Comprehensive Evaluation of VAD-Based and STM-Based Speech Detection Under Heavy Noise Conditions

Speech detection under heavy noise conditions remains a significant challenge, even for modern voice activity detection (VAD) methods.In this study, we propose a framework based on spectro-temporal modulation (STM) features that demonstrates superior performance compared with conventional VAD-based methods.Furthermore, comprehensive analyses across various metrics and signal-to-noise ratios (SNRs) provide deeper insights into the efficacy of detection methods in heavy noise environments.

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Publication Details

Journal
Journal of Signal Processing
Published
2026-06-30
DOI
https://doi.org/10.2299/jsp.30.115
Primary Topic
Speech and Audio Processing
Type
article
Field-Weighted Citation Impact
0.00

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article

Comprehensive Evaluation of VAD-Based and STM-Based Speech Detection Under Heavy Noise Conditions

Masashi Unoki, Như Quỳnh Trần, Quoc‐Huy Nguyen, Nguyen Van Dinh
Journal of Signal Processing
Speech and Audio Processing
article

Comprehensive Evaluation of VAD-Based and STM-Based Speech Detection Under Heavy Noise Conditions

Masashi Unoki, Như Quỳnh Trần, Quoc‐Huy Nguyen, Nguyen Van Dinh
article en

Abstract

Speech detection under heavy noise conditions remains a significant challenge, even for modern voice activity detection (VAD) methods.In this study, we propose a framework based on spectro-temporal modulation (STM) features that demonstrates superior performance compared with conventional VAD-based methods.Furthermore, comprehensive analyses across various metrics and signal-to-noise ratios (SNRs) provide deeper insights into the efficacy of detection methods in heavy noise environments.

Journal of Signal ProcessingVol. 30(4)
Graduate School USA (US)
Japan Society for the Promotion of Science
Peace, Justice and strong institutions
Openalex Percentile: Top 6%
Speech and Audio Processing
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