A new hybrid GMM/SVM for speaker verification

Proceedings - International Conference on Pattern Recognition

Volumn 4, Issue , 2006, Pages 314-317

  Liu, Minghui ^a   Xie, Yanlu ^a   Yao, Zhiqiang ^a   Dai, Beiqian ^a  

^a UNIVERSITY OF SCIENCE AND TECHNOLOGY OF CHINA   (China)

Author keywords

[No Author keywords available]

Indexed keywords

FEATURE VECTORS; GAUSSIAN MIXTURE MODEL (GMM); SPEAKER VERIFICATION;

COMPUTATIONAL METHODS; DATABASE SYSTEMS; FEATURE EXTRACTION; SPEECH RECOGNITION; VECTORS; VERIFICATION;

SUPPORT VECTOR MACHINES;

EID: 34147190252     PISSN: 10514651     EISSN: None     Source Type: Conference Proceeding    
DOI: 10.1109/ICPR.2006.118     Document Type: Conference Paper

References (11)

1. Douglas A. Reynolds, "Speaker Verification using Adapted Gaussian Mixture Models," Digital Signal Processing, vol. 10, pp.19-41, 2000.
2. C. J. C. Burges, "A tutorial on support vector machines for pattern recognition," Data Mining and Knowledge Discovery, vol. 2, no. 2, pp. 1-47, 1998.
3. V. Wan and W. M. Campbell, "Support vector machines for speaker verification and identification," in Proc. Neural Networks for Signal Processing X, 2000, pp. 775-784.
4. V. Wan and S. Renais, "SVMSVM: Support Vector Machine speaker verification methodology," in Proc. IEEE ICASSP, 2003.
5. S. Bengio, "Learning the decision function for speaker verification," in Proc. IEEE ICASSP, 2001.
6. M.H. Liu, B.Q. Dai, Y.L. Xie, Z.Q. Yao, "Improved GMM-UBM/SVM for speaker verification," in Proc. IEEE ICASSP, 2006.
7. S. Fine, J. Navratil and R. A. Gopinath, "Enhancing GMM scores using SVM "hints"," in Proceedings of Eurospeech, 2001, pp. 1757-1761.
8. V. N. Vapnik, The Nature of Statistical Learning Theory, Springer, 1995.
9. Y. Zhang, C.J.S. deSilva, "An Isolated Word Recognizer Using the EM Algorithm for Vector Quantization," in IREECON, 1991, pp. 289-292.
10. [Online] The NIST Speaker Recognition Evaluation Home: http://www.nist.gov/speech/tests/spk/index.htm.
11. Chih-Wei Hsu, Chih-Chung Chang, and Chih-Jen Lin, "A Practical Guide to Support Vector Classification", available at http://www.csie.ntu. edu.tw/~cjlin/libsvm.