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Minimum of Information Divergence Criterion for Signals with Tuning to Speaker Voice in Automatic Speech Recognition

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Abstract

It is considered a problem of automatic speech recognition at basic, phonetic level of speech signal processing. It is researched a problem of noise-immunity increase. For its solution it is proposed a criterion of minimum information divergence of the signals with tuning to a speaker voice and automatic scaling of speech template to thin structure of observed (current) speech frame. An example of its practical realization is considered, efficiency characteristics are researched. Applying the author’s software we carry out an experiment and obtain qualitative estimations of threshold signals gain in case of application of proposed criterion. It is shown than this gain can be 10 dB and greater under certain conditions. Obtained results and drawn conclusions are intended it to their application for development and modernization of existent systems and techniques of automatic processing and recognition of speech intended it to operation in conditions of intensive noise effect.

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Authors and Affiliations

  1. Nizhny Novgorod State Linguistic University, Nizhny Novgorod, Russia

    V. V. Savchenko

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  1. V. V. Savchenko
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Correspondence to V. V. Savchenko.

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The authors declare that they have no conflict of interest.

Russian Text © The Author(s), 2020, published in Izvestiya Vysshikh Uchebnykh Zavedenii, Radioelektronika, 2020, Vol. 63, No. 1, pp. 55–68.

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Savchenko, V.V. Minimum of Information Divergence Criterion for Signals with Tuning to Speaker Voice in Automatic Speech Recognition. Radioelectron.Commun.Syst. 63, 42–54 (2020). https://doi.org/10.3103/S0735272720010045

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  • DOI: https://doi.org/10.3103/S0735272720010045

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