Impulsive Noise Detection for Intelligibility and Quality Improvement of Speech Enhancement Methods Applied in Time-Domain
This work addresses speech enhancement for noisy environments, but it is incremental as it builds on existing methods with a specific domain focus.
The paper tackled the problem of acoustic impulsive noise in speech enhancement by introducing a method in the Hilbert-Huang Transform domain, achieving the best results in objective quality measures and similar intelligibility rates to competitive methods.
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.