B. Bigi, A Phonetization Approach for the Forced-Alignment Task in SPPAS, Proc. LTC, 2013.
DOI : 10.1007/978-3-319-43808-5_30
URL : https://hal.archives-ouvertes.fr/hal-01455223

S. Brognaux and T. Drugman, HMM-Based Speech Segmentation: Improvements of Fully Automatic Approaches, IEEE/ACM Transactions on Audio, Speech, and Language Processing, vol.24, issue.1, pp.5-15, 2016.
DOI : 10.1109/TASLP.2015.2456421

C. Cerisara, O. Mella, and D. Fohr, Jtrans, an open-source software for semi-automatic text-to-speech alignment, Proc. INTERSPEECH, 2009.
URL : https://hal.archives-ouvertes.fr/inria-00431398

F. Chollet, Keras. https, 2015.

F. De-jong, R. Ordelman, and M. Huijbregts, Automated Speech and Audio Analysis for Semantic Access to Multimedia, Proc. International Conference on Semantic and Digital Media Technologies, 2006.
DOI : 10.1007/11930334_18

D. Fohr, O. Mella, and D. Jouvet, De l'importance de l'homogénéisation des conventions de transcription pour l'alignement automatique de corpus oraux de parole spontanée, 8` emes Journées Internationales de Linguistique de Corpus (JLC2015), 2015.

A. Haubold and J. R. Kender, Alignment of Speech to Highly Imperfect Text Transcriptions, Multimedia and Expo, 2007 IEEE International Conference on, 2007.
DOI : 10.1109/ICME.2007.4284627

T. J. Hazen, Automatic alignment and error correction of human generated transcripts for long speech recordings, Proc. Interspeech, pp.1606-1609, 2006.

J. Hosom, Speaker-independent phoneme alignment using transition-dependent states, Speech Communication, vol.51, issue.4, pp.352-368, 2009.
DOI : 10.1016/j.specom.2008.11.003

J. Keshet, S. Shalev-shwartz, Y. Singer, and D. Chazan, Phoneme alignment based on discriminative learning, Proc. Interspeech, pp.2961-2964, 2005.

P. Lanchantin, M. Gales, P. Karanasou, X. Liu, Y. Qian et al., The development of the cambridge university alignment systems for the multi-genre broadcast challenge, 2015 IEEE Workshop on Automatic Speech Recognition and Understanding (ASRU), 2015.
DOI : 10.1109/ASRU.2015.7404857

A. Martin, G. Doddington, T. Kamm, M. Ordowski, and M. Przybocki, The det curve in assessment of detection task performance, 1997.

B. Milde, Unsupervised acquisition of acoustic models for speech-to-text alignment, 2014.

P. J. Moreno, C. Joerg, J. Van-thong, and O. Glickman, A recursive algorithm for the forced alignment of very long audio segments, Proc. ICSLP, 1998.

S. Paulo and L. Oliveira, Automatic Phonetic Alignment and Its Confidence Measures, Advances in Natural Language Processing, pp.36-44, 2004.
DOI : 10.1109/TASSP.1978.1163055

M. S. Seigel, Confidence Estimation for Automatic Speech Recognition Hypotheses, 2013.

A. Stan, Y. Mamiya, J. Yamagishi, P. Bell, O. Watts et al., ALISA: An automatic lightly supervised speech segmentation and alignment tool, Computer Speech & Language, vol.35, pp.116-133, 2016.
DOI : 10.1016/j.csl.2015.06.006

A. Stolcke, N. Ryant, V. Mitra, J. Yuan, W. Wang et al., Highly accurate phonetic segmentation using boundary correction models and system fusion, 2014 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP), 2014.
DOI : 10.1109/ICASSP.2014.6854665

D. Willett, A. Worm, C. Neukirchen, and G. , Confidence measures for hmm-based speech recognition, ICSLP, pp.3241-3244, 1998.

D. Yu, J. Li, and L. Deng, Calibration of Confidence Measures in Speech Recognition, IEEE Transactions on Audio, Speech, and Language Processing, vol.19, issue.8, pp.2461-2473, 2011.
DOI : 10.1109/TASL.2011.2141988

J. Yuan, N. Ryant, M. Liberman, A. Stolcke, V. Mitra et al., Automatic phonetic segmentation using boundary models, Proc. Interspeech ISCA -International Speech Communication Association, 2013.

Y. Zhao, L. Wang, M. Chu, F. K. Soong, and Z. Cao, Refining phoneme segmentations using speakeradaptive context dependent boundary models, Proc. Interspeech, 2005.