Speech Probability distribution based on generalized gamma distribution

Jong Won Shin, Joon Hyuk Chang, Nam Soo Kim

Research output: Contribution to conferencePaper

1 Scopus citations

Abstract

In this paper, we propose a new speech probability distribution, two-sided generalized gamma distribution (GΓD) for an efficient parametric characterization of speech spectra. GΓD forms a generalized class of parametric distributions including the Gaussian, Laplacian and Gamma probability density functions (pdf's) as special cases. All the parameters associated with the GΓD are estimated by the on-line tracking procedure according to the maximum likelihood principle. Likelihoods, coefficients of variation (CV's), and Kolmogorov-Smirnov (KS) tests show that GΓD can model the distribution of the real speech signal more accurately than the conventional Gaussian, Laplacian, Gamma pdf or generalized Gaussian distribution (GGD).

Original languageEnglish
Pages2477-2480
Number of pages4
StatePublished - 2004 Jan 1
Event8th International Conference on Spoken Language Processing, ICSLP 2004 - Jeju, Jeju Island, Korea, Republic of
Duration: 2004 Oct 42004 Oct 8

Other

Other8th International Conference on Spoken Language Processing, ICSLP 2004
CountryKorea, Republic of
CityJeju, Jeju Island
Period04/10/404/10/8

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    Shin, J. W., Chang, J. H., & Kim, N. S. (2004). Speech Probability distribution based on generalized gamma distribution. 2477-2480. Paper presented at 8th International Conference on Spoken Language Processing, ICSLP 2004, Jeju, Jeju Island, Korea, Republic of.