JOURNAL ARTICLE

Adaptation mode control with residual noise estimation for beamformer-based multi-channel speech enhancement

Abstract

In this paper, we propose a new adaptation mode controller (AMC) for a generalized sidelobe canceller (GSC) having prior knowledge of the direction-of-arrival (DOA) of a desired speech source. In order to optimize the adaptation mode of a GSC, the residual noise remaining in the GSC output must be employed for adapting the AMC. The residual noise in the GSC output is estimated by using a short-time Fourier transform (STFT)-based Wiener filter, where a priori signal-to-noise ratio (SNR) and a posteriori target-to-non-target-directional signal ratio (TNR) are estimated based on a decision-directed approach and a DOA-based approach, respectively. The estimated residual noise is finally incorporated as a control parameter into the adaptive filters in the AMC. The performance of the proposed AMC is evaluated by measuring the perceptual evaluation of speech quality (PESQ) scores and cepstral distortion in car noise environments with SNRs from 0 to 20 dB. Experimental results show that the proposed AMC performs better than the conventional AMCs.

Keywords:
PESQ Computer science Speech recognition Residual Speech enhancement Wiener filter Noise (video) Signal-to-noise ratio (imaging) A priori and a posteriori Noise reduction Artificial intelligence Algorithm Telecommunications

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FWCI (Field Weighted Citation Impact)
15
Refs
0.19
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Topics

Speech and Audio Processing
Physical Sciences →  Computer Science →  Signal Processing
Advanced Adaptive Filtering Techniques
Physical Sciences →  Engineering →  Computational Mechanics
Acoustic Wave Phenomena Research
Physical Sciences →  Engineering →  Biomedical Engineering

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