R. Bahl, R. Bakis, P. De-souza, and R. Mercer, Obtaining candidate words by polling in a large vocabulary speech recognition system, Int. Conference on Acoustics, Speech and Signal Processing, pp.489-492, 1988.

R. Balchandran, L. Rachevsky, B. Ramabhadran, and M. Novak, Techniques for topic detection based processing in spoken dialog systems, pp.82-85, 2010.

J. R. Bellegarda, Exploiting latent semantic information in statistical language modeling, Proceedings of the IEEE, vol.88, pp.1279-1296, 2000.

D. M. Blei, A. Y. Ng, and M. I. Jordan, Latent dirichlet allocation. the J. of machine Learning res, vol.3, pp.993-1022, 2003.

X. Bost, M. El-b`-eze, and R. De-mori, Multiple topic identification in telephone conversations, pp.3756-3760, 2013.
URL : https://hal.archives-ouvertes.fr/hal-01313070

N. Camelin, R. De-mori, F. Béchet, and G. Damnati, Error correction of proportions in spoken opinion surveys, pp.2715-2718, 2009.
URL : https://hal.archives-ouvertes.fr/hal-01314530

A. C. De-carvalho and A. A. Freitas, A tutorial on multi-label classification techniques, Found. of Computational Intelligence, vol.5, pp.177-195, 2009.

H. Chen, Learning semantic structures from in-domain documents, 2010.

Y. N. Chen, Y. Huang, S. Y. Kong, and L. S. Lee, Automatic key term extraction from spoken course lectures using branching entropy and prosodic/semantic features, Spok. Lang. Technology Workshop (SLT), pp.265-270, 2010.

J. T. Chien and M. S. Wu, Adaptive bayesian latent semantic analysis, Transactions on Audio, Speech, and Lang. Processing, vol.16, pp.198-207, 2008.

W. W. Cohen and Y. Singer, Context-sensitive learning methods for text categorization, ACM Transactions on Inf. Syst. (TOIS), vol.17, pp.141-173, 1999.

J. Eisenstein and R. Barzilay, Bayesian unsupervised topic segmentation, Proceedings of the 2008 Conference on Emp. Methods in Nat. Lang. Processing, pp.334-343, 2008.

T. Hazen, Mce training techniques for topic identification of spoken audio documents, Transactions on Audio, Speech, and Lang. Processing, vol.19, pp.2451-2460, 2011.

T. J. Hazen, Topic identification, pp.319-356, 2011.

T. Joachims, Text categorization with support vector machines: Learning with many relevant features, 1998.

T. Joachims, Making large scale SVM learning practical, 1999.

T. Joachims, Learning to classify text using support vector machines: Methods, theory and algorithms, 2002.

T. Joachims, Optimizing search engines using clickthrough data, Proceedings of the eighth ACM SIGKDD international conference on Knowledge discovery and data mining, Association for Computational Linguistics, pp.133-142, 2002.

D. D. Lewis and W. A. Gale, A sequential algorithm for training text classifiers, Proceedings of the 17th annual Int. ACM SIGIR conference on Res. and development in inf. retr, pp.3-12, 1994.

Y. H. Li and A. K. Jain, Classification of text documents, The Computer J, vol.41, pp.537-546, 1998.

G. Linarès, P. Nocéra, D. Massonie, and D. Matrouf, The lia speech recognition system: from 10xrt to 1xrt, Text, Speech and Dialogue, pp.302-308, 2007.

B. Maza, M. El-b`-eze, G. Linarès, and R. De-mori, On the use of linguistic features in an automatic system for speech analytics of telephone conversations, pp.2049-2052, 2011.
URL : https://hal.archives-ouvertes.fr/hal-01318522

K. Min and Y. Ma, Joint topic-document modeling via low-dimensional sparse models, Int. Conference on Acoustics, Speech and Signal Processing (ICASSP), IEEE, pp.8590-8594, 2013.

E. Mittendorf and P. Schäuble, Document and passage retrieval based on hidden markov models, Proceedings of the 17th Annual Int. ACM SIGIR Conference on Res. and Development in Inf. Retr, pp.318-327, 1994.

M. Morchid, M. Bouallegue, R. Dufour, G. Linarès, D. Matrouf et al., An i-vector based approach to compact multi-granularity topic spaces representation of textual documents, Proceedings of the 2014 Conference on Emp. Methods in Nat. Lang. Processing, pp.443-454, 2014.
URL : https://hal.archives-ouvertes.fr/hal-01318651

M. Morchid, R. Dufour, P. M. Bousquet, M. Bouallegue, G. Linarès et al., Improving dialogue classification using a topic space representation and a gaussian classifier based on the decision rule, Int. Conference on Acoustics, Speech and Signal Processing, pp.126-130, 2014.
URL : https://hal.archives-ouvertes.fr/hal-01318674

J. Niekrasz and J. D. Moore, Unbiased discourse segmentation evaluation, Spok. Lang. Technology Workshop (SLT), IEEE, pp.43-48, 2010.

M. Purver, Topic segmentation, Spok. Lang. Underst.: Syst. for Extracting Semantic Inf. from Speech, pp.291-317, 2011.

G. Tsoumakas and I. Katakis, Multi-label classification: An overview, Int. J. of Data Warehous. and Min. (IJDWM), vol.3, pp.1-13, 2007.

G. Tur and R. De-mori, Spoken language understanding: Systems for extracting semantic information from speech, 2011.

G. Tur and D. Hakkani-tür, Human/human conversation understanding, Spok. Lang. Underst.: Syst. for Extracting Semantic Inf. from Speech, pp.225-255, 2011.

B. C. Wallace, T. A. Trikalinos, M. B. Laws, I. B. Wilson, and E. Charniak, A generative joint, additive, sequential model of topics and speech acts in patient-doctor communication, Proceedings of the 2013 Conference on Emp. Methods in Nat. Lang. Processing, Association for Computational Linguistics, pp.1765-1775, 2013.

J. Wintrode, Using latent topic features to improve binary classification of spoken documents, Int. Conference on Acoustics, Speech and Signal Processing, pp.5544-5547, 2011.

J. Wintrode and S. Kulp, Techniques for rapid and robust topic identification of conversational telephone speech, pp.1471-1474, 2009.

Y. Yang and J. O. Pedersen, A comparative study on feature selection in text categorization, pp.412-420, 1997.

, He is actually an Associate Editor of the ieee Transactions on Audio, Speech and Language. His major contributions have been in the area of Automatic Speech Recognition and Understanding, Signal Processing