Automatic segmentation and identification of mixed-language speech using delta-BIC and LSA-based GMMs

IEEE Transactions on Audio, Speech and Language Processing

Volumn 14, Issue 1, 2006, Pages 266-275

  Wu, Chung Hsien ^a,b,c,d   Chiu, Yu Hsien ^b   Shia, Chi Jiun ^b   Lin, Chun Yu ^b  

^a IEEE   (Taiwan)

^b NATIONAL CHENG KUNG UNIVERSITY   (Taiwan)

^c International Speech Communication Association   (Taiwan)

^d International Speech Communication Association ^*  (Taiwan)

Author keywords

Gaussian mixture model; Language identification; Latent semantic analysis; Mixed language speech; Single language speech

Indexed keywords

GAUSSIAN MIXTURE MODEL; LANGUAGE IDENTIFICATION; LATENT SEMANTIC ANALYSIS; MIXED-LANGUAGE SPEECH; SINGLE-LANGUAGE SPEECH;

ACOUSTIC WAVES; DYNAMIC PROGRAMMING; MATHEMATICAL MODELS; MAXIMUM LIKELIHOOD ESTIMATION; SEMANTICS; VECTORS;

SPEECH RECOGNITION;

EID: 33745000055     PISSN: 15587916     EISSN: None     Source Type: Journal    
DOI: 10.1109/TSA.2005.852992     Document Type: Conference Paper

References (30)

1. A. Waibel, P. Geutner, and L. M. Tomokiyo et al., "Multilinguality in speech and spoken language systems," Proc. IEEE, vol. 88, no. 8, pp. 1297-1313, 2000.
2. Y. K. Muthusamy, "A segmental approach to automatic language identification," Ph.D. dissertation, Oregon Grad. Inst. Sci. Technol., Beaverton, 1993.
3. Y. K. Muthusamy, E. Barnard, and R. A. Cole, "Reviewing automatic language identification," IEEE Signal Processing Mag., vol. 11, no. 4, pp. 33-41, 1994.
4. M. A. Zissman, "Comparison of four approaches to automatic language identification of telephone speech," IEEE Trans. Speech Audio Processing, vol. 4, no. 1, pp. 31-44, 1996.
5. A. P. Martin and M. A. Przybocki, "NIST 2003 language recognition evaluation," in Proc. EUROSPEECH'03, 2003, pp. 1341-1344.
6. P. A. Torres-Carrasquillo et al., "Approaches to language identification using Gaussian mixture models and shift delta ceptral features," in Proc. ICSLP'02, 2002, pp. 89-92.
7. K.-H. You and H.-C. Wang, "Joint estimation of feature transformation parameters and Gaussian mixture model for speaker identification," Speech Commun., vol. 28, pp. 227-241, 1999.
8. J. Köhler, "Multilingual phone models for vocabulary- independent speech recognition tasks," Speech Commun., vol. 35, pp. 21-30, 2001.
9. W.-H. Tsai and W.-W. Chang, "Discriminative training of Gaussian mixture bi-gram models with application to Chinese dialect identification," Speech Commun., vol. 36, pp. 317-326, 2002.
10. R. Hariharan, I. Kiss, and O. Viikki, "Noise robust speech parameterization using multiresolution feature extraction," IEEE Trans. Speech Audio Processing, vol. 9, no. 8, pp. 856-865, 2001.
11. L. K. Saul and M. G. Rahim, "Maximum likelihood and minimum classification error factor analysis for automatic speech recognition," IEEE Trans. Speech Audio Processing, vol. 8, no. 2, pp. 115-125, 2000.
12. F. Pellegrino and R. Andre-Obrecht, "Automatic language identification: an alternative approach to phonetic modeling," Signal Process., vol. 80, pp. 1231-1244, 2000.
13. J. Navratil, "Spoken language recognition - a step toward multilinguality in speech processing," IEEE Trans. Speech Audio Processing, vol. 9, no. 6, pp. 678-685, 2001.
14. M. Cettolo and A. Federico, "Model selection criteria for acoustic segmentation," in Proc. ISCA ITRW ASR '00 Automatic Speech Recognition, Paris, France, 2000, pp. 221-227.
15. A. Tritschler and R. Gopinath, "Improved speaker segmentation and segments clustering using the Bayesian information criterion," in Proc. EUROSPEECH'99, vol. 2, 1999, pp. 679-682.
16. J. R. Bellegarda, "Exploiting latent semantic information in statistical language modeling," Proc. IEEE, vol. 88, no. 8, pp. 1279-1296, 2000.
17. C. D. Manning and H. Schutze, Foundations of Statistical Natural Language Processing. Cambridge, MA: MIT Press, 1999.
18. A. C. Rencher, Multivariate Statistical Inference and Applications. New York: Wiley, 1998.
19. A. P. Dempster, N. M. Laird, and D. B. Rubin, "Maximum likelihood from incomplete data via the EM algorithm," J. R. Statist. Soc., vol. 39, pp. 1-38, 1977.
20. X. Huang, A. Acero, and H.-W. Hon, Spoken Language Processing: A Guide to Theory, Algorithm, and System Development. Englewood Cliffs, NJ: Prentice-Hall, 2001.
21. S. D. Pietra, V. D. Pietra, and J. Lafferty, "Inducing features of random fields," IEEE Trans. Pattern Anal. Machine Intell., vol. 19, no. 4, pp. 380-393, Apr. 1997.
22. S. M. Kay, Fundamentals of Statistical Signal Processing: Detection Theory. Englewood Cliffs, NJ: Prentice-Hall, 1998.
23. L. L. Chang, "The Modality Words in Modern Mandarin," Tech. Rep., CKIP 93-06, 1993.
24. Y.-J. Chen, C.-H, Wu, Y.-H. Chiu, and H.-C. Liao, "Generation of robust phonetic set and decision tree for Mandarin using chi-square testing," Speech Commun., vol. 38, no. 3-4, pp. 349-364, 2002.
25. Carnegie Mellon University Pronouncing Dictionary, [Online], Available: http://www.speech.cs.cmu.edu/cgi-bin/cmudict.
26. K. Liim, Taiwan Dictionary of Words With Modern Spelling: Taiwan EDUTECH Foundation Press, 1988.
27. Y.-J. Sher, K.-C. Chung, and C.-H. Wu, "Establish Taiwanese 7-tones syllable-based synthesis units database for the prototype development of text-to-speech system," in Proc. ROCUNG XII, 1999, pp. 15-35.
28. Y. J. Chen, "A Study on Conversational Speech Recognition and Verification in Computer Telephony Integration," Ph.D. Thesis, National Cheng Kung Univ., Tainan, Taiwan, R.O.C., 2000.
29. R. Baeza-Yates and B. Ribeiro-Neto, Modern Information Retrieval. Reading, MA: Addison-Wesley, 1999.
30. J. Chen and A. K. Gupta, Parametric Statistical Change Point Analysis. New York: Birkhäuser, 2000.