Preprocessing of speech signals is considered a crucial step in the development of a robust and efficient speech or speaker recognition system. In this paper, we present some popular statistical outlier-detection based strategies to segregate the silence/unvoiced part of the speech signal from the voiced portion. The proposed methods are based on the utilization of the 3 σ edit rule, and the Hampel Identifier which are compared with the conventional techniques: (i) short-time energy (STE) based methods, and (ii) distribution based methods. The results obtained after applying the proposed strategies on some test voice signals are encouraging.
[1] Saha. G., Chakroborty. S., and Senapati. S, "A new Silence
Removal and End Point Detection Algorithm for Speech and
Speaker Recognition Applications", in Proc. of Eleventh
National Conference on Communications (NCC), IITKharagpur,
India, January 28-30, 2005, pp. 291-295.
[2] Mitra. A., Chatterjee. B., Mitra. B. K., "Identification of
Primitive Speech Signals using TMS320C54X DSP Processor",
in Proc. of Eleventh National Conference on Communications
(NCC), IIT- Kharagpur, India, January 28-30, 2005, pp. 286-
290.
[3] Rabiner. L. R., and Juang. B. H., "Fundamentals of Speech
Recognition", AT&T, 1993, Prentice-Hall, Inc.
[4] Mitra. B. K., Young. R., Chatwin. C., "On shadow elimination
after moving region segmentation based on different threshold
selection strategies", Optics and Lasers in Engineering, vol. 45,
no. 11, pp. 1088-1093, July 2007.
[5] Atal B., Rabiner L., "A pattern recognition approach to voicedunvoiced-
silence classification with applications to speech
recognition" Acoustics, Speech, and Signal Processing [see also
IEEE transactions on Signal Processing], vol 24, 3, June 1976,
pp. 201-212.
[6] Childers. D. G., Hand. M., Larar. M. J., "Silent and
Voiced/Unvoiced/Mixed Excitation (Four Way), Classification
of Speech", IEEE Trans. On ASSP, vol 37, 11, Nov 1989,
pp1771-74.
[7] Mitra. A, Mitra. B. K., Chatterjee. B., "Recognition of Isolated
Speech Signals using Simplified Statistical Parameters",
Proceedings of World Academy of Science, Engineering and
Technology, vol.8, pp. 151-154, October 2005.
[8] Rabiner. L. R., Schafer. R. W., "Digital Processing of Speech
Signals", First Edition, Prentice-Hall.
[9] Duda R. O., Hart. P. E, Strok. D. G., "Pattern Classification",
Second Edition, John Wiley and Sons Inc., 2001.
[10] Sarma. V., Venugopal. D., "Studies on pattern recognition
approach to voiced-unvoiced-silence classification", IEEE
international conference on ICASSP, 78, 3, April 1978, pp. 1-4.
[11] Hawkins D.M, "Identification of Outliers", Great Britain,
Chapman and Hall, 1980.
[12] Pearson R.K, "Outliers in process modeling and Identification",
IEEE transactions. Consol Syst. Technologies 2001. lo (1) pp55-
63.
[13] Halin G.Z, Shafiro S.S, "Statistical Models in Engineering",
USA: Wiley, 1967.
[14] Pearson R.K. "Mining imperfect data dealing with
contamination and incomplete records", Philadelphia: SIAM;
2005.
[1] Saha. G., Chakroborty. S., and Senapati. S, "A new Silence
Removal and End Point Detection Algorithm for Speech and
Speaker Recognition Applications", in Proc. of Eleventh
National Conference on Communications (NCC), IITKharagpur,
India, January 28-30, 2005, pp. 291-295.
[2] Mitra. A., Chatterjee. B., Mitra. B. K., "Identification of
Primitive Speech Signals using TMS320C54X DSP Processor",
in Proc. of Eleventh National Conference on Communications
(NCC), IIT- Kharagpur, India, January 28-30, 2005, pp. 286-
290.
[3] Rabiner. L. R., and Juang. B. H., "Fundamentals of Speech
Recognition", AT&T, 1993, Prentice-Hall, Inc.
[4] Mitra. B. K., Young. R., Chatwin. C., "On shadow elimination
after moving region segmentation based on different threshold
selection strategies", Optics and Lasers in Engineering, vol. 45,
no. 11, pp. 1088-1093, July 2007.
[5] Atal B., Rabiner L., "A pattern recognition approach to voicedunvoiced-
silence classification with applications to speech
recognition" Acoustics, Speech, and Signal Processing [see also
IEEE transactions on Signal Processing], vol 24, 3, June 1976,
pp. 201-212.
[6] Childers. D. G., Hand. M., Larar. M. J., "Silent and
Voiced/Unvoiced/Mixed Excitation (Four Way), Classification
of Speech", IEEE Trans. On ASSP, vol 37, 11, Nov 1989,
pp1771-74.
[7] Mitra. A, Mitra. B. K., Chatterjee. B., "Recognition of Isolated
Speech Signals using Simplified Statistical Parameters",
Proceedings of World Academy of Science, Engineering and
Technology, vol.8, pp. 151-154, October 2005.
[8] Rabiner. L. R., Schafer. R. W., "Digital Processing of Speech
Signals", First Edition, Prentice-Hall.
[9] Duda R. O., Hart. P. E, Strok. D. G., "Pattern Classification",
Second Edition, John Wiley and Sons Inc., 2001.
[10] Sarma. V., Venugopal. D., "Studies on pattern recognition
approach to voiced-unvoiced-silence classification", IEEE
international conference on ICASSP, 78, 3, April 1978, pp. 1-4.
[11] Hawkins D.M, "Identification of Outliers", Great Britain,
Chapman and Hall, 1980.
[12] Pearson R.K, "Outliers in process modeling and Identification",
IEEE transactions. Consol Syst. Technologies 2001. lo (1) pp55-
63.
[13] Halin G.Z, Shafiro S.S, "Statistical Models in Engineering",
USA: Wiley, 1967.
[14] Pearson R.K. "Mining imperfect data dealing with
contamination and incomplete records", Philadelphia: SIAM;
2005.
@article{"International Journal of Information, Control and Computer Sciences:53581", author = "Ayaz Keerio and Bhargav Kumar Mitra and Philip Birch and Rupert Young and Chris Chatwin", title = "On Preprocessing of Speech Signals", abstract = "Preprocessing of speech signals is considered a crucial step in the development of a robust and efficient speech or speaker recognition system. In this paper, we present some popular statistical outlier-detection based strategies to segregate the silence/unvoiced part of the speech signal from the voiced portion. The proposed methods are based on the utilization of the 3 σ edit rule, and the Hampel Identifier which are compared with the conventional techniques: (i) short-time energy (STE) based methods, and (ii) distribution based methods. The results obtained after applying the proposed strategies on some test voice signals are encouraging.
", keywords = "STE based methods, Mahalanobis distance, 3 edit σ rule, Hampel Identifier.", volume = "2", number = "11", pages = "3723-7", }
