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

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 detectionmethods in heavy noise environments.