A mixture model approach for formant tracking and the robustness of student's-t distribution

IEEE Transactions on Audio, Speech and Language Processing

Volumn 20, Issue 10, 2012, Pages 2626-2636

  Sundar, Harshavardhan ^a   Seelamantula, Chandra Sekhar ^a   Sreenivas, Thippur V ^a  

^a INDIAN INSTITUTE OF SCIENCE   (India)

Author keywords

Formant tracking; Gaussian mixture model (GMM); multimodal density estimation; statistical mixture modeling; Student's t mixture model (tMM)

Indexed keywords

DENSITY ESTIMATION; FORMANT TRACKING; GAUSSIAN MIXTURE MODEL; MIXTURE MODEL; MIXTURE MODELING;

ADDITIVE NOISE; MODULATION; STUDENTS; TRACKING (POSITION);

MIXTURES;

EID: 84867168402     PISSN: 15587916     EISSN: None     Source Type: Journal    
DOI: 10.1109/TASL.2012.2209418     Document Type: Article

References (41)

1. S. McCandless, "An algorithm for automatic formant extraction using linear prediction spectra," IEEE Trans. Acoust., Speech, Signal Process., vol. ASSP-22, no. 2, pp. 135-141, Apr. 1974.
2. T. Toyoshima, N. Miki, and N. Nagai, "Adaptive formant estimation with compensation for gross spectral shape," Electron. Comm. Jpn. Pt. III, pp. 58-68, 1991.
3. A. Potamianos and P. Maragos, "Speech formant frequency and bandwidth tracking using multiband energy demodulation," J. Acoust. Soc. Amer., vol. 99, no. 6, pp. 3795-3806, 1996.
4. P. Maragos, J. F. Kaiser, and T. F. Quatieri, "On amplitude and frequency demodulation using energy operators," IEEE Trans. Signal Process., vol. 41, no. 4, pp. 1532-1550, Apr. 1993.
5. W. A. Gardner, Introduction to Random Processes With Applications to Signals and Systems, 2nd ed. New York: McGraw-Hill, 1990.
6. A. Papoulis, Probability, Random Variables and Stochastic Processes, 3rd ed. New York: McGraw-Hill, Feb. 1991.
7. L. Deng, L. Lee, H. Attias, and A. Acero, "A structured speech model with continuous hidden dynamics and prediction-residual training for tracking vocal tract resonances," in Proc. Int. Conf. Acoust., Speech, Signal Process., 2004, pp. 557-560.
8. L. Deng, L. Lee, H. Attias, and A. Acero, "Adaptive Kalman filtering and smoothing for tracking vocal-tract resonances using a continuous-valued hidden dynamic model," IEEE Trans. Audio, Speech, Lang. Process., vol. 15, no. 1, pp. 13-23, Jan. 2007.
9. I. Y. Ozbek and M. Demirekler, "Tracking of speech formant frequencies," in Proc. IEEE 14th Signal Process. Commun. Appl. Conf., 2006, pp. 1-4.
10. I. Y. Ozbek and M. Demirekler, "Tracking of vocal-tract resonances based on dynamic programming and Kalman filtering," in Proc. IEEE 16th Signal Process. Commun. Appl. Conf., 2008, pp. 1-4.
11. I. Y. Ozbek and M. Demirekler, "Vocal-tract resonances tracking based on voiced and unvoiced speech classification using dynamic programming and fixed-interval Kalman smoother," in Proc. Int. Conf. Acoust., Speech, Signal Process., 2008, pp. 4217-4220.
12. K. Kalgaonkar and M. Clements, "Vocal-tract-area based formant tracking using particle filter," in Proc. Int. Conf. Acoust., Speech, Signal Process., Mar. 2008, pp. 3405-3408.
13. Y. Shi and E. Chang, "Spectrogram-based formant tracking via particle filters," in Proc. Int. Conf. Acoust. Speech Signal Process., 2003, vol. 1, pp. 168-171.
14. E. Ozkan, I. Y. Ozbek, and M. Demirekler, "Dynamic speech spectrum representation and tracking variable number of vocal tract resonance frequencies with time-varying Dirichlet process mixture models," IEEE Trans. Audio, Speech, Lang. Process., vol. 17, no. 8, pp. 1518-1532, Nov. 2009.
15. C. Glaser, M. Heckmann, F. Joublin, and C. Goerick, "Combining auditory preprocessing and Bayesian estimation for robust formant tracking," IEEE Trans. Audio, Speech Lang. Process., vol. 18, no. 2, pp. 224-236, Feb. 2010.
16. K. Mustafa and I. C. Bruce, "Robust formant tracking for continuous speech with speaker variability," IEEE Trans. Audio, Speech, Lang. Process., vol. 14, no. 2, pp. 435-444, Mar. 2006.
17. G. Garcia, P. Depalle, and X. Rodet, "Tracking of partials for additive sound synthesis using hidden Markov models," in Proc. Int. Conf. Acoust. Speech, Signal Process., Apr. 1993, vol. 1, pp. 225-228.
18. A. Acero, "Formant analysis and synthesis using hidden Markov models," in Proc. Eur. Conf. Speech Commun. Technol. (EUROSPEECH), 1999, pp. 1047-1050.
19. D. T. Toledano, J. G. Villardebo, and L. H. Gomez, "Initialization, training, and context-dependency in HMM-based formant tracking," IEEE Trans. Audio, Speech, Lang. Process., vol. 14, no. 2, pp. 511-523, Mar. 2006.
20. A. D. Doulamis, N. D. Doulamis, and S. D. Kollias, "On-line retrainable neural networks: Improving the performance of neural networks in image analysis problems," IEEE Trans. Neural Netw., vol. 11, no. 1, pp. 137-155, Jan. 2000.
21. D. G. Tzikas, A. C. Likas, and N. P. Galatsanos, "Variational Bayesian sparse kernel-based blind image deconvolution with Student's-t priors," IEEE Trans. Image Process., vol. 18, no. 4, pp. 753-764, Apr. 2009.
22. G. Sfikas, C. Nikou, and N. Galatsanos, "Robust image segmentation with mixtures of Student's-t distributions," in Proc. IEEE Int. Conf. Image Process., 2007, vol. 1, pp. 273-276.
23. S. Chatzis and T. Varvarigou, "Robust fuzzy clustering using mixtures of Student's-t distributions," Patt. Recog. Lett., vol. 29, no. 13, pp. 1901-1905, 2008.
24. S. P. Chatzis, D. I. Kosmopoulos, and T. A. Varvarigou, "Robust sequential data modeling using an outlier tolerant hidden markov model," IEEE Trans. Pattern Anal. Mach. Intell., vol. 31, no. 9, pp. 1657-1669, Sep. 2009.
25. T. M. Nguyen and Q. M. J. Wu, "Robust Student's-t mixture model with spatial constraints and its application in medical image segmentation," IEEE Trans. Med. Imag., vol. 31, no. 1, pp. 103-116, Jan. 2012.
26. Z. Moghaddam and M. Piccardi, "Robust density modelling using the Student's-t distribution for human action recognition," in Proc. IEEE Int. Conf. Imag. Process., 2011, pp. 3261-3264.
27. K. Makantasis, A. Doulamis, and N. Matsatstnis, "Student's-t background modeling for person's fall detection through visual cues," in Proc. IEEE Workshop Interactive Multimedia Services, Dublin, Ireland, 2012.
28. H. Sundar and T. V. Sreenivas, "Robust mixture modeling using t-distribution: Application to speaker ID," in Proc. Interspeech, 2010, pp. 2750-2753.
29. S. Chatzis and T. Varvarigou, "A robust to outliers hidden Markov model with application in text-dependent speaker identification," in Proc. IEEE Int. Conf. Signal Process. Commun., Nov. 2007, pp. 804-807.
30. Y. Hu and P. C. Loizou, "Subjective evaluation and comparison of speech enhancement algorithms," Speech Commun., vol. 49, pp. 588-601, 2007.
31. P. Boersma and D.Weenik, Praat: Doing Phonetics by Computer (Version 5.1.25), (Computer Program).
32. [Online]. Available: https://sites.google.com/site/ chandrasekharseelamantula/projects
33. A. C. Bovik, P. Maragos, and T. F. Quatieri, "AM-FM energy detection and separation in noise using multiband energy operators," IEEE Trans. Signal Process., vol. 41, no. 12, pp. 3245-3265, Dec. 1993.
34. P. Maragos, J. F. Kaiser, and T. F. Quatieri, "Energy separation in signal modulations with application to speech analysis," IEEE Trans. Signal Process., vol. 41, no. 10, pp. 3024-3051, Oct. 1993.
35. C. M. Bishop, Pattern Recognition and Machine Learning (Information Science and Statistics). Secaucus, NJ: Springer-Verlag, 2006.
36. D. Peel and G. J. McLachlan, "Robust mixture modelling using the t distribution," Statist. Comput., vol. 10, no. 4, pp. 339-348, 2000.
37. [Online]. Available: http://www.ece.mcmaster.ca/ibruce/mb-ftracker/mb- ftracker.htm
38. R. J. Wakelin, "Tribology: The friction, lubrication, and wear of moving parts," Ann. Rev. Mat. Sci., vol. 4, no. 1, pp. 221-253, 1974.
39. [Online]. Available: http://www.torontostle.com/Tribology-101.html
40. T. Thayaparan, L. Stankovic, M. Amin, V. Chen, L. Cohen, and B. Boashash, "Editorial: Time-frequency approach to radar detection, imaging, and classification," IET Signal Process., vol. 4, no. 3, p. 197, 2010.
41. B. Boashash, Time-Frequency Signal Analysis and Processing-A Comprehensive Reference. Amsterdam, The Netherlands: Elsevier, Oct. 2003.