A. Abdel-rahman, Code-switching and Linguistic Accommodation in Arabic, Perspectives on Arabic Linguistics III: Papers from the Third Annual Symposium on Arabic Linguistics, p.231250, 1991.

M. Alghamdi, M. Elshafei, and H. Muhtaseb, Speech Units for Arabic Text-to-speech, Fourth Workshop on Computer and Information Sciences, pp.199-212, 2002.

M. Alghamdi, Z. Muza?ar, and H. Alhakami, Automatic restoration of Arabic diacritics : a simple, purely statical approach, The Arabian Journal for Science and Engineering, vol.35, issue.2, 2010.

O. Andersen, R. Kuhn, A. Lazaridès, P. Dalsgaard, J. Haas et al., Comparison of two tree-structured approaches for grapheme-to-phoneme conversion, Spoken Language Processing, pp.1700-1703, 1996.

T. Baccouche, Larabe, dune koin dialectale une langue de culture, pp.87-93, 2003.

E. Barnard, M. H. Davel, and G. B. Van-huyssteen, Speech technology for information access: a south african case study, AAAI Spring Symposium: Artificial Intelligence for Development, 2010.

L. Besacier, V. B. Le, E. Castelli, S. Sethserey, and L. Protin, , 2005.

L. Besacier, E. Barnard, A. Karpov, and T. Schultz, Automatic speech recognition for under-resourced languages: A survey, Speech Communication, vol.56, 2014.
DOI : 10.1016/j.specom.2013.07.008
URL : https://hal.archives-ouvertes.fr/hal-00953644

F. Biadsy, N. Habash, and J. Julia-hirschberg, Improving the Arabic Pronunciation Dictionary for Phone and Word Recognition with Linguistically-Based Pronunciation Rules, Annual Conference of the North American, p.397405, 2009.

;. M. Bisani and H. Ney, Joint-sequence models for grapheme-to-phoneme conversion, Speech Communication, vol.50, issue.5, pp.434-451, 2008.
DOI : 10.1016/j.specom.2008.01.002
URL : https://hal.archives-ouvertes.fr/hal-00499203

D. Blachona, E. Gauthiera, L. Besacier, G. Kouarata, M. Adda-deckerb et al., Parallel Speech Collection for Under-resourced Language Studies Using the Lig-Aikuma Mobile Device App, Procedia Computer Science, vol.81, 2016.
DOI : 10.1016/j.procs.2016.04.030

H. Cucu, A. Buzo, L. Besacier, and C. Burileanu, SMT-based ASR domain adaptation methods for under-resourced languages: Application to Romanian, Speech Communication, vol.56, 2014.
DOI : 10.1016/j.specom.2013.05.003
URL : https://hal.archives-ouvertes.fr/hal-00953643

Y. El-imam, Phonetization of Arabic: rules and algorithms, Computer Speech & Language, vol.18, issue.4, 2003.
DOI : 10.1016/S0885-2308(03)00035-4

M. Elmahdy, M. Hasegawa-johnson, and E. Mustafawi, Development of a tv broadcasts speech recognition system for qatari arabic, The 9th edition of the Language Resources and Evaluation Conference, 2014.

M. Elshafei, H. Al-muhtaseb, and . M. Alghamdi, Statistical methods for automatic diacritization of Arabic text, The Saudi 18th National Computer Conference, pp.301-306, 2006.

E. Gauthier, L. Besacier, S. Voisin, M. Melese, and U. P. Elingui, Collecting resources in sub-saharan african languages for automatic speech recognition: a case study of wolof, 2016.
URL : https://hal.archives-ouvertes.fr/hal-01350037

E. Gauthiera, L. Besacier, and S. Voisinb, Automatic Speech Recognition for African Languages with Vowel Length Contrast, 5th Workshop on Spoken Language Technology for Under-resourced Languages, 2016.

H. Gelas, S. Teferra, S. Besacier, L. Pellegrino, and F. , Analyse des performances de modles de langage sub-lexicale pour des langues peu-dotees morphologie riche, 2012.

M. Graja, M. Jaoua, and L. Belguith, Lexical Study of A Spoken Dialogue Corpus in Tunisian Dialect, ACIT2010: the International Arab Conference on Information Technology, 1416.

M. Graja, M. Jaoua, and L. Belguith, Statistical Framework with Knowledge Base Integration for Robust Speech Understanding of the Tunisian Dialect, IEEE/ACM Transactions on Audio, Speech, and Language Processing, vol.23, issue.12, pp.2311-2321, 2015.
DOI : 10.1109/TASLP.2015.2464687

N. Habash, D. Diab, and O. Rambow, Conventional Orthography for dialectal Arabic, Proceedings of the Eighth International Conference on Language Resources and Evaluation LREC'2012, 2012.

N. Habash, Introduction to Arabic Natural Language Processing, Synthesis Lectures on Human Language Technologies, 2010.

N. Habash, On Arabic and its Dialects, Multilingual Magazine, p.17, 2006.

J. Häkkinen, J. Suontausta, S. Riis, and K. Jensen, Assessing text-to-phoneme mapping strategies in speaker independent isolated word recognition, Speech Communication, vol.41, issue.2-3, pp.455-467, 2003.
DOI : 10.1016/S0167-6393(03)00015-3

S. Harrat, K. Meftouh, M. Abbas, and K. Sma¨?lisma¨?li, Grapheme To Phoneme Conversion-An Arabic Dialect Case, Spoken Language Technologies for Under-resourced Languages (SLTU'2014), 2014.
URL : https://hal.archives-ouvertes.fr/hal-01067022

I. Illina, D. Fohr, and D. Jouvet, Grapheme-to-Phoneme Conversion using Conditional Random Fields, 2011.
URL : https://hal.archives-ouvertes.fr/inria-00614981

J. Jensen and S. Riis, Self-organizing letter code-book for text-to-phoneme neural network model, Spoken Language Processing, pp.318-321, 2000.

S. Juan and L. Besacier, Fast bootstrapping of grapheme to phoneme system for under-resourced languages-application to the iban language, p.2013, 2013.
URL : https://hal.archives-ouvertes.fr/hal-00953784

S. Kheang, K. Katsurada, Y. Iribe, and T. Nitta, Solving the Phoneme Conflict in Grapheme-to-Phoneme Conversion Using a Two-Stage Neural Network-Based Approach, IEICE Transactions on Information and Systems, vol.97, issue.4, p.97, 2014.
DOI : 10.1587/transinf.E97.D.901

S. Lawson and S. Itesh, Accommodation communicative en Tunisie: une tude empirique, pp.101-114, 1997.

R. Lileikyta, A. Gorinaa, L. Lamela, J. Gauvaina, and T. Fraga-silva, Lithuanian Broadcast Speech Transcription using Semi-supervised Acoustic Model Training, 5th Workshop on Spoken Language Technology for Under-resourced Languages, 2016.

L. Loots and T. Niesler, Automatic conversion between pronunciations of di?erent English accents, Speech Communication, vol.53, p.7584, 2011.

Y. Marchand and R. Damper, A Multistrategy Approach to Improving Pronunciation by Analogy, Computational Linguistics, vol.1, issue.3, pp.195-219, 2000.
DOI : 10.1080/09296179408590015

A. Masmoudi, M. Khmekhem, Y. Estève, L. Belguith, and N. Habash, A Corpus and Phonetic Dictionary for Tunisian Arabic Speech Recognition, Proceedings of the Ninth International Conference on Language Resources and Evaluation (LREC-2014), pp.306-310, 2014.
URL : https://hal.archives-ouvertes.fr/hal-01433247

A. Masmoudi, N. Habash, M. Khmekhem, Y. Estève, and L. Belguith, Arabic Transliteration of Romanized Tunisian Dialect Text: A Preliminary Investigation, Computational Linguistics and Intelligent Text Processing -16th International Conference, pp.608-619, 2015.
DOI : 10.1007/978-3-319-18111-0_46

S. Mejri, S. Said, and I. Sfar, Pluringuisme et diglossie en Tunisie, Synergies Tunisie, vol.1, pp.53-74, 2009.

A. Nimaan, P. Nocera, and J. M. Torres-moreno, Boites a outils tal pour les langues peu informatisees: Le cas du somali, 2006.

. V. Pagel, K. W. Lenzo, and A. Black, Letter-to-sound rules for accented lexicon compression,Spoken Language Processing, 1998.

T. Pellegrini, Transcription automatique de langues peu dotees, 2008.
URL : https://hal.archives-ouvertes.fr/tel-00619657

D. Povey, A. Ghoshal, G. Boulianne, L. Burget, O. Glembek et al., The Kaldi Speech Recognition Toolkit, IEEE 2011 Workshop on Automatic Speech Recognition and Understanding, 2011.

R. Rasipuram and M. Doss, Acoustic data-driven grapheme-to-phoneme conversion using KL-HMM, Acoustics, Speech and Signal Processing, pp.4841-4844, 2012.
DOI : 10.1109/icassp.2012.6289003
URL : http://publications.idiap.ch/downloads/reports/2012/Rasipuram_Idiap-RR-38-2011.pdf

H. Saadane and N. Habash, A Conventional Orthography for Algerian Arabic, Proceedings of the Second Workshop on Arabic Natural Language Processing, pp.69-79, 2015.
DOI : 10.18653/v1/W15-3208

S. Samson, L. Besacier, B. Lecouteux, and M. Dyab, Using Resources from a Closely-related Language to Develop ASR for a Very Under-resourced Language: A Case Study for Iban, 2015.
URL : https://hal.archives-ouvertes.fr/hal-01170493

T. Schlippe, E. Djomgang, N. Vu, S. Ochs, and T. Schultz, hause large vocabulary continuous speech recognition,The third International Workshop on Spoken Languages Technologies for Under-resourced Languages, Cape Town, 2012.

T. Sejnowski and C. Rosenberg, Parallel networks that learn to pronounce English text, pp.145-168, 1987.

. K. Seng, Y. Iribe, and T. Nitta, Letter-to-Phoneme Conversion Based on Two- Stage Neural Network Focusing on Letter and Phoneme Contexts, 12th Annual Conference of the International Speech Communication Association, ISCA, pp.1885-1888, 2011.

P. Taylor, Hidden Markov models for grapheme to phoneme conversion, INTER- SPEECH' 2005 -Eurospeech, 9th European Conference on Speech Communication and Technology, ISCA, pp.1973-1976, 2005.

H. Tebbi, Transcription orthographique phonétique en vue de la synthèse de la parole partir du texte de lArabe, 2007.

D. Vergyri, A. Mandal, W. Wang, A. Stolcke, J. Zheng et al., , 2008.

N. T. Vu, F. Kraus, and T. Schultz, Rapid building of an asr system for underresourced languages based on multilingual unsupervised training, 2011.

X. Wang and K. Sim, Integrating Conditional Random Fields and Joint Multi-gram Model with Syllabic features for Grapheme-to-Phone Conversion, 2013.

I. Zribi, R. Boujelbane, A. Masmoudi, M. Ellouze, L. Belguith et al., , 2014.

A. Conventional-orthography-for-tunisian and . Arabic, Proceedings of the Ninth International Conference on Language Resources and Evaluation (LREC-2014), pp.2355-2361