A method for voiced (V), unvoiced (UV), or silence (S) classification of speech segments, based on the maximum a posteriori probability criterion, is presented. The a posteriori probabilities of the three classes are determined using a vector x equals (f//1 . . . , f//L ) of measurements on the segment under consideration. It is assumed that the vector x has an L-dimensional Gaussian distribution with an expected random value also characterized by an L-dimensional Gaussian distribution. In addition, it is assumed that the sequence of the classes constitutes a first-order stationary Markov chain. The initial parameters are estimated in a training phase. During the application phase, the decision method is adapted by using the previous classifications in order to update the probability density function of the expected random values

A Bayesian-adaptive decision method for Voiced-Unvoiced-Silence classification of segments of a speech signal / Bruno, Giordano; DI BENEDETTO, Maria Gabriella; DI BENEDETTO M., G; Gilio, Angelo; P., Mandarini. - In: IEEE TRANSACTIONS ON ACOUSTICS, SPEECH, AND SIGNAL PROCESSING. - ISSN 0096-3518. - STAMPA. - ASSP-35:(1987), pp. 556-559.

A Bayesian-adaptive decision method for Voiced-Unvoiced-Silence classification of segments of a speech signal

BRUNO, Giordano;DI BENEDETTO, Maria Gabriella;GILIO, ANGELO;
1987

Abstract

A method for voiced (V), unvoiced (UV), or silence (S) classification of speech segments, based on the maximum a posteriori probability criterion, is presented. The a posteriori probabilities of the three classes are determined using a vector x equals (f//1 . . . , f//L ) of measurements on the segment under consideration. It is assumed that the vector x has an L-dimensional Gaussian distribution with an expected random value also characterized by an L-dimensional Gaussian distribution. In addition, it is assumed that the sequence of the classes constitutes a first-order stationary Markov chain. The initial parameters are estimated in a training phase. During the application phase, the decision method is adapted by using the previous classifications in order to update the probability density function of the expected random values
01 Pubblicazione su rivista::01a Articolo in rivista
A Bayesian-adaptive decision method for Voiced-Unvoiced-Silence classification of segments of a speech signal / Bruno, Giordano; DI BENEDETTO, Maria Gabriella; DI BENEDETTO M., G; Gilio, Angelo; P., Mandarini. - In: IEEE TRANSACTIONS ON ACOUSTICS, SPEECH, AND SIGNAL PROCESSING. - ISSN 0096-3518. - STAMPA. - ASSP-35:(1987), pp. 556-559.
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Utilizza questo identificativo per citare o creare un link a questo documento: https://hdl.handle.net/11573/16213
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