TaylorBeamformer: Learning All-Neural Beamformer for Multi-Channel Speech Enhancement from Taylor's Approximation Theory

03/14/2022
by   Andong Li, et al.
0

While existing end-to-end beamformers achieve impressive performance in various front-end speech processing tasks, they usually encapsulate the whole process into a black box and thus lack adequate interpretability. As an attempt to fill the blank, we propose a novel neural beamformer inspired by Taylor's approximation theory called TaylorBeamformer for multi-channel speech enhancement. The core idea is that the recovery process can be formulated as the spatial filtering in the neighborhood of the input mixture. Based on that, we decompose it into the superimposition of the 0th-order non-derivative and high-order derivative terms, where the former serves as the spatial filter and the latter is viewed as the residual noise canceller to further improve the speech quality. To enable end-to-end training, we replace the derivative operations with trainable networks and thus can learn from training data. Extensive experiments are conducted on the synthesized dataset based on LibriSpeech and results show that the proposed approach performs favorably against the previous advanced baselines.

READ FULL TEXT

page 2

page 4

research
04/30/2022

Taylor, Can You Hear Me Now? A Taylor-Unfolding Framework for Monaural Speech Enhancement

While the deep learning techniques promote the rapid development of the ...
research
03/14/2022

MDNet: Learning Monaural Speech Enhancement from Deep Prior Gradient

While traditional statistical signal processing model-based methods can ...
research
03/13/2023

Guided Speech Enhancement Network

High quality speech capture has been widely studied for both voice commu...
research
11/18/2022

Exploring WavLM on Speech Enhancement

There is a surge in interest in self-supervised learning approaches for ...
research
12/09/2021

A Training Framework for Stereo-Aware Speech Enhancement using Deep Neural Networks

Deep learning-based speech enhancement has shown unprecedented performan...
research
09/01/2021

Embedding and Beamforming: All-neural Causal Beamformer for Multichannel Speech Enhancement

The spatial covariance matrix has been considered to be significant for ...
research
10/01/2021

Leveraging Low-Distortion Target Estimates for Improved Speech Enhancement

A promising approach for multi-microphone speech separation involves two...

Please sign up or login with your details

Forgot password? Click here to reset