Algorithms of segmentation of speech signal on the correlated noise background

Authors

DOI:

https://doi.org/10.15587/2313-8416.2018.129703

Keywords:

speech segmentation, sliding-average autoregressive model, moment functions, formants, phonemes, correlated noise

Abstract

Algorithms of segmentation based on formant and antiformant assessments are considered in the article. An algorithm for speech segmentation using momentary functions of third and fourth order is obtained. It is proposed to use digital filtering based on the sliding-average autoregressive model to suppress correlated noise. Estimates of variance in estimating the time boundaries of words for a number of proposed speech segmentation algorithms are obtained

Author Biography

Sergey Omelchenko, Kharkiv National University of Radio Electronics Nauky ave., 14, Kharkiv, Ukraine, 61166

PhD, Associate Professor

Department of Information Network Engineering

References

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Published

2018-04-27

Issue

No. 4 (2018)

Section

Technical Sciences

License

Copyright (c) 2018 Sergey Omelchenko

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