Abstract

This research relates to the field of speech technologies, where the key problem is the optimization of speech signal processing under conditions of a priori uncertainty of its fine structure. The task of automatic (objective) analysis of voice timbre using a speech signal of finite duration is considered. It is proposed to use a universal information-theoretic approach to solve it. Based on the Kullback-Leibler divergence, an expression is obtained for the asymptotically optimal decision statistic for distinguishing speech signals by voice timbre. Pointed to an acute problem in its practical implementation, namely: synchronization of the sequence of observations with the main tone of speech signals. To overcome the described problem, an objective measure of timbre differences in speech signals is proposed in terms of the acoustic theory of speech production and its model of the speaker’s vocal tract of the “acoustic trumpet” type. The possibilities of practical implementation of a new measure based on an adaptive recursive are considered. A full-scale experiment was set up and carried out. According to its results, two main properties of the proposed measure were confirmed: high sensitivity to differences in speech signals in terms of voice timbre and, at the same time, invariance with respect to the pitch frequency. The results obtained can be used in the design and research of digital speech processing systems tuned to the speaker’s voice, for example, digital speech transmission systems, biometric, biomedical systems, etc.

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