Model-based Speech Enhancement for Intelligibility Improvement in Binaural Hearing Aids

TL;DR

This paper introduces a binaural speech enhancement framework using a Kalman filter and joint estimation of speech and noise parameters, significantly improving speech intelligibility and quality in noisy, multi-talker scenarios for hearing aids.

Contribution

It proposes a novel binaural enhancement method that jointly estimates speech and noise parameters using a Kalman filter, leveraging information from both ears for improved robustness.

Findings

Objective measures show improved speech quality and intelligibility.

Listening tests indicate up to 15% improvement in speech intelligibility.

The method outperforms single-channel approaches in complex acoustic scenes.

Abstract

Speech intelligibility is often severely degraded among hearing impaired individuals in situations such as the cocktail party scenario. The performance of the current hearing aid technology has been observed to be limited in these scenarios. In this paper, we propose a binaural speech enhancement framework that takes into consideration the speech production model. The enhancement framework proposed here is based on the Kalman filter that allows us to take the speech production dynamics into account during the enhancement process. The usage of a Kalman filter requires the estimation of clean speech and noise short term predictor (STP) parameters, and the clean speech pitch parameters. In this work, a binaural codebook-based method is proposed for estimating the STP parameters, and a directional pitch estimator based on the harmonic model and maximum likelihood principle is used to estimate the pitch parameters. The proposed method for estimating the STP and pitch parameters jointly uses the information from left and right ears, leading to a more robust estimation of the filter parameters. Objective measures such as PESQ and STOI have been used to evaluate the enhancement framework in different acoustic scenarios representative of the cocktail party scenario. We have also conducted subjective listening tests on a set of nine normal hearing subjects, to evaluate the performance in terms of intelligibility and quality improvement. The listening tests show that the proposed algorithm, even with access to only a single channel noisy observation, significantly improves the overall speech quality, and the speech intelligibility by up to 15%.