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arXiv · 2507.02192

An Investigation on Combining Geometry and Consistency Constraints into Phase Estimation for Speech Enhancement

Chun-Wei Ho·Pin-Jui Ku·Hao Yen·Sabato Marco Siniscalchi·Yu Tsao·Chin-Hui Lee
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Abstract

We propose a novel iterative phase estimation framework, termed multi-source Griffin-Lim algorithm (MSGLA), for speech enhancement (SE) under additive noise conditions. The core idea is to leverage the ad-hoc consistency constraint of complex-valued short-time Fourier transform (STFT) spectrograms to address the sign ambiguity challenge commonly encountered in geometry-based phase estimation. Furthermore, we introduce a variant of the geometric constraint framework based on the law of sines and cosines, formulating a new phase reconstruction algorithm using noise phase estimates. We first validate the proposed technique through a series of oracle experiments, demonstrating its effectiveness under ideal conditions. We then evaluate its performance on the VB-DMD and WSJ0-CHiME3 data sets, and show that the proposed MSGLA variants match well or slightly outperform existing algorithms, including direct phase estimation and DNN-based sign prediction, especially in terms of background noise suppression.

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Chun-Wei Ho, Pin-Jui Ku, Hao Yen, Sabato Marco Siniscalchi, Yu Tsao, Chin-Hui Lee. 2025-07-02. An Investigation on Combining Geometry and Consistency Constraints into Phase Estimation for Speech Enhancement. https://arxiv.org/abs/2507.02192

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