Speech Segmentation Algorithm Based on an Analysis of the Normalized Power Spectral Density

Authors

DOI:

https://doi.org/10.26636/jtit.2010.4.1095

Keywords:

phoneme segmentation, power spectral density, short-term signal energy, peaker independent, voice systems

Abstract

This article demonstrates a new approach to speaker independent phoneme detection. The core of the algorithm is to measure the distance between normalized power spectral densities in adjacent, short-time segments and verify it based on velocity of changes of values of short-time signal energy analysis. The results of experiment analysis indicate that proposed algorithm allows revealing a phoneme structure of pronounced speech with high probability. The advantages of this algorithm are absence of any prior information on a signal or model of phonemes and speakers that allows the algorithm to be speaker independent and have a low computation complexity.

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References

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Submitted

2023-06-27

Published

2010-12-30

Issue

No. 4 (2010)

Section

RESEARCH ARTICLES

License

Copyright (c) 2023 Journal of Telecommunications and Information Technology

Creative Commons License

This work is licensed under a Creative Commons Attribution 4.0 International License.

How to Cite

[1]
D. Pekar and S. Tsikhanenka, “Speech Segmentation Algorithm Based on an Analysis of the Normalized Power Spectral Density”, JTIT, vol. 42, no. 4, pp. 44–49, Dec. 2010, doi: 10.26636/jtit.2010.4.1095.