Discriminative vector for spoken language recognition

ICASSP, IEEE International Conference on Acoustics, Speech and Signal Processing - Proceedings

Volumn 4, Issue , 2007, Pages

  Ma, Bin ^a   Tong, Rong ^a   Li, Haizhou ^a  

^a INSTITUTE FOR INFOCOMM RESEARCH   (Singapore)

Author keywords

Discriminative vector; Ensemble classifiers; Output codes; Spoken language recognition

Indexed keywords

BINARY CODES; CLASSIFICATION (OF INFORMATION); ERROR DETECTION; FEATURE EXTRACTION; MATHEMATICAL MODELS; VECTOR QUANTIZATION;

DISCRIMINATIVE VECTORS; ENSEMBLE CLASSIFIERS; OUTPUT CODES; SPOKEN LANGUAGE RECOGNITION;

NATURAL LANGUAGE PROCESSING SYSTEMS;

EID: 34547538784     PISSN: 15206149     EISSN: None     Source Type: Conference Proceeding    
DOI: 10.1109/ICASSP.2007.367241     Document Type: Conference Paper

References (12)

1. M. A. Zissman, "Comparison of four approaches to automatic language identification of telephone speech," IEEE Trans. Speech and Audio Processing, Vol. 4, No. 1, pp. 31-44, 1996.
2. E. Singer, P. A. Torres-Carrasquillo, T. P. Gleason, W. M. Campbell and D. A. Reynolds, "Acoustic, phonetic and discriminative approaches to automatic language recognition," Proc Eurospeech, 2003.
3. R. Tong, B. Ma, D. Zhu, H. Li and E. S. Chng, "Integrating acoustic, prosodic and phonotactic features for spoken language identification," Proc ICASSP, 2006.
4. H. Li, B. Ma and C.-H. Lee, "A vector space modeling approach to spoken language identification," IEEE Trans. Audio, Speech and Language Processing, Vol. 15, No. 1, 2007.
5. J. R. Bellegarda, "Exploiting latent semantic information in statistical language modeling," Proc. IEEE, Vol. 88, No. 8, pp. 1279-1296, 2000.
6. M. Kobayashi and M. Aono, "Vector space models for search and cluster mining," Survey of Text Mining, M. W. Berry (ed), Springer, 2003
7. H. Li, B. Ma, and R. Tong, "Vector-Based Spoken Language Recognition using Output Coding," Proc Interspeech, 2006.
8. T. G. Dietterich and G. Bakiri, "Solving multiclass learning problems via error-correcting output codes," Journal of Artificial Intelligence Research, vol. 2, pp.263-286. 1995.
9. K. Crammer, and Y. Singer, "Improved output coding for classification using continuous relaxation," Proc NIPS, 2000.
10. V. Vapnik, The nature of statistical learning theory. Springer-Verlag, 1995.
11. R. O. Duda, P. E. Hart and D. G. Stork, Pattern Classification, John Wiley & Sons, Inc., 2001.
12. T. Schultz, Q. Jin, K. Laskowski, A. Tribble, and A. Waibel, "Improvements in Non-verbal Cue Identification Using Multilingual Phone Strings," Proc. the Workshop on Spcech-to-Speech Translation: Algorithms and Systems at ACL 2002.