M. Adda-decker and L. Lamel, Pronunciation variants across system configuration, language and speaking style, Speech Communication, vol.29, issue.2-4, pp.83-98, 1999.
DOI : 10.1016/S0167-6393(99)00032-1

L. Adde, B. Rveil, J. Martens, and T. Svendsen, A minimum classification error approach to pronunciation variation modeling of non-native proper names, Proc. of Interspeech, pp.2282-2285, 2010.

M. Akbacak, D. Vergyri, and A. Stolcke, Open-vocabulary spoken term detection using graphone-based hybrid recognition systems, 2008 IEEE International Conference on Acoustics, Speech and Signal Processing, pp.5240-5243, 2008.
DOI : 10.1109/ICASSP.2008.4518841

Y. Akita and T. Kawahara, Generalized Statistical Modeling of Pronunciation Variations using Variable-length Phone Context, Proceedings. (ICASSP '05). IEEE International Conference on Acoustics, Speech, and Signal Processing, 2005., pp.689-692, 2005.
DOI : 10.1109/ICASSP.2005.1415207

C. Allauzen, M. Mohri, and B. Roark, Generalized algorithms for constructing statistical language models, Proceedings of the 41st Annual Meeting on Association for Computational Linguistics , ACL '03, pp.40-47, 2003.
DOI : 10.3115/1075096.1075102

C. Allauzen, M. Mohri, and M. Saraclar, General indexation of weighted automata:application to spoken utterance retrieval, Proc. of HLT-NAACL, 2004.

C. Allauzen, M. Riley, J. Schalkwyk, W. Skut, and M. Mohri, OpenFst: A General and Efficient Weighted Finite-State Transducer Library, Proc. of the 12th international conference on Implementation and application of automata, CIAA'07, pp.11-23, 2007.
DOI : 10.1007/978-3-540-76336-9_3

I. Amdal, F. Korkmazsdiy, and A. C. Surendran, Data-driven pronunciation modelling for non-native speakers using association strength between phones, Proc. of ASRU, pp.85-90, 2000.

A. Antilla, Variation and Phonological Theory, 2002.
DOI : 10.1002/9780470756591.ch8

X. L. Aubert, A brief overview of decoding techniques for large vocabulary continuous speech recognition, Automatic Speech Recognition: Challenges for the new Millenium (ASR2000), pp.91-97, 2000.

I. Badr, J. Mcgraw, and . Glass, Learning new word pronunciations from spoken examples, Proc. of Interspeech, 2010.

C. Bannard and C. Callison-burch, Paraphrasing with bilingual parallel corpora, Proceedings of the 43rd Annual Meeting on Association for Computational Linguistics , ACL '05, pp.597-604, 2005.
DOI : 10.3115/1219840.1219914

F. Beaufays, A. Sankar, S. Williams, and M. Weintraub, Learning linguistically valid pronunciations from acoustic data, Proc. of Interspeech, 2003.

F. Béchet and F. Yvon, Les noms propres en traitement automatique de la parole, Traitement Automatique des Langues, vol.41, issue.3, pp.671-707, 2000.

J. R. Bellegarda, Unsupervised, language-independent grapheme-to-phoneme conversion by latent analogy, Speech Communication, vol.46, issue.2, pp.140-152, 2005.
DOI : 10.1016/j.specom.2005.03.002

J. Bilmes and G. Zweig, The graphical models toolkit: An open source software system for speech and time-series processing, ICASSP, pp.3916-3919, 2002.

M. Bisani and H. Ney, Investigations on joint-multigram models for grapheme-tophoneme conversion, Proc. of ICSLP, 2002.

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

N. Bodenstab and M. Fanty, Multi-Pass Pronunciation Adaptation, 2007 IEEE International Conference on Acoustics, Speech and Signal Processing, ICASSP '07, pp.865-868, 2007.
DOI : 10.1109/ICASSP.2007.367207
URL : http://citeseerx.ist.psu.edu/viewdoc/summary?doi=10.1.1.115.7940

L. Bottou, Large-scale machine learning with stochastic gradient descent, Proc. of the 19th International Conference on Computational Statistics (COMPSTAT'2010), pp.177-187, 2010.

L. Breiman, J. Friedman, C. J. Stone, and R. Olshen, Classification and regression trees, 1984.

P. F. Brown, V. J. Pietra, S. A. Pietra, and R. L. Mercer, The mathematics of statistical machine translation: Parameter estimation, Computational linguistics, vol.19, issue.2, pp.263-311, 1993.

D. Can and M. Saraclar, Lattice Indexing for Spoken Term Detection, IEEE Transactions on Audio, Speech, and Language Processing, vol.19, issue.8, pp.2338-2347, 2011.
DOI : 10.1109/TASL.2011.2134087

D. Can, E. Cooper, A. Sethy, C. White, B. Ramabhadran et al., Effect of pronunciations on oov queries in spoken term detection, ICASSP, pp.3957-3960, 2009.

L. Chase, Error-responsive feedback mechanisms for speech recognizers, 1997.

N. F. Chen, Informative dialect recognition using context-dependent pronunciation modeling, 2011 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP), pp.4396-4399, 2011.
DOI : 10.1109/ICASSP.2011.5947328

S. F. Chen, Conditional and joint models for grapheme-to-phoneme conversion, Proc. of Eurospeech, pp.2033-2036, 2003.

Y. Chen, P. Liu, J. You, and F. K. Soong, Discriminative training for improving letter-to-sound conversion performance, ICASSP, pp.4649-4652, 2008.

N. Chomsky and M. Halle, The Sound Pattern of English, 1968.

G. F. Choueiter, S. Seneff, and J. R. Glass, Automatic lexical pronunciations generation and update, 2007 IEEE Workshop on Automatic Speech Recognition & Understanding (ASRU), pp.225-230, 2007.
DOI : 10.1109/ASRU.2007.4430113
URL : http://citeseerx.ist.psu.edu/viewdoc/summary?doi=10.1.1.154.4877

A. W. Coetzee and S. Kawahara, Frequency biases in phonological variation, Natural Language & Linguistic Theory, vol.28, issue.1, pp.1-43, 2012.
DOI : 10.1007/s11049-012-9179-z

M. Collins, Discriminatively training methods for hmms. theory and experiments with perceptron algorithm, Proc. of ACL-02:EMNLP, pp.1-8, 2002.

C. Cortes, M. Mohri, A. Rastogi, and M. D. Riley, Efficient Computation of the Relative Entropy of Probabilistic Automata, Proc. of the 7th Latin American conference on Theoretical Informatics, pp.323-336, 2006.
DOI : 10.1007/11682462_32

T. M. Cover and J. A. Thomas, Elements of information theory, 1991.

N. Cremelie and J. Martens, In search of better pronunciation models for speech recognition, Speech Communication, vol.29, issue.2-4, pp.115-136, 1999.
DOI : 10.1016/S0167-6393(99)00034-5

M. Dedina and H. Nusbaum, PRONOUNCE: a program for pronunciation by analogy, Computer Speech & Language, vol.5, issue.1, pp.55-64, 1991.
DOI : 10.1016/0885-2308(91)90017-K

S. Deligne, F. Yvon, and F. Bimbot, Variable-length sequence matching for phonetic transcription using joint multigrams, Proc. of Eurospeech, 1995.

Y. Deng, M. Mahajan, and A. Acero, Estimating speech recognition error rate without acoustic test data, Proc. of Eurospeech, pp.929-932, 2003.

T. G. Dietterich and G. Bakiri, Solving multiclass learning problems via error-correcting output codes, Journal of Artificial Intelligence, 1995.

M. Divay and A. Vitale, Algorithms for grapheme-phoneme translation for english and french: Applications for database searches and speech synthesis, Computational linguistics, vol.23, issue.4, pp.495-523, 1997.

J. Eisner, Expectation semiring: Flexible em for learning finite-state transducers, Proc. of FSMNLP, 2001.

J. Eisner, Parameter estimation for probabilistic finite-state transducers, Proceedings of the 40th Annual Meeting on Association for Computational Linguistics , ACL '02, pp.1-8, 2002.
DOI : 10.3115/1073083.1073085

E. Fosler-lussier, Dynamic Pronunciation Models for Automatic Speech Recognition, 1999.

E. Fosler-lussier and G. Williams, Not just what, but also when: Guided automatic pronunciation modeling for broadcast news, DARPA Broadcast News Workshop, pp.171-174, 1999.

E. Fosler-lussier, I. Amdal, and H. J. Kuo, On the road to improved lexical confusability metrics, Workshop on Pronunciation Modeling and Lexicon Adaptation for Spoken Language Technology, PMLA, pp.53-58, 2002.

E. Fosler-lussier, I. Amdal, and H. K. Kuo, A framework for predicting speech recognition errors. Speech Communication issue on Pronunciation Modeling and Lexicon Adaptation, pp.153-170, 2005.

Y. Freund and R. Schapire, Large margin classification using the perceptron algorithm, Proceedings of the eleventh annual conference on Computational learning theory , COLT' 98, pp.277-296, 1999.
DOI : 10.1145/279943.279985

T. Fukada, T. Yoshimura, and Y. Sagisaka, Automatic generation of multiple pronunciations based on neural networks, Speech Communication, vol.27, issue.1, pp.63-73, 1999.
DOI : 10.1016/S0167-6393(98)00066-1

M. Gales and S. Young, The Application of Hidden Markov Models in Speech Recognition, Foundations and Trends?? in Signal Processing, vol.1, issue.3, pp.195-304, 2007.
DOI : 10.1561/2000000004

J. L. Gauvain, L. Lamel, and G. Adda, Partitioning and transcription of broadcast news data, Proc. of ICSLP, 1998.

J. L. Gauvain, L. Lamel, and G. Adda, The LIMSI Broadcast News transcription system, Speech Communication, vol.37, issue.1-2, pp.89-108, 2002.
DOI : 10.1016/S0167-6393(01)00061-9
URL : https://hal.archives-ouvertes.fr/hal-01434493

M. Gerosa and M. Federico, Coping with out-of-vocabulary words:open versus huge vocabulary asr, ICASSP, 2009.

K. Gimpel and N. A. Smith, Softmax-margin crfs: Training log-linear models with cost functions, Proc. of HLT-NAACL, pp.733-736, 2010.

N. Goel, M. Thomas, S. Agarwal, P. Akyazi, L. Burget et al., Approaches to automatic lexicon learning with limited training examples, 2010 IEEE International Conference on Acoustics, Speech and Signal Processing, pp.5094-5097, 2010.
DOI : 10.1109/ICASSP.2010.5495037

V. Goel, S. Kumar, and W. Byrne, Segmental Minimum Bayes-Risk Decoding for Automatic Speech Recognition, IEEE Transactions on Speech and Audio Processing, vol.12, issue.3, pp.234-249, 2004.
DOI : 10.1109/TSA.2004.825678

S. Goronzy and R. Kompe, Generating non-native pronunciation variants for lexicon adaptation, Speech Communication, vol.42, issue.1, pp.109-123, 2004.
DOI : 10.1016/j.specom.2003.09.003

Y. Grandvalet and Y. Bengio, Entropy regularization, Semi-Supervised Learning, pp.151-168, 2006.

S. Greenberg, S. Chang, and J. Hollenback, An introduction to the diagnostic evaluation of the switchboard-corpus automatic speech recognition systems, Proc. of NIST Speech Transcription Workshop, pp.16-19, 2000.

T. Hain, Implicit modelling of pronunciation variation in automatic speech recognition, Speech Communication, vol.46, issue.2, pp.171-188, 2005.
DOI : 10.1016/j.specom.2005.03.008

T. J. Hazen, I. Lee-hetherington, H. Shu, and K. Livescu, Pronunciation modeling using a finite-state transducer representation, Speech Communication, vol.46, issue.2, pp.189-203, 2005.
DOI : 10.1016/j.specom.2005.03.004

G. Heigold, A Log-Linear Discriminative Modeling Framework for Speech Recognition, 2010.

J. Holmes and W. Holmes, Speech Synthesis and Recognition, 2002.

T. Holter and T. Svendsen, Maximum likelihood modelling of pronunciation variation, Speech Communication, vol.29, issue.2-4, pp.177-191, 1999.
DOI : 10.1016/S0167-6393(99)00036-9

C. Huang, T. Cahen, and E. Chang, Accent Issues in Large Vocabulary Continuous Speech Recognition, International Journal of Speech Technology, vol.7, issue.2/3, pp.141-153, 2004.
DOI : 10.1023/B:IJST.0000017014.52972.1d

I. Illina, D. Fohr, and D. Jouvet, Grapheme-to-phoneme conversion using conditional random fields, Proc. of Interspeech, pp.2313-2316, 2011.
URL : https://hal.archives-ouvertes.fr/inria-00614981

M. Jansche, Inference of string mappings for language technology, 2003.

F. Jelinek, Fast Sequential Decoding Algorithm Using a Stack, IBM Journal of Research and Development, vol.13, issue.6, pp.675-685, 1969.
DOI : 10.1147/rd.136.0675

S. Jiampojamarn, C. Cherry, and G. Kondrak, Joint processing and discriminative training for letter-to-phoneme conversion, Proc. of ACL-08:HLT, pp.905-913, 2008.

D. Jurafsky, W. Ward, Z. Banping, K. Herold, Y. Xiuyang et al., What kind of pronunciation variation is hard for triphones to model?, 2001 IEEE International Conference on Acoustics, Speech, and Signal Processing. Proceedings (Cat. No.01CH37221), pp.577-580, 2001.
DOI : 10.1109/ICASSP.2001.940897

P. Jyothi and E. Fosler-lussier, A comparison of audio-free speech recognition error prediction methods, Proc. of Interspeech, pp.1211-1214, 2009.

P. Jyothi, E. Fosler-lussier, and K. Livescu, Discriminatively learning factorized finite state pronunciation models from dynamic bayesian networks, Proc. of Interspeech, 2012.

E. M. Kaisse, Word-Formation and Phonology, 2005.
DOI : 10.1007/1-4020-3596-9_2

P. Karanasou and L. Lamel, Pronunciation variants generation using SMT-inspired approaches, 2011 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP), pp.4908-4911, 2011.
DOI : 10.1109/ICASSP.2011.5947456

J. M. Kessens, M. Wester, and H. Strik, Improving the performance of a Dutch CSR by modeling within-word and cross-word pronunciation variation, Speech Communication, vol.29, issue.2-4, pp.193-207, 1999.
DOI : 10.1016/S0167-6393(99)00048-5

A. Kipp, M. Weswnick, and F. Schiel, Pronunciation modeling applied to automatic segmentation of spontaneous speech, Proc. of Eurospeech, pp.1023-1026, 1997.

P. Koehn, F. J. Och, and D. Marcu, Statistical phrase-based translation, Proceedings of the 2003 Conference of the North American Chapter of the Association for Computational Linguistics on Human Language Technology , NAACL '03, pp.48-54, 2003.
DOI : 10.3115/1073445.1073462

P. Koehn, H. Hoang, A. Birch, C. Callison-burch, M. Federico et al., Moses:open source toolkit for statistical machine translation, Annual meetingassociation for computational linguistics, pp.177-180, 2007.

P. Ladefoged, A course in phonetics, 2006.

J. Lafferty, A. Mccallum, and P. Pereira, Conditional random fields: Probabilistic models for segmenting and labeling sequence data, Proc. of ICML, 2001.

L. Lamel and G. Adda, On designing pronunciation lexicons for large vocabulary continuous speech recognition, Proceeding of Fourth International Conference on Spoken Language Processing. ICSLP '96, pp.6-9, 1996.
DOI : 10.1109/ICSLP.1996.606916

A. Laurent, P. Deleglise, and S. Meignier, Grapheme to phoneme conversion using an smt system, Proc. of Interspeech, 2009.
URL : https://hal.archives-ouvertes.fr/hal-01451534

T. Lavergne, O. Cappé, and F. Yvon, Practical very large scale crfs, Proc. of the 48th Annual Meeting of the Association for Computational Linguistics, pp.504-513, 2010.

K. F. Lee and H. W. Hon, Speaker-independent phone recognition using hidden Markov models, IEEE Transactions on Acoustics, Speech, and Signal Processing, vol.37, issue.11, pp.1641-1648, 1989.
DOI : 10.1109/29.46546

P. Lehnen, S. Hahn, A. Guta, and H. Ney, Incorporating alignments into Conditional Random Fields for grapheme to phoneme conversion, 2011 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP), pp.4916-4919, 2011.
DOI : 10.1109/ICASSP.2011.5947458

B. Logan, P. Moreno, J. V. Thong, and E. Whittake, An experimental study of an audio indexing system for the web, Proc. of ICSLP, pp.676-679, 2000.

L. Mangu, E. Brill, and A. Stolcke, Finding consensus among words: Lattice-based word error minimization, Proc. of Eurospeech, 1999.

L. Mangu, E. Brill, and A. Stolcke, Finding consensus in speech recognition: word error minimization and other applications of confusion networks, Computer Speech & Language, vol.14, issue.4, pp.373-400, 2000.
DOI : 10.1006/csla.2000.0152

D. Mcallaster, L. Gillick, F. Scattone, and M. Newman, Fabricating conversational speech data with acoustic models: a program to examine model-data mismatch, ICSLP, 1998.

I. Mcgraw, I. Badr, and J. R. Glass, Learning Lexicons From Speech Using a Pronunciation Mixture Model, IEEE Transactions on Audio, Speech, and Language Processing, vol.21, issue.2, pp.357-366, 2013.
DOI : 10.1109/TASL.2012.2226158

M. Mohri, Finite-state transducers in language and speech processing, Computational Linguistics, vol.23, issue.2, pp.269-311, 1997.

M. Mohri, Weighted automata algorithms. Handbook of weighted automata, pp.213-254, 2009.
DOI : 10.1007/978-3-642-01492-5_6
URL : http://citeseerx.ist.psu.edu/viewdoc/summary?doi=10.1.1.308.1601

M. Mohri, F. Pereira, and M. Riley, Weighted finite-state transducers in speech recognition, Computer Speech & Language, vol.16, issue.1, pp.69-88, 2002.
DOI : 10.1006/csla.2001.0184

N. Moreau, H. G. Kim, and T. Sikora, Phonetic confusion based document expansion for spoken document retrieval, ICSLP Interspeech, 2004.

S. Nakamura, R. Gruhn, and H. Binder, Recognition of non-native speech using dynamic phoneme lattice processing, Acoustic Society of Japan, 2002.

F. J. Och and H. Ney, Improved statistical alignment models, Proceedings of the 38th Annual Meeting on Association for Computational Linguistics , ACL '00, pp.440-447, 2000.
DOI : 10.3115/1075218.1075274
URL : http://acl.ldc.upenn.edu/P/P00/P00-1056.pdf

B. Oshika, V. Zue, R. Weeks, H. Neu, and J. Aurbach, The role of phonological rules in speech understanding research, IEEE Transactions on Acoustics, Speech, and Signal Processing, vol.23, issue.1, pp.104-112, 1975.
DOI : 10.1109/TASSP.1975.1162639

V. Pagel, K. Lenzo, and A. W. Black, Letter-to-sound rules for accented lexicon compression, Proc. of ICSLP, pp.2015-2018, 1998.

K. Papineni, S. Roukos, T. Ward, and W. Zhu, BLEU, Proceedings of the 40th Annual Meeting on Association for Computational Linguistics , ACL '02, pp.311-318, 2002.
DOI : 10.3115/1073083.1073135

C. Parada, A. Sethy, and B. Ramabhadran, Balancing false alrams and hits in spoken term detection, ICASSP, pp.5286-5289, 2010.
DOI : 10.1109/icassp.2010.5494966
URL : http://citeseerx.ist.psu.edu/viewdoc/summary?doi=10.1.1.169.2986

D. B. Paul, Algorithms for an optimal a* search and linearizing the search in the stack decoder, ICASSP, pp.693-696, 1991.

A. Paz, Introduction to probabilistic automata, 1971.

F. C. Pereira and M. D. Riley, Speech recognition by composition of weighted finite automata, Finite-State Language Processing, pp.431-453, 1996.

J. Pinto, A. Lovitt, and H. Hermansky, Exploiting phoneme similarities in hybrid hmmann keyword spotting, Proc. of Interspeech, pp.1817-1820, 2007.

D. Povey, Discriminative Training for Large Vocabulary Speech Recognition, 2003.

D. Povey, D. Kanevsky, B. Kingsbury, B. Ramabhadran, G. Saon et al., Boosted MMI for model and feature-space discriminative training, 2008 IEEE International Conference on Acoustics, Speech and Signal Processing, pp.4057-4060, 2008.
DOI : 10.1109/ICASSP.2008.4518545

A. Prince and P. Smolensky, Optimality Theory: Constraint Interaction in Generative Grammar, 2004.
DOI : 10.1002/9780470756171.ch1

H. Printz and P. Olsen, Theory and practice of acoustic confusability, Proc. of ISCA ITRW ASR, pp.77-84, 2000.
DOI : 10.1006/csla.2001.0188

M. Pucher, A. Türk, J. Ajmera, and N. Fecher, Phonetic distance measures for speech recognition vocabulary and grammar optimization, 3rd Congress of the Alps Adria Acoustics Association, pp.2-5, 2007.

T. Rama, A. K. Singh, and S. Kolachina, Modeling letter-to-phoneme conversion as a phrase based statistical machine translation problem with minimum error rate training, Proceedings of Human Language Technologies: The 2009 Annual Conference of the North American Chapter of the Association for Computational Linguistics, Companion Volume: Student Research Workshop and Doctoral Consortium on, NAACL '09, 2009.
DOI : 10.3115/1620932.1620948

V. Raykar, R. Duraiswami, and B. Krishnapuram, A fast algorithm for learning large scale preference relations, Proc. of the Eleventh International Conference on Artificial Intelligence and Statistics, pp.385-392, 2007.

G. Riccardi, R. Pieraccini, and E. Bocchieri, Stochastic automata for language modeling, Computer Speech & Language, vol.10, issue.4, pp.265-293, 1996.
DOI : 10.1006/csla.1996.0014

M. Riley, W. Byrne, M. Finke, S. Khudanpur, A. Ljolje et al., Stochastic pronunciation modelling from hand-labelled phonetic corpora, Speech Communication, vol.29, issue.2-4, pp.209-224, 1999.
DOI : 10.1016/S0167-6393(99)00037-0

B. Roark, M. Saraclar, M. Collins, and M. Johnson, Discriminative language modeling with conditional random fields and the perceptron algorithm, Proceedings of the 42nd Annual Meeting on Association for Computational Linguistics , ACL '04, p.47, 2004.
DOI : 10.3115/1218955.1218962

H. Robbins and S. Monro, A Stochastic Approximation Method, The Annals of Mathematical Statistics, vol.22, issue.3, pp.400-407, 1951.
DOI : 10.1214/aoms/1177729586

J. R. Rohlicek, W. Russell, S. Roukos, and H. Gish, Continuous hidden Markov modeling for speaker-independent word spotting, International Conference on Acoustics, Speech, and Signal Processing, pp.627-630, 1989.
DOI : 10.1109/ICASSP.1989.266505

A. Salomaa and M. Soittola, Automata-Theoretic Aspects of Formal Power Series, 1978.
DOI : 10.1007/978-1-4612-6264-0

M. Saraclar and S. Khudanpur, Pronunciation ambiguity vs. pronunciation variability in speech recognition, 2000 IEEE International Conference on Acoustics, Speech, and Signal Processing. Proceedings (Cat. No.00CH37100), pp.515-518, 1999.
DOI : 10.1109/ICASSP.2000.862073

M. Saraclar and S. Khudanpur, Pronunciation change in conversational speech and its implications for automatic speech recognition, Computer Speech & Language, vol.18, issue.4, pp.375-395, 2004.
DOI : 10.1016/j.csl.2003.09.005

M. Saraclar and R. Sproat, Lattice-based search for spoken utterance retrieval, Proc. of the HLT-NAACL, pp.129-136, 2004.

T. Sejnowski and C. Rosenberg, Nettalk: a parallel network that learns to read aloud, Report JHU/EECS-86/01, 1986.

H. Shu and I. L. Hetherington, Em training of finite-state transducers and its application to pronunciation modeling, Proc. of ICSLP, pp.1293-1296, 2002.

T. Sloboda and A. Waibel, Dictionary learning for spontaneous speech recognition, Proceeding of Fourth International Conference on Spoken Language Processing. ICSLP '96, pp.2328-2331, 1996.
DOI : 10.1109/ICSLP.1996.607274

N. A. Smith, Linguistic Structure Prediction, Synthesis Lectures on Human Language Technologies, vol.4, issue.2, 2011.
DOI : 10.2200/S00361ED1V01Y201105HLT013

M. F. Spiegel, Using the orator synthesizer for a public reverse-directory service:design, lessons, and recommendations, Proc. of Eurospeech, pp.1897-1900, 1993.

V. Steinbiss, Sentence-hypotheses generation in a continuous-speech recognition system, Proc. of European Conference on Speech Communication and Technology, pp.51-54, 1989.

A. Stolcke, Srilm-an extensible language modeling toolkit, Proc. of ICSLP, 2002.

H. Strik and C. Cucchiarini, Modeling pronunciation variation for ASR: A survey of the literature, Speech Communication, vol.29, issue.2-4, pp.225-246, 1999.
DOI : 10.1016/S0167-6393(99)00038-2

N. Stroppa, Analogy-Based Models for Natural Language Learning, 2005.
URL : https://hal.archives-ouvertes.fr/tel-00145147

T. Svendsen, F. K. Soong, and H. Purnhagen, Optimizing baseforms for hmm-based speech recognition, Proc. of Eurospeech, p.1, 1995.

H. Tang, J. Keshet, and K. Livescu, Discriminative pronunciation modeling: a largemargin , feature-rich approach, Proc. of ACL, pp.194-203, 2012.

P. Taylor, Hidden markov models for grapheme to phoneme conversion, Proc. of Interspeech, 2005.

J. Tejedor, D. Wang, S. King, J. Frankel, and J. Cols, A posterior probability-based system hybridisation and combination for spoken term detection, Proc. of Interspeech, pp.2131-2134, 2009.

R. Tibshirani, Regression shrinkage and selection via the lasso, Journal of the Royal Statistical Society. Series B (Methodological), pp.267-288, 1996.

M. Tsai, F. Chou, and L. Lee, Improved pronunciation modeling by inverse word frequency and pronunciation entropy, Proc. of ASRU, pp.53-56, 2001.

M. Tsai, F. Chou, and L. , Pronunciation Modeling With Reduced Confusion for Mandarin Chinese Using a Three-Stage Framework, IEEE Transactions on Audio, Speech and Language Processing, vol.15, issue.2, pp.661-675, 2007.
DOI : 10.1109/TASL.2006.876769

C. Van-bael, L. Boves, H. Van-den-heuvel, and H. Strik, Automatic phonetic transcription of large speech corpora, Computer Speech & Language, vol.21, issue.4, pp.652-668, 2007.
DOI : 10.1016/j.csl.2007.03.003

B. Van-berkel and K. Smedt, Triphone analysis, Proceedings of the second conference on Applied natural language processing -, 1988.
DOI : 10.3115/974235.974250

A. Van-den, S. Bosch, and . Canisius, Improved morpho-phonological sequence processing with constraint satisfaction inference, Proceedings of the Eighth Meeting of the ACL Special Interest Group on Computational Phonology and Morphology, SIGPHON '06, pp.41-49, 2006.
DOI : 10.3115/1622165.1622171

H. Van-den-heuvel, J. Martens, and N. Konings, G2p conversion of names. what can we do (better), Proc. of Interspeech, pp.1773-1776, 2007.

H. Van-den-heuvel, B. Reveil, and J. Martens, Pronunciation-based asr for names, Proc of Interspeech, pp.2991-2994, 2009.

C. J. Van-rijsbergen, Information retrieval, In Butterworths, 1979.

B. Vazirnezhad, F. Almasganj, and M. Bijankhan, A Hybrid Statistical Model to Generate Pronunciation Variants of Words, 2005 International Conference on Natural Language Processing and Knowledge Engineering, pp.106-110, 2005.
DOI : 10.1109/NLPKE.2005.1598716

U. Venkataramani and W. Byrne, MLLR adaptation techniques for pronunciation modeling, IEEE Workshop on Automatic Speech Recognition and Understanding, 2001. ASRU '01., pp.421-424, 2001.
DOI : 10.1109/ASRU.2001.1034674

D. Vergyri, I. Shafran, A. Stolcke, V. R. Gadde, M. Akbacak et al., The sri/ogi 2006 spoken term detection system, Proc. of Interspeech, pp.2393-2396, 2007.

O. Vinyals, L. Deng, D. Yu, and A. Acero, Discriminative pronunciation learning using phonetic decoder and minimum-classification-error, ICASSP, pp.4445-4448, 2009.
DOI : 10.1109/icassp.2009.4960616

R. Wallace, B. Baker, R. Vogt, and S. Sridharan, Discriminative Optimization of the Figure of Merit for Phonetic Spoken Term Detection, IEEE Transactions on Audio, Speech, and Language Processing, vol.19, issue.6, pp.1677-1687, 2011.
DOI : 10.1109/TASL.2010.2096215

C. Wang and P. Zhang, Optimization of Spoken Term Detection System, Journal of Applied Mathematics, vol.2012, 2012.
DOI : 10.1016/j.specom.2003.11.002

D. Wang and S. King, Letter-to-Sound Pronunciation Prediction Using Conditional Random Fields, IEEE Signal Processing Letters, vol.18, issue.2, pp.122-125, 2011.
DOI : 10.1109/LSP.2010.2098440

D. Wang, S. King, and J. Frankel, Stochastic pronunciation modelling for spoken term detection, Proc. of Interspeech, pp.2135-2138, 2009.

W. Ward, H. Krech, X. Yu, K. Herold, G. Figgs et al., Lexicon adaptation for lvcsr: Speaker idiosyncracies, non-native speakers, and pronunciation choice, Proc. of PMLA Workshop, pp.83-88, 2002.

J. A. Wasser, English to phoneme translation, final version, 1985.

M. Weintraub, E. Fosler, C. Galles, Y. Kao, S. Khudanpur et al., Ws96 project report:automatic learning of word pronunciation from data, JHU Workshop Pronunciation Group, 1996.

M. Wester, Pronunciation modeling for asr-knowledge-based and data-driven methods, Computer Speech and Language, pp.69-85, 2003.

G. Williams and S. Renals, Confidence measures for evaluating pronunciation models, 1998.

M. Wolff, M. Eichner, and R. Hoffmann, Automatic learning and optimization of pronunciation dictionaries, ISCA Tutorial and Research Workshop (ITRW) on Adaptation Methods for Speech Recognition, 2001.

M. Wolff, M. Eichner, and R. Hoffmann, Measuring the quality of pronunciation dictionaries, Proc. of PMLA, pp.117-122, 2002.

Q. Yang, J. Martens, P. Ghesquiere, and D. Van-compernolle, Pronunciation variation modeling for asr: large improvements are possible but small ones are likely to achieve, Proc. of PMLA, pp.123-128, 2002.

S. Young, A review of large-vocabulary continuous-speech. Speech Processing Magazine, IEEE, vol.13, issue.5, p.45, 1996.

F. Yvon, Grapheme-to-phoneme conversion using multiple unbounded overlapping chunks, Proc. of NeMLaP, pp.218-228, 1996.

F. Yvon, P. Boula-de-mareüil, C. Alessandro, V. Aubergé, M. Bagein et al., Objective evaluation of grapheme to phoneme conversion for text-to-speech synthesis in French, Computer Speech & Language, vol.12, issue.4, pp.393-410, 1998.
DOI : 10.1006/csla.1998.0104

P. Zhang, J. Shao, J. Han, Z. Liu, and Y. Yan, Keyword spotting based on phoneme confusion matrix, Proc. of ISCSLP, pp.408-419, 2006.

H. Zou and T. Hastie, Regularization and variable selection via the elastic net, Journal of the Royal Statistical Society: Series B (Statistical Methodology), vol.5, issue.2, pp.301-320, 2005.
DOI : 10.1073/pnas.201162998