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Speech Signal Analysis With a Refined Iterative Adaptive Method

Speech Signal Analysis With a Refined Iterative Adaptive Method

Youcef Tabet
Copyright: © 2022 |Volume: 11 |Issue: 1 |Pages: 18
ISSN: 2578-7551|EISSN: 2578-7543|EISBN13: 9781683183457|DOI: 10.4018/IJECME.313036
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MLA

Tabet, Youcef. "Speech Signal Analysis With a Refined Iterative Adaptive Method." IJECME vol.11, no.1 2022: pp.1-18. http://doi.org/10.4018/IJECME.313036

APA

Tabet, Y. (2022). Speech Signal Analysis With a Refined Iterative Adaptive Method. International Journal of Electronics, Communications, and Measurement Engineering (IJECME), 11(1), 1-18. http://doi.org/10.4018/IJECME.313036

Chicago

Tabet, Youcef. "Speech Signal Analysis With a Refined Iterative Adaptive Method," International Journal of Electronics, Communications, and Measurement Engineering (IJECME) 11, no.1: 1-18. http://doi.org/10.4018/IJECME.313036

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Abstract

A new speech signal analysis method referred to as a refined iterative adaptive method (RIAM) is introduced in this paper. Based on time-varying adaptive sinusoidal modeling, the RIAM method tries to determine in an iterative adaptive manner the instantaneous components of time-varying quasi-periodic multi-component signals such as voiced speech. The proposed method can adjust the current analysis parameters to the time-varying characteristics of the speech signal. This is done using a refined iterative sinusoidal parameter estimation algorithm based on a frequency correction mechanism combined with an adaptive scheme. The experiments on voiced speech demonstrate that the proposed RIAM algorithm outperforms some well-known state-of-the-art approaches. The RIAM algorithm provides a higher signal to reconstruction error ratio (SRER) of 42.267 dB with an improvement of 19.752 dB, 5.054 dB, and 2.552 dB compared to the conventional sinusoidal model (SM), adaptive harmonic model (aHM), and extended adaptive quasi harmonic model (eaQHM), respectively.

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