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Journal Article

Dual-Microphone Speech Localization and Enhancement Using a Generalized Sidelobe Canceler With Deep Voice Activity Detection

Authors: Kung, Fan-Jie; Lin, Jhong-Yan; Hsu, Kai-Hsiang; Chang, Ping-Chun

Journal of the Audio Engineering Society · Volume 74 · Issue 11 · pp. 887–903 · November 2026

Abstract

Robust speech communication in adverse acoustic environments requires high speech quality and intelligibility. This paper presents an integrated dual-microphone processing framework that jointly addresses voice activity detection (VAD), speech source localization, and speech enhancement. The proposed system employs a deep learning–based VAD trained using combined zero-crossing rate, log-likelihood ratio, and energy features to reliably distinguish speech from nonspeech segments under noisy conditions. The detected speech activity is incorporated into a diagonal unloading beamformer to improve the robustness of direction of arrival estimation, which subsequently guides a generalized sidelobe canceler for effective interference suppression. A coherence-function–based Wiener postfilter is further applied to refine residual noise estimation. The proposed framework is evaluated in terms of VAD performance, source localization accuracy, and speech enhancement effectiveness. VAD performance is assessed using accuracy, recall, precision, and F1-score, while localization accuracy is evaluated using root-mean-square error. Speech enhancement performance is evaluated using perceptual evaluation of speech quality and short-time objective intelligibility and compared with several baseline methods. Results obtained from both the simulated and real-recording experiments demonstrate that the proposed framework generally outperforms baseline methods in VAD accuracy, localization robustness, and speech enhancement performance.

Details

Publication
Journal of the Audio Engineering Society
Volume
74
Issue
11
Pages
887–903
Publication date
November 10, 2026
Affiliation
Department of Electrical Engineering, National Taipei University of Technology, Taipei, Taiwan; Department of Electrical Engineering, National Taipei University of Technology, Taipei, Taiwan; Department of Electrical Engineering, National Taipei University of Technology, Taipei, Taiwan; Department of Electrical Engineering, National Taipei University of Technology, Taipei, Taiwan (See document for exact affiliation information.)
Type
Journal Article

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