. , M. Vacher, S. Rossato, and F. Portet, Speech Recognition of Aged Voices in the AAL Context: Detection of Distress Sentences, The 7th International Conference on Speech Technology and Human-Computer Dialogue (SpeD), pp.177-184, 2013.
URL : https://hal.archives-ouvertes.fr/hal-00953248

A. , S. J. Et, and R. P. Singh, Automatic Speech Recognition: A Review, International Journal of Computer Applications, vol.609, pp.34-44, 2012.

A. , A. , R. Schwartz, and J. Makhoul, Automatic modeling for adding new words to a large-vocabulary continuous speech recognition system, Proceedings of the IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP). T. 1, pp.305-308, 1991.

J. K. Baker, The DRAGON system--An overview, IEEE Transactions on Acoustics, Speech, and Signal Processing, vol.23, issue.1, pp.24-29, 1975.
DOI : 10.1109/TASSP.1975.1162650

B. , K. Et, and D. Jouvet, Automatic Detection of the Prosodic Structures of Speech Utterances, Speech and Computer. T. 8113, pp.1-8, 2013.

B. , S. , G. Kondrak, and C. Cherry, On the Syllabification of Phonemes, Proceedings of Human Language Technologies: The 2009 Annual Conference of the North American Chapter of the Association for Computational Linguistics, pp.308-316, 2009.

L. E. Baum, J. A. Et, and . Eagon, An inequality with applications to statistical estimation for probabilistic functions of Markov processes and to a model for ecology, Bulletin of the American Mathematical Society, vol.73, issue.3, pp.360-363, 1967.
DOI : 10.1090/S0002-9904-1967-11751-8

L. E. Baum, T. Et, and . Petrie, Statistical Inference for Probabilistic Functions of Finite State Markov Chains, The Annals of Mathematical Statistics, vol.37, issue.6, pp.1554-1563, 1966.
DOI : 10.1214/aoms/1177699147

Y. Bengio, R. Ducharme, P. Vincent, and C. Janvin, Neural Probabilistic Language Models, The Journal of Machine Learning Research, vol.3, pp.1137-1155, 2003.
DOI : 10.1007/3-540-33486-6_6
URL : https://hal.archives-ouvertes.fr/hal-01434258

B. , B. , C. Meunier, R. Bertrand, and I. Nesterenko, Annotation automatique en syllabes d'un dialogue oral spontané, Journées d'Étude sur la Parole (JEP), pp.1-4, 2010.

B. , M. , and H. Ney, Open vocabulary speech recognition with flat hybrid models, Proceedings of Interspeech, pp.725-728, 2005.

B. , K. , B. Favre, and D. Hakkani-tur, Any questions? Automatic question detection in meetings, IEEE Workshop on Automatic Speech Recognition and Understanding (ASRU), pp.485-489, 2009.
URL : https://hal.archives-ouvertes.fr/hal-01194279

P. F. Brown, P. V. Desouza, R. L. Mercer, V. J. Della-pietra, and J. C. Lai, Class-Based n-gram Models of Natural Language, Computational Linguistics 18, pp.467-479, 1992.

B. , A. , M. Ravanelli, P. Svaizer, and M. Omologo, A speech event detection and localization task for multiroom environments, Workshop on Handsfree Speech Communication and Microphone Arrays (HSCMA), pp.157-161, 2014.

C. , M. De, and G. Pérennou, BDLEX : a Lexicon for Spoken and Written French, Proceedings of the International Conference on Language Resources and Evaluation (LREC), pp.1129-1136, 1998.

C. , H. , A. Derouault, M. Elbeze, and B. Mérialdo, Speech recognition in French with a very large dictionary, Proceedings of Eurospeech, pp.2150-2153, 1989.

C. , S. Le, J. Van, and H. , Ridge estimators in Logistic Regression, Applied Statistics, vol.411, pp.191-201, 1992.

C. Michel-de-l-'épée, Institution des sourds et muets par la voie des signes méthodiques, 1776.

C. , C. Et, and F. Jelinek, Structured language modeling, Computer Speech & Language 14, pp.283-332, 2000.

C. , S. F. Et, and J. Goodman, An Empirical Study of Smoothing Techniques for Language Modeling, 1998.

C. , Y. , M. Dunham, O. Kimball, M. Krasner et al., The BBN BYBLOS Continuous Speech Recognition system, Proceedings of the workshop on Speech and Natural Language , HLT '89, pp.89-92, 1987.
DOI : 10.3115/100964.100968

C. , A. , and F. Destombes, LIPCOM, prototype d'aide automatique à la réception de la parole par les personnes sourdes, pp.36-40, 1999.

C. , S. , M. Lincoln, J. Tryggvason, M. Nakisa et al., Tessa, a system to aid communication with deaf people, Proceedings of the fifth international ACM conference on Assistive technologies, pp.205-212, 2002.

D. , I. , L. Lee, and F. C. Pereira, Similarity-Based Models of Word Cooccurrence Probabilities, In : Machine Learning. T, vol.34, pp.1-3, 1999.

D. , G. E. , D. Yu, L. Deng, and A. Acero, Context-Dependent Pre-trained Deep Neural Networks for Large Vocabulary Speech Recognition, IEEE Transactions on Audio, Speech and Language Processing, 2012.

D. , K. H. , R. Biddulph, and S. Balashek, Automatic Recognition of Spoken Digits, The Journal of the Acoustical Society of America, vol.246, pp.637-642, 1952.

D. , S. B. Et, and P. Mermelstein, Comparison of Parametric Representations for Monosyllabic Word Recognition in Continuously Spoken Sentences, IEEE Transactions on Acoustics, Speech, and Signal Processing, vol.284, pp.357-366, 1980.

D. , R. Et, and M. Federico, Language Model Adaptation, Computational Models of Speech Pattern Processing. T. 169, pp.280-303, 1999.

D. , P. Et, and M. V. Mathews, Spoken digit recognition using time-frequency pattern matching, The Journal of the Acoustical Society of America, vol.32, issue.11, pp.1450-1455, 1960.

E. , Y. , T. Bazillon, J. Antoine, F. Béchet et al., The EPAC corpus: manual and automatic annotations of conversational speech in French broadcast news, Proceedings of the International Conference on Language Resources and Evaluation (LREC), 2010.
URL : https://hal.archives-ouvertes.fr/hal-01433895

F. , D. Et, and O. Mella, CoALT: A Software for Comparing Automatic Labelling Tools, Proceedings of the International Conference on Language Resources and Evaluation (LREC), 2012.

F. , Y. Et, and R. E. Schapire, Experiments with a new boosting algorithm, Thirteenth International Conference on Machine Learning, pp.148-156, 1996.

G. , G. , G. Potamianos, and F. Makedon, Audio-visual speech recognition incorporating facial depth information captured by the Kinect, Proceedings of the 20th European Signal Processing Conference (EUSIPCO), pp.2714-2717, 2012.

G. , S. , G. Gravier, L. Chaubard-ganapathiraju, A. et al., The ESTER 2 evaluation campaign for rich transcription of French broadcasts Syllable-based large vocabulary continuous speech recognition, Proceedings of Interspeech. IEEE Transactions on Speech and Audio Processing 9, pp.358-366, 2001.

G. , J. , Y. Miao, F. Metze, and A. Waibel, Extracting deep bottleneck features using stacked auto-encoders, Proceedings of the IEEE International Conference on Acoustics, Speech and Signal Processing, pp.3377-3381, 2013.

G. , G. , G. Adda, N. Paulson, M. Carré et al., The ETAPE corpus for the evaluation of speech-based TV content processing in the French language, Proceedings of the International Conference on Language Resources, Evaluation and Corpora (LREC), 2012.
URL : https://hal.archives-ouvertes.fr/hal-00712591

G. , F. , M. Karafiát, S. Kontár, and J. Cernocky, Probabilistic and bottle-neck features for LVCSR of meetings, Proceedings of the IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP). T. 4, pp.757-760, 2007.

H. , M. , E. Frank, G. Holmes, B. Pfahringer et al., The WEKA Data Mining Software: An Update, In : SIGKDD Explorations, vol.11, issue.1, pp.10-18, 2009.

H. , A. , L. Boves, J. De, and V. , Syllable-Length Acoustic Units in Large-Vocabulary Continuous Speech Recognition, Proceedings of SPECOM, pp.499-502, 2005.

H. , G. E. Et, and S. Osindero, A fast learning algorithm for deep belief nets, Neural Computation, vol.187, pp.1527-1554, 2006.

H. , C. , T. Chen, S. Z. Li, E. Chang et al., Analysis of speaker variability, Proceedings of Interspeech, pp.1377-1380, 2001.

H. , D. , M. Kumar, A. Chan, A. W. Black et al., PocketSphinx: A free, real-time continuous speech recognition system for hand-held devices, Proceedings of the IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP), 2006.

I. , I. , D. Fohr, and D. Jouvet, Grapheme-to-Phoneme Conversion using Conditional Random Fields, Proceedings of Interspeech, pp.2313-2316, 2011.
URL : https://hal.archives-ouvertes.fr/inria-00614981

I. , K. , R. Schlüter, and H. Ney, Bag-of-Words Input for Long History Representation in Neural Network-Based Language Models for Speech Recognition, Proceedings of Interspeech, 2015.

J. , F. , L. R. Bahl, and R. L. Mercer, Design of a linguistic statistical decoder for the recognition of continuous speech, IEEE Transactions on Information Theory, vol.213, pp.250-256, 1975.

J. , F. , B. Merialdo, S. Roukos, and M. Strauss-i, Self-organized language modeling for speech recognition, Readings in Speech Recognition, pp.450-506, 1990.

J. , F. , B. Merialdo, S. Roukos, and M. Strauss, A Dynamic Language Model for Speech Recognition, Proceedings of the Workshop on Speech and Natural Language, pp.293-295, 1991.

J. , Q. , T. Schultz, and A. Waibel, Phonetic speaker identification, Proceedings of Interspeech, 2002.

J. , D. , D. Fohr, and I. Illina, Evaluating grapheme-to-phoneme converters in automatic speech recognition context, Proceedings of the IEEE International Conference on Acoustics, Speech and Signal Processing, pp.4821-4824, 2012.
URL : https://hal.archives-ouvertes.fr/hal-00753364

J. , D. Et, and D. Fohr, Combining forward-based and backward-based decoders for improved speech recognition performance, Proceedings of Interspeech, 2013.

J. , D. Et, and D. Langlois, A machine learning based approach for vocabulary selection for speech transcription, Proceedings of the 16th International Conference on Text, Speech and Dialogue (TSD). T. 8082, pp.60-67, 2013.

J. , B. H. Et, and S. Furui, Automatic speech recognition and understanding: A first step toward natural human machine communication, Proceedings of the IEEE. T. 88. 8, pp.1142-1165, 2000.

J. , D. , R. Bates, N. Coccaro, R. Martin et al., Automatic detection of discourse structure for speech recognition and understanding, IEEE Workshop on Automatic Speech Recognition and Understanding (ASRU), pp.88-95, 1997.

K. , S. W. Chou, and B. H. Juang, Pattern Recognition in Speech and Language Processing, 2003.

K. , F. Et, and M. Lapata, Using the Web to Obtain Frequencies for Unseen Bigrams, In : Computational Linguistics, vol.293, pp.459-484, 2003.

K. , T. , and T. Schaaf, Estimating confidence using word lattices, Proceedings of Eurospeech, 1997.

K. , O. , W. G. Al-khatib, and L. Cheded, A Preliminary Study Of Prosodybased Detection Of Questions In Arabic Speech Monologues, Arabian Journal for Science and Engineering2C, vol.35, pp.167-181, 2010.

K. , C. Et, and R. M. Stern, Power-normalized cepstral coefficients (PNCC) for robust speech recognition, Proceedings of the IEEE International Conference on Acoustics, Speech and Signal Processing, pp.4101-4104, 2012.

K. , J. Et, and L. Lamel, On Development of Consistently Punctuated Speech Corpora, Proceedings of Interspeech, pp.833-836, 2011.

K. , P. , J. Kleckova, and C. Cerisara, Sentence modality recognition in French based on prosody, International Conference on Enformatika, Systems Sciences and Engineering -ESSE 2005. T. 8, pp.185-188, 2005.
URL : https://hal.archives-ouvertes.fr/hal-00013968

K. , S. Et, and R. A. Leibler, On Information and Sufficiency, The Annals of Mathematical Statistics 22.1, pp.79-86, 1951.

K. , N. Et, and A. G. Andreou, Heteroscedastic discriminant analysis and reduced rank HMMs for improved speech recognition, Speech communication 26, pp.283-297, 1998.

K. , K. , J. W. Mcdonough, and B. Raj, Microphone Array Processing for Distant Speech Recognition: From Close-Talking Microphones to Far-Field Sensors, IEEE Signal Processing Magazine, vol.296, pp.127-140, 2012.

L. , P. Et, and I. Maddieson, The Sounds of the World's Languages, 1996.

L. Blouch, O. Et, and P. Collen, Reconnaissance automatique de phonemes guide par les syllables, 2006.

L. , G. , G. Gravier, and P. Sébillot, Automatically finding semantically consistent n-grams to add new words in LVCSR systems, Proceedings of the IEEE International Conference on Acoustics, Speech and Signal Processing, pp.4676-4679, 2011.
URL : https://hal.archives-ouvertes.fr/hal-00645223

L. , C. H. , L. R. Rabiner, R. Pieraccini, and J. G. Wilpon, Acoustic modeling for large vocabulary speech recognition, Computer Speech and Language, vol.4, issue.2, pp.127-165, 1990.

L. , K. F. , H. W. Hon, and R. Reddy, An overview of the SPHINX speech recognition system, IEEE Transactions on Acoustics, Speech and Signal Processing, vol.38, issue.1, pp.35-45, 1990.

L. , V. R. Et, and L. D. Erman, A Retrospective View of the HEARSAY-II Architecture, Proceedings of the Fifth International Joint Conference on Artificial Intelligence, pp.790-800, 1977.

L. , J. , J. Venditti, and J. Hirschberg, Detecting question-bearing turns in spoken tutorial dialogues, Proceedings of Interspeech, 2006.

L. , X. , M. J. Gales, and P. C. Woodl, Context dependent language model adaptation, Proceedings of Interspeech, 2008.

L. , V. , C. Gonzalez-morcillo, J. López, E. Ferreiro et al., Methodology for developing an advanced communications system for the Deaf in a new domain, Knowledge-Based Systems 56, pp.240-252, 2014.

M. , D. , L. Mauuary, B. Noé, Y. M. Cheng et al., Evaluation of a noise-robust DSR front-end on Aurora databases, Proceedings of Interspeech, 2002.

M. , A. , and M. Ostendorf, Question detection in spoken conversations using textual conversations, pp.118-124, 2011.

M. , J. A. Neustein, and J. A. Markowitz, Beyond SIRI: Exploring Spoken Language in Warehouse Operations, Offender Monitoring and Robotics " . In : Mobile Speech and Advanced Natural Language Solutions, pp.3-21, 2013.

M. , C. , A. J. Teixeira, and J. P. Neto, Automatic estimation of language model parameters for unseen words using morpho-syntactic contextual information, Proceedings of Interspeech, pp.1602-1605, 2008.

M. , W. S. Et, and W. Pitts, A logical calculus of the ideas immanent in nervous activity " . In : The bulletin of mathematical biophysics 5, pp.115-133, 1943.

M. , A. , D. Graff, and D. Dipersio, French Gigaword third edition, Proceedings of the Linguistic Data Consortium, 2011.

M. , T. , M. Karafiát, L. Burget, J. Cernock-`-ycernock-`-cernock-`-y et al., Recurrent neural network based language model, Proceedings of Interspeech, pp.1045-1048, 2010.

M. , T. , A. Deoras, S. Kombrink, L. Burget et al., Empirical Evaluation and Combination of Advanced Language Modeling Techniques, Proceedings of Interspeech. ISCA, 2011.

M. , T. , S. Kombrink, L. Burget, J. Cernocký et al., Extensions of recurrent neural network language model, Proceedings of the IEEE International Conference on Acoustics, Speech and Signal Processing, pp.5528-5531, 2011.

M. , T. , K. Chen, G. Corrado, and J. Dean, Efficient Estimation of Word Representations in Vector Space, 2013.

M. , B. Et, and K. Bruder, Philosophy: The Power Of Ideas: Ninth Edition, 2013.

M. , A. E. , M. A. Shaik, R. Schl-"-uter, and H. Ney, Morpheme Based Factored Language Models for German LVCSR, Proceedings of Interspeech, pp.1445-1448, 2011.

N. , W. , M. Tsuchiya, and S. Nakagawa, Class-Based N-Gram Language Model for New Words Using Out-of-Vocabulary to In-Vocabulary Similarity, IEICE Transactions on Information and Systems E95-D.9, pp.2308-2317, 2012.

N. , H. , U. Essen, and R. Kneser, On the estimation of 'small' probabilities by leaving-one-out, IEEE Transactions on Pattern Analysis and Machine Intelligence, vol.1712, pp.1202-1212, 1995.

N. , J. M. Et, and C. R. Frankish, Speech recognition technology for individuals with disabilities, Augmentative and Alternative Communication 8.4, pp.297-303, 1992.

O. , L. Et, and D. Jouvet, Comparison and Analysis of Several Phonetic Decoding Approaches, Proceedings of the 16th International Conference on Text, Speech and Dialogie (TSD), 2013.

P. , J. , J. Han, B. Mortazavi-asl, H. Pinto et al., PrefixSpan: Mining Sequential Patterns Efficiently by Prefix-Projected Pattern Growth, International Conference on Data Engineering, pp.215-224, 2001.

P. , A. , O. Mella, J. Miranda, D. Jouvet et al., Qualitative investigation of the display of speech recognition results for communication with deaf people, Workshop on Speech and Language Processing for Assistive Technologies (SLPAT), 2015.
URL : https://hal.archives-ouvertes.fr/hal-01183349

P. , A. , P. Ircing, and L. Müller, Language Model Adaptation Using Different Class-Based Models, Proceedings of SPECOM, pp.449-454, 2007.

Q. , V. M. , E. Castelli, and P. N. Yen, A decision tree-based method for speech processing: question sentence detection, Proceedings of the Third international conference on Fuzzy Systems and Knowledge Discovery, pp.1205-1212, 2006.

Q. , V. M. , L. Besacier, and E. Castelli, Automatic question detection: prosodic-lexical features and crosslingual experiments, Proceedings of Interspeech, pp.2257-2260, 2007.

R. , L. , S. Levinson, A. Rosenberg, and J. G. Wilpon, Speaker independent recognition of isolated words using clustering techniques, Proceedings of the IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP) 4, pp.574-577, 1979.

R. , L. Et, and B. Juang, Fundamentals of Speech Recognition, 1993.

R. , A. , A. Sethy, and B. Ramabhadran, A new method for OOV detection using hybrid word/fragment system, Proceedings of the IEEE International Conference on Acoustics, Speech and Signal Processing, pp.3953-3956, 2009.

R. , A. , A. Sethy, B. Ramabhadran, and F. Jelinek, Towards using hybrid word and fragment units for vocabulary independent LVCSR systems, Proceedings of Interspeech, pp.1931-1934, 2009.

R. , J. , O. Mella, D. Fohr, and J. Haton, Transcription automatique pour malentendants : amélioration à l'aide de mesures de confiance locales, 2008.

R. , J. , R. Dridan, S. Oepen, and J. L. Solberg, Sentence Boundary Detection: A Long Solved Problem, In : Proceedings of COLING, pp.985-994, 2012.

R. , C. , D. A. Schneider, R. E. Gur, F. Schneider et al., Multimodal human communication -Targeting facial expressions, speech content and prosody, pp.2346-2356, 2012.

R. , R. C. , B. Juang, and C. Lee, A training procedure for verifying string hypotheses in continuous speech recognition, Proceedings of the IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP). T. 1, pp.281-284, 1995.

R. , D. W. , S. K. Rogers, M. Kabrisky, M. E. Oxley et al., The multilayer perceptron as an approximation to a Bayes optimal discriminant function, IEEE Transactions on Neural Networks 1.4, pp.296-298, 1990.

S. , H. , A. W. Senior, and F. Beaufays, Long short-term memory recurrent neural network architectures for large scale acoustic modeling, Proceedings of Interspeech, pp.338-342, 2014.

S. , R. , and H. Ney, Using phase spectrum information for improved speech recognition performance, Proceedings of the IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP). T. 1, pp.133-136, 2001.

S. , M. A. , A. E. Mousa, R. Schlüter, and H. Ney, Hybrid Language Models Using Mixed Types of Sub-Lexical Units for Open Vocabulary German LVCSR, Proceedings of Interspeech, pp.1441-1444, 2011.

S. , M. A. , A. E. Mousa, R. Schlüter, and H. Ney, Using morpheme and syllable based sub-words for Polish LVCSR, Proceedings of the IEEE International Conference on Acoustics, Speech and Signal Processing, pp.4680-4683, 2011.

R. C. Simpson, Voice control of a powered wheelchair, IEEE Transactions on Neural Systems and Rehabilitation Engineering 10.2, pp.122-125, 2002.
DOI : 10.1109/TNSRE.2002.1031981

S. , N. , M. Collins, and T. J. Hazen, Dimensionality reduction for speech recognition using neighborhood components analysis, Proceedings of Interspeech, pp.1158-1161, 2007.

S. , A. , T. Ramabadran, D. Chazan, R. Hoory et al., The ETSI extended distributed speech recognition (DSR) standards: client side processing and tonal language recognition evaluation, Proceedings of the IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP). T. 1, pp.129-132, 2004.

S. , B. Et, and A. Waibel, Towards better language models for spontaneous speech, The 3rd International Conference on Spoken Language Processing (ICSLP). ISCA, 1994.

S. , P. , A. Ghoshal, and S. Renals, Hybrid acoustic models for distant and multichannel large vocabulary speech recognition, IEEE Workshop on Automatic Speech Recognition and Understanding (ASRU), pp.285-290, 2013.

S. , I. , L. Burget, J. Cernocký, and M. Fapso, Sub-word modeling of out of vocabulary words in spoken term detection " . In : Spoken Language Technology Workshop (SLT), pp.273-276, 2008.

T. , M. Y. , S. Abate, and W. Menzel, Using morphemes in language modeling and automatic speech recognition of Amharic, In : Natural Language Engineering, pp.235-259, 2014.

T. , M. , S. Abate, L. Besacier, and S. Rossato, Syllable-based and hybrid acoustic models for Amharic speech recognition, Workshop on Spoken Language Technologies for Under-Resourced Languages (SLTU), pp.5-10, 2012.
URL : https://hal.archives-ouvertes.fr/hal-00954042

T. , K. W. , R. Kamoua, V. Sutan, O. Farooq et al., Speech recognition technology for disabilities education, Journal of Educational Technology Systems, vol.33, issue.2, pp.173-184, 1994.

T. , C. Et, and C. Juang, Recurrent type-2 fuzzy neural network using Haar wavelet energy and entropy features for speech detection in noisy environments, Expert systems with applications 39.3, pp.2479-2488, 2012.

T. , P. D. Et, and P. Pantel, From Frequency to Meaning: Vector Space Models of Semantics, Journal of Artificial Intelligence Research, vol.37, issue.1, pp.141-188, 2010.

M. Vacher, B. Lecouteux, and F. Portet, Multichannel Automatic Recognition of Voice Command in a Multi-Room Smart Home : an Experiment involving Seniors and Users with Visual Impairment, Proceedings of Interspeech, pp.1008-1012, 2014.
URL : https://hal.archives-ouvertes.fr/hal-01003492

V. , A. , Y. Zhao, V. Fossum, and D. Chiang, Decoding with Large-Scale Neural Language Models Improves Translation, pp.1387-1392, 2013.

V. , E. , A. Sini, and F. Charpillet, Audio source localization by optimal control of a mobile robot, Proceedings of the IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP), 2015.
URL : https://hal.archives-ouvertes.fr/hal-01103949

W. , R. A. Et, and M. J. Fischer, The String-to-String Correction Problem, Journal of the ACM, vol.21, issue.1, pp.168-173, 1974.

W. , A. , T. Hanazawa, G. Hinton, K. Shikano et al., Phoneme recognition using time-delay neural networks, IEEE Transactions on Acoustics, Speech and Signal Processing, vol.373, pp.328-339, 1989.

W. , D. Et, and S. King, Letter-to-sound pronunciation prediction using conditional random fields, Signal Processing Letters 18, 2011.

W. , M. , H. Murveit, M. Cohen, P. Price et al., Linguistic constraints in hidden Markov model based speech recognition, Proceedings of the IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP). T. 2, pp.699-702, 1989.

W. , M. , F. Beaufays, Z. Rivlin, Y. Konig et al., Neuralnetwork based measures of confidence for word recognition, Proceedings of the IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP), pp.887-890, 1997.

W. , F. , K. Macherey, and H. Ney, A Comparison Of Word Graph And N-Best List Based Confidence Measures, Proceedings of Eurospeech, pp.315-318, 1999.

W. , F. , R. Schlüter, K. Macherey, and H. Ney, Confidence Measures for Large Vocabulary Continuous Speech Recognition, IEEE Transactions on Speech and Audio Processing 9, pp.288-298, 2001.

W. , J. J. Et, and W. A. Woods, The HWIM speech understanding system, Proceedings of the IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP) 2, pp.784-787, 1977.

W. , M. Et, and C. Nadeu, Channel Selection Measures for Multi-Microphone Speech Recognition, Speech Communication, vol.57, pp.170-180, 2013.

W. , S. , B. Kingsbury, N. Morgan, and S. Greenberg, Incorporating Information From Syllable-Length Time Scales Into Automatic Speech Recognition, Proceedings of the IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP), pp.721-724, 1998.

X. , P. Et, and F. Jelinek, Random forests and the data sparseness problem in language modeling, Computer Speech & Language 21.1, pp.105-152, 2007.

Y. , Y. Et, and E. Barnard, An approach to automatic language identification based on language-dependent phone recognition, Proceedings of the IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP), pp.3511-3514, 1995.

Y. , A. , and M. Saraclar, Hybrid language models for out of vocabulary word detection in large vocabulary conversational speech recognition, Proceedings of the IEEE International Conference on Acoustics, Speech and Signal Processing, pp.745-748, 2004.

Y. , S. J. , D. Kershaw, J. Odell, D. Ollason et al., The HTK Book Version 3.4, 2006.

Y. , D. Et, and M. L. Seltzer, Improved Bottleneck Features Using Pretrained Deep Neural Networks, Proceedings of Interspeech, pp.237-240, 2011.

Y. , J. Et, and D. Jurafsky, Detection of questions in Chinese conversational speech, IEEE Workshop on Automatic Speech Recognition and Understanding (ASRU), pp.47-52, 2005.

Z. , R. Et, and A. I. Rudnicky, Word level confidence annotation using combinations of features, Proceedings of Eurospeech, 2001.

Z. , A. , R. Schlüter, and H. Ney, Acoustic Feature Combination for Robust Speech Recognition, Proceedings of the IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP). T. 1, pp.457-460, 2005.

Z. , V. , J. Glass, M. Phillips, and S. Seneff, The MIT SUMMIT Speech Recognition System: A Progress Report, Proceedings of the Workshop on Speech and Natural Language, pp.179-189, 1989.

O. Publications-personnelles, L. Et, and D. Jouvet, Comparison and Analysis of Several Phonetic Decoding Approaches, Proceedings of the 16th International Conference on Text, Speech and Dialogie (TSD), 2013.