Extraction of speaker-specific excitation information from linear prediction residual of speech

Speech Communication

Volumn 48, Issue 10, 2006, Pages 1243-1261

  Mahadeva Prasanna, S R ^a   Gupta, Cheedella S ^b   Yegnanarayana, B ^b  

^a INDIAN INSTITUTE OF TECHNOLOGY GUWAHATI   (India)

^b INDIAN INSTITUTE OF TECHNOLOGY MADRAS   (India)

Author keywords

AANN model; Excitation information; LP residual; Speaker recognition; Vocal tract information

Indexed keywords

DATA ACQUISITION; DATABASE SYSTEMS; ERROR CORRECTION; NEURAL NETWORKS; SAMPLING; SPEECH RECOGNITION;

AUTOASSOCIATIVE NEURAL NETWORK (AANN); EXCITATION INFORMATION; SPEAKER RECOGNITION; VOCAL TRACT INFORMATION;

SPEECH SYNTHESIS;

EID: 33748443739     PISSN: 01676393     EISSN: None     Source Type: Journal    
DOI: 10.1016/j.specom.2006.06.002     Document Type: Article

References (44)

1. Ananthapadmanabha T.V., and Yegnanarayana B. Epoch extraction from linear prediction residual for identification of closed glottis interval. IEEE Trans. Acoust. Speech Signal Process. ASSP-27 (1979) 309-319
2. Anjani, A.V.N.S., 2000. Autoassociate neural network models for processing degraded speech. MS thesis, Department of Computer Science and Engineering, Indian Institute of Technology Madras, Chennai 600 036, India.
3. Atal B.S. Automatic speaker recognition based on pitch contours. J. Acoust. Soc. Amer. 52 6 (1972) 1687-1697
4. Atal B.S. Automatic recognition of speakers from their voices. Proc. IEEE 64 4 (1976) 460-475
5. Campbell J.P. Speaker recognition: a tutorial. Proc. IEEE 85 (1997) 1436-1462
6. Deller Jr. J.R., Hansen J.H.L., and Proakis J.G. Discrete-Time Processing of Speech Signals (2000), IEEE Press, New York
7. Diamantaras K.I., and Kung S.Y. Principal Component Neural Networks: Theory and Applications (1996), John Wiley and Sons, New York
8. Doddington, G., 2001. Speaker recognition based on idiolectal differences between speakers. In: Proc. European Conf. on Speech Processing, Technology (EUROSPEECH), Aalborg, Denmark, pp. 2521-2524.
9. M. Faundez, D. Rodriguez, 1998. Speaker recognition using residual signal of linear and nonlinear prediction models. In: Proc. Internat. Conf. on Spoken Language Processing.
10. Feustel T.C., Velius G.A., and Logan R.J. Human and machine performance on speaker identity verification. Speech Technol. (1989) 169-170
11. Furui S. An overview of speaker recognition technology. In: Lee C.H., Soong F.K., and Paliwal K.K. (Eds). Automatic Speech and Speaker Recognition (1996), Kluwer Academic, Boston Chapter 2
12. Furui S. Recent advances in speaker recognition. Pattern Recognition Lett. 18 (1997) 859-872
13. Gupta, C.S., 2003. Significance of source features for speaker recognition. MS thesis, Department of Computer Science and Engineering, Indian Institute of Technology Madras, Chennai 600 036, India.
14. Haykin S. Neural Networks: A Comprehensive Foundation (1999), Prentice-Hall Inc., New Jersey
15. Ikbal, M.S., Misra, H., Yegnanarayana, B., 1999. Analysis of autoassociative mapping neural networks. In: Proc. Internat. Joint Conf. on Neural Networks (IJCNN), USA, pp. 854-858.
16. Kajarekar, S.S., Adami, A.G., Hermansky, H., 2002. Ogi submission - NIST 2002 one-speaker detection task. In: Proc. NIST Speaker Recognition Workshop, Vienna, VA, USA.
17. Kajarekar, S.S., Adami, A.G., Hermansky, H., 2003. Novel approaches for one and two-speaker detection. In: Proc. European Conf. on Speech Processing, Technology (EUROSPEECH).
18. Kishore, S.P., 2001. Speaker verification using autoassociative neural network models. MS thesis, Department of Computer Science and Engineering, Indian Institute of Technology Madras, Chennai 600 036, India.
19. Kishore, S.P., Yegnanarayana, B., 2001. Online text-independent speaker verification system using autoassociative neural network models. In: Proc. Internat. Joint Conf. on Neural Networks (IJCNN), Washington, DC, USA.
20. Liu, J.H.L., Palm, G., 1997. On the use of features from prediction residual signal in speaker recognition. In: Proc. European Conf. Speech Processing, Technology (EUROSPEECH), pp. 313-316.
21. Madhukumar, A.S., 1993. Intonation knowledge for speech systems for an Indian language. Ph.D. thesis, Department of Computer Science and Engineering, Indian Institute of Technology Madras, Chennai 600 036, India.
22. Makhoul J. Linear prediction: a tutorial review. Proc. IEEE 63 (1975) 561-580
23. Martin, A., 1999. NIST 1999 speaker recognition evaluation plan. In: Proc. NIST Speaker Recognition Workshop, USA.
24. Martin, A., 2001. NIST 2001 speaker recognition evaluation plan. In: Proc. NIST Speaker Recognition Workshop, USA.
25. Martin, A., 2002. NIST 2002 speaker recognition evaluation plan. In: Proc. NIST Speaker Recognition Workshop, USA.
26. Murthy, K.S.R., Prasanna, S.R.M., Yegnanarayana, B., 2004. Speaker-specific information from residual phase. In: Internat. Conf. on Signal Processing and Communications, Bangalore, India, pp. 516-519.
27. O'Shaughnessy D. Speaker recognition. IEEE ASSP Mag. 3 (1986) 4-17
28. O'Shaughnessy D. Speech Communication: Human and Machine (1987), Addison-Wesley, New York
29. Plumpe M.D., Quatieri T.F., and Reynolds D.A. Modeling of the glottal flow derivative waveform with application to speaker identification. IEEE Trans. Speech Audio Process. 1 (1999) 569-586
30. Prasanna, S.R.M., Yegnanarayana, B., 2004. Extraction of pitch in adverse conditions. In: Proc. IEEE Internat. Conf. on Acoust., Speech, Signal Processing (ICASSP), Montreal, Canada.
31. Rabiner L.R., and Juang B.H. Fundamentals of Speech Recognition (1993), Prentice-Hall, Englewood Cliffs, NJ
32. Reddy, K.S., 2004. Source and system features for speaker recognition. MS thesis, Department of Computer Science and Engineering, Indian Institute of Technology Madras, Chennai 600 036, India.
33. Reynolds D.A., Quateri T.F., and Dunn R.B. Speaker recognition using adapted gaussian mixture models. Digital Signal Process. 10 (2000) 19-41
34. Rosenberg A.E. Effect of glottal pulse shape on the quality of natural vowels. J. Acoust. Soc. Amer. 49 (1971) 583-590
35. Rosenberg A.E. Automatic speaker verification: a review. Proc. IEEE 64 4 (1976) 475-487
36. Smits R., and Yegnanarayana B. Determination of instants of significant excitation in speech using group delay function. IEEE Trans. Speech Audio Process. 3 (1995) 325-333
37. Thevenaz P., and Hugli H. Usefulness of lpc residue in text-independent speaker verification. Speech Commun. 17 (1995) 145-157
38. Wakita H. Residual energy of linear prediction to vowel and speaker recognition. IEEE Trans. Acoust. Speech Signal Process. 24 (1976) 270-271
39. Weber, F., Manganaro, L., Peskin, B., Shriberg, E., 2002. Using prosodic and lexical information for speaker identification. In: Proc. IEEE Internat. Conf. on Acoust. Speech Signal Processing (ICASSP), Orlando, FL, USA, pp. 141-144.
40. Yegnanarayana B. Artificial Neural Networks (1999), Prentice-Hall, New Delhi, India
41. Yegnanarayana, B., Madhukumar, A.S., Ramachandran, V.R., 1992. Robust features for applications in speech and speaker recognitions. In: Proc. ESCA Workshop on Speech in Adverse Conditions, Cannes Mandelieu, France.
42. Yegnanarayana, B., Reddy, K.S., Kishore, S.P., 2001. Source and system features for speaker recognition using AANN models. In: Proc. IEEE Internat. Conf. on Acoust. Speech Signal Processing (ICASSP), Salt Lake City, Utah, USA, pp. 409-412.
43. Yegnanarayana, B., Prasanna, S.R.M., Gangashetty, S.V., Gupta, C.S., Guruprasad, S., Dhananjay, N., 2002. IIT Madras speaker verification system. In: Proc. NIST Speaker Recognition Workshop, Vienna, VA, USA.
44. Yegnanarayana B., Prasanna S.R.M., Zachariah J.M., and Gupta C.S. Combining evidences from source, suprasegmental and spectral features for fixed-text speaker verification. IEEE Trans. Speech Audio Process. 13 4 (2005) 575-582