An enhanced centered binary tree of SVMs algorithm for phoneme recognition

EUROCON 2007 - The International Conference on Computer as a Tool

Volumn , Issue , 2007, Pages 209-213

  Gauci, Oliver ^a   Debono, Carl J ^a   Micallef, Paul ^a  

^a UNIVERSITY OF MALTA   (Malta)

Author keywords

Multiclass classification; Speech recognition; Support vector machine

Indexed keywords

ALGORITHMS; BINARY TREES; BOOLEAN FUNCTIONS; CLASSIFICATION (OF INFORMATION); CLASSIFIERS; DATA STRUCTURES; FILE ORGANIZATION; LEARNING SYSTEMS; SUPPORT VECTOR MACHINES; VECTORS;

(P ,P ,T) MEASUREMENTS; (SPM) CLASSES; APPLIED (CO); BINARY CLASSIFIERS; COMPUTATION (CPU) TIMES; DATA SETS; INTERNATIONAL CONFERENCES; LEARNING MACHINES; MULTICLASS RECOGNITION; PHONEME RECOGNITION; POSTERIOR PROBABILITIES; PRACTICAL USE; SUPPORT VECTOR MACHINES ((SVM)); TIMIT DATABASE;

TREES (MATHEMATICS);

EID: 46149101527     PISSN: None     EISSN: None     Source Type: Conference Proceeding    
DOI: 10.1109/EURCON.2007.4400272     Document Type: Conference Paper

References (23)

1. S. Furui, "Recent advances in spontaneous speech recognition," The Journal of the acoustical society of America, vol. 103, Issue 5, p. 2817, May 1998.
2. S. Renals, R, Rohwer, "Learning phoneme recognition using neural networks," ICASSP-89, vol. 1, pp. 413-416, 1989.
3. Petr Schwarz, Pavel Matijka, Jan Cemocky, "Hierarchical structure of neural networks of an neural networks for phoneme recognition," ICASSP-06, vol. 1, pp. 325-328, 2006.
4. X. D. Huang, "Phoneme Classification Using Semicontinuous Hidden Markov Models," IEEE Trans. On Signal Processing, vol. 40, No. 5, pp. 1062 - 1067, May 1992.
5. R. N. V. Sitaram, T. V. Sreenivas, "Phoneme recognition in continuous speech using large inhomogeneous Hidden Markov Models," ICASSP-94, vol. 1, pp 41-44, 1994.
6. J. Zeng, Z. Q. Liu, "Type-2 fuzzy Hidden Markov Models to phoneme recognition," ICPR-04, vol. 1, pp. 192 - 195, 2004.
7. N. Cristianini and J. S. Taylor, "An introduction to Support Vector Machines and other Kernel-Based learning methods," Cambridge University press, 2000.
8. A. Ganapathiraju, J. E. Hamaker, J. Picone, "Applications of Support Vector Machines to Speech Recognition," IEEE Trans. On Signal Processing, vol. 52, No. 8, August 2004.
9. D. deterding, M. Niranja, A. J. Robinson. Vowel recognition (Deterding Data), Berkley, CA. Available: http://ftp.ics.uci.edu/pub/machine-leaming- databases/undocument-ed/connectionist-bench/vowel.
10. A. Ech-Cherif, M. Kohili, A. Benyettou, M. Benyettou, "Lagrangian Support Vector Machines for phoneme classification," ICONIP 2002, vol. 5, pp. 2507 - 2511, 2002.
11. W. M. Fisher, G. R. Doddington and K. M. Goudie-Marshall, "The DARPA speech recognition research database: Specifications and Status," Proceedings of DARPA workshop on speech recognition, pp. 93 - 99, February 1986.
12. N. Smith, M. Gales, "Speech Recognition using SVMs", Advances in Neural Information processing system, 2002.
13. O. Scharenborg, V. Wan, R. K. Moore, "Capturing fine-phonetic variation in speech through automatic classification of articulatory features," SRIV 2006, ISCA archive, 2006.
14. J. C. Platt, N. Cristianini, and J. W. Taylor. "Large Margin DAGs for MultiClass Classification," MIT press, pp. 547-553, 2000.
15. B. Fei and J. Liu, "Binary Tree of SVM: A new Fast MultiClass Training and Classification Algorithm," IEEE Trans. On neural Networks, vol 17. No. 3, May 2006.
16. N. Cristianinini and J. S. Taylor, An introduction to Support Vector Machines and other Kernel-Based Learning methods, Cambridge University press, 2000.
17. C. W. Hsu and C. J. Lin, "A comparison of Methods for multiclass support vector machines," IEEE Trans. On neural networks, vol. 13, No. 2, March 2002.
18. J. H. Friedman, "Another approach to polychotomus classification," Technical report, Stanford department of statistics, 1996.
19. J. C. Platt, N. Cristianini and J. S. Taylor, "Large Margin DAGs for Multiclass Classification," MIT press, pp 547-553, 2000.
20. T. G. Dietterich and G. Bakiri, "Solving multiclass learning problems via error-correcting output codes," Journal of Artificial intelligence research 2, pp263-286, 1995.
21. J. C. Platt, A. J. Smola, P. Barlette, B. Scholkopf and D. Shuurmans, "Probabilistic outputs for support vector machines and comparisons to regularize likelihood methods," in Advances in Large Margin Classifiers, MIT Press, 1999.
22. J. C Platt, "Sequential Minimal Optimization: A fast algorithm for training support vector machines," Microsoft Research Technical Report MSR-TR-98-14, April 1998.
23. G. Wahab, "Support Vector Machine, reproducing kernel Hilbert spaces and the randomized GACV," University of Wistconsis, Technical report no. 984rr., July 1998.