Impulsive Noise Detection for Intelligibility and Quality Improvement of Speech Enhancement Methods Applied in Time-Domain

TL;DR

This paper proposes a novel speech enhancement technique in the Hilbert-Huang Transform domain that effectively reduces impulsive noises, improving speech quality without sacrificing intelligibility, based on impulsiveness index-based noise component selection.

Contribution

It introduces a new method for impulsive noise mitigation in speech enhancement using Hilbert-Huang Transform and impulsiveness index, outperforming existing methods in quality metrics.

Findings

Achieves superior objective quality measures

Maintains similar speech intelligibility rates

Effective across various impulsive noises and SNR levels

Abstract

This letter introduces a novel speech enhancement method in the Hilbert-Huang Transform domain to mitigate the effects of acoustic impulsive noises. The estimation and selection of noise components is based on the impulsiveness index of decomposition modes. Speech enhancement experiments are conducted considering five acoustic noises with different impulsiveness index and non-stationarity degrees under various signal-to-noise ratios. Three speech enhancement algorithms are adopted as baseline in the evaluation analysis considering spectral and time domains. The proposed solution achieves the best results in terms of objective quality measures and similar speech intelligibility rates to the competitive methods.