Speech Enhancement with Dual-path Multi-Channel Linear Prediction Filter and Multi-norm Beamforming

TL;DR

This paper introduces a novel speech enhancement approach combining dual-path multi-channel linear prediction filters with multi-norm beamforming, effectively reducing reverberation and noise in challenging acoustic environments.

Contribution

The paper presents a dual-path MCLP filter design and a robust prediction order selection method, improving speech enhancement performance over existing techniques in high reverberation conditions.

Findings

Outperforms baseline methods in reverberant environments

Effective in high reverberation scenarios

Robust prediction order selection method

Abstract

In this paper, we propose a speech enhancement method us ing dual-path Multi-Channel Linear Prediction (MCLP) filters and multi-norm beamforming. Specifically, the MCLP part in the proposed method is designed with dual-path filters in both time and frequency dimensions. For the beamforming part, we minimize the power of the microphone array output as well as the l1 norm of the denoised signals while preserving source sig nals from the target directions. An efficient method to select the prediction orders in the dual-path filters is also proposed, which is robust for signals with different reverberation time (T60) val ues and can be applied to other MCLP-based methods. Eval uations demonstrate that our proposed method outperforms the baseline methods for speech enhancement, particularly in high reverberation scenarios.