Soft-Constrained Spatially Selective Active Noise Control for Open-fitting Hearables

TL;DR

This paper introduces a soft-constrained spatially selective active noise control system for hearables that balances noise reduction and speech quality, outperforming traditional hard-constrained methods in simulations.

Contribution

It proposes a novel soft-constrained SSANC approach with a frequency-independent parameter, unifying and extending previous hard-constrained and conventional ANC methods.

Findings

Significant improvement in SNR, PESQ, and ESTOI over hard-constrained design.

Theoretical derivations validated through simulations.

Flexible trade-off parameter effectively balances noise reduction and speech quality.

Abstract

Recent advances in spatially selective active noise control (SSANC) using multiple microphones have enabled hearables to suppress undesired noise while preserving desired speech from a specific direction. Aiming to achieve minimal speech distortion, a hard constraint has been used in previous work in the optimization problem to compute the control filter. In this work, we propose a soft-constrained SSANC system that uses a frequency-independent parameter to trade off between speech distortion and noise reduction. We derive both time- and frequency-domain formulations, and show that conventional active noise control and hard-constrained SSANC represent two limiting cases of the proposed design. We evaluate the system through simulations using a pair of open-fitting hearables in an anechoic environment with one speech source and two noise sources. The simulation results validate the theoretical derivations and demonstrate that for a broad range of the trade-off parameter, the signal-to-noise ratio and the speech quality and intelligibility in terms of PESQ and ESTOI can be substantially improved compared to the hard-constrained design.