A. Esposito and G. Aversano, Text independent methods for speech segmentation, " in Lecture Notes in Computer Science, pp.261-290, 2005.

S. Dusan and L. Rabiner, On the relation between maximum spectral transition positions and phone boundaries, pp.645-648, 2006.

D. T. Toledando, L. A. Gómez, and L. V. Grande, Automatic phonetic segmentation, IEEE Transactions on Speech and Audio Processing, vol.11, issue.6, pp.617-625, 2003.
DOI : 10.1109/TSA.2003.813579

O. J. Räsänen, U. K. Laine, and T. Altosaar, Blind Segmentation of Speech Using Non-Linear Filtering Methods, Speech Technologies (I. Ipsic InTech, 2011.
DOI : 10.5772/16433

P. Delacourt and C. J. Wellekens, DISTBIC: A speaker-based segmentation for audio data indexing, Speech Communication, vol.32, issue.1-2, pp.111-126, 2000.
DOI : 10.1016/S0167-6393(00)00027-3

M. Sharma and R. J. Mammone, "Blind" speech segmentation: automatic segmentation of speech without linguistic knowledge, Proceeding of Fourth International Conference on Spoken Language Processing. ICSLP '96, pp.1237-1240, 1996.
DOI : 10.1109/ICSLP.1996.607832

M. Artimy, W. Robertson, and W. Phillips, Automatic detection of acoustic sub-word boundaries for single digit recognition, Engineering Solutions for the Next Millennium. 1999 IEEE Canadian Conference on Electrical and Computer Engineering (Cat. No.99TH8411), pp.751-754, 1999.
DOI : 10.1109/CCECE.1999.808034

C. Mitchell, M. Harper, and L. Jamieson, Using explicit segmentation to improve HMM phone recognition, 1995 International Conference on Acoustics, Speech, and Signal Processing, pp.229-232, 1995.
DOI : 10.1109/ICASSP.1995.479406

S. R. Quackenbush, T. P. Barnwell, and M. A. Clements, Objective Measures of Speech Quality, 1988.

J. S. Garofolo, L. F. Lamel, W. M. Fisher, J. G. Fiscus, D. S. Pallett et al., DARPA TIMIT acoustic phonetic continuous speech corpus CDROM VOICEBOX: Speech processing toolbox for MATLAB, 1993.

G. Almpanidis and C. Kotropoulos, Phonemic segmentation using the generalised Gamma distribution and small sample Bayesian information criterion, Speech Communication, vol.50, issue.1, pp.38-55, 2008.
DOI : 10.1016/j.specom.2007.06.005

URL : https://hal.archives-ouvertes.fr/hal-00499191

O. J. Räsänen, U. K. Laine, and T. Altosaar, An improved speech segmentation quality measure: the r-value, Proceedings of the 10th Annual Conference of the International Speech Communication Association, pp.1851-1854, 2009.

S. Cheng, H. Wang, and H. Fu, BIC-based speaker segmentation using divide-and-conquer strategies with application to speaker diarization, Audio, Speech, and Language Processing, pp.141-157, 2010.

S. Chen and P. S. Gopalakrishnan, Speaker, environment and channel change detection and clustering via the bayesian information criterion, DARPA Broadcast News Transcription and Understanding Workshop, pp.127-132, 1998.

M. D. Skowronski and J. G. Harris, Exploiting independent filter bandwidth of human factor cepstral coefficients in automatic speech recognition, The Journal of the Acoustical Society of America, vol.116, issue.3, 2004.
DOI : 10.1121/1.1777872

M. D. Skowronski and J. G. Harris, Human factor cepstral coefficients, The Journal of the Acoustical Society of America, vol.112, issue.5, 2002.
DOI : 10.1121/1.4779137

B. J. Moore and B. R. Glasberg, Suggested formula for calculating auditory-filter bandwidth and excitation patterns, Journal of the Acoustical Society of America, 1983.

I. Mporas, T. Ganchev, and N. Fakotakis, Speech segmentation using regression fusion of boundary predictions, Computer Speech & Language, vol.24, issue.2, pp.273-288, 2010.
DOI : 10.1016/j.csl.2009.04.004

URL : https://hal.archives-ouvertes.fr/hal-00593885

V. Khanagha, K. Daoudi, O. Pont, and H. Yahia, Improving text-independent phonetic segmentation based on the Microcanonical Multiscale Formalism, 2011 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP), 2011.
DOI : 10.1109/ICASSP.2011.5947350

URL : https://hal.archives-ouvertes.fr/inria-00557661

G. Aversano, A. Esposito, and M. Mariano, A new text-independent method for phoneme segmentation, Proceedings of the 44th IEEE 2001 Midwest Symposium on Circuits and Systems. MWSCAS 2001 (Cat. No.01CH37257), 2001.
DOI : 10.1109/MWSCAS.2001.986241

A. Kondoz, Digital Speech: Coding for Low Bit Rate Communication Systems, ch. Voice Activity Detection, pp.357-377, 2004.
DOI : 10.1002/0470870109

J. Sohn, S. Member, N. S. Kim, and W. Sung, A statistical model-based voice activity detection, IEEE Signal Processing Letters, vol.6, issue.1, pp.1-3, 1999.
DOI : 10.1109/97.736233

D. Ying, Y. Yonghong, D. Jianwu, and F. K. Soong, Voice Activity Detection Based on an Unsupervised Learning Framework, Audio, Speech, and Language Processing, 2011.
DOI : 10.1109/TASL.2011.2125953

M. Huijbregts, F. De, and J. , Robust speech/non-speech classification in heterogeneous multimedia content, Speech Communication, vol.53, issue.2, 2010.
DOI : 10.1016/j.specom.2010.08.008

J. Ramírez, M. Gorríz, and J. C. Segura, Robust Speech Recognition and Understanding, ch. Voice Activity Detection. Fundamentals and Speech Recognition System Robustness, 2007.

G. Almpanidis, M. Kotti, and C. Kotropoulos, Robust Detection of Phone Boundaries Using Model Selection Criteria With Few Observations, Audio, Speech, and Language Processing, pp.287-298, 2009.
DOI : 10.1109/TASL.2008.2009162

M. Kotti, E. Benetos, and C. Kotropoulos, Computationally Efficient and Robust BIC-Based Speaker Segmentation, Audio, Speech, and Language Processing, pp.920-933, 2008.
DOI : 10.1109/TASL.2008.925152

URL : http://spiral.imperial.ac.uk/bitstream/10044/1/11710/2/IEEE_TRANS_ASLP_2008_Margarita_Kotti.pdf