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Automatic Segmentation Of Speech By Analysis Of The Informational Homogeneity

Author

Listed:
  • Umanets S.V.

    (Belgorod filial PJSC “Rostelekom”)

  • Boldyshev A.V.

    (Belgorod filial PJSC “Rostelekom”)

  • Likholob P.G.

    (Belgorod State National Research University)

Abstract

In this paper, an algorithm for digital signal processing is considered. The purpose of the algorithm is automatic segmentation of the speech signal, that is, splitting the original signal into segments generated by action in different conditions. The principle of operation of the algorithm is based on the analysis of information homogeneity. At the beginning of the algorithm, an information model is compiled, then an analysis of information homogeneity is performed and a search for the boundaries of sound change is performed. The application of non-linearity and moving average for confident decision-making about the presence of a boundary between different sounds is considered. The paper also presents the results of computational experiments for various combinations of algorithm parameters. Numerical evaluation of the algorithm was carried out on the material from the database of marked speech fragments of the American Agency for advanced defense research projects DARPA TIMIT Acoustic-Phonetic Continuous Speech Corpus. The conclusion about the algorithm's performance is made.

Suggested Citation

  • Umanets S.V. & Boldyshev A.V. & Likholob P.G., 2020. "Automatic Segmentation Of Speech By Analysis Of The Informational Homogeneity," Economics. Information Technologies, Belgorod State University, vol. 47(2), pages 441-451.
    • Handle: RePEc:eul:ecoinf:v:47:y:2020:i:2:p:441-451
    DOI: 10.18413/2687-0932-2020-47-2-441-451
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