Journal Article10.1007/S10772-018-9514-9
An efficient wavelet-based adaptive filtering algorithm for automatic blind speech enhancement
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TL;DR: The obtained results have confirmed the best performance of the proposed WBBSS algorithm in a lot of situations when blind noisy observations are available and it shows better performances in terms of convergence speed and steady state in comparison with the classical BBSS one.
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Abstract: In this paper, we address the problem of speech enhancement by adaptive filtering algorithms. A particular attention has been paid to the backward blind source separation (BBSS) algorithm and its use in crosstalk resistant speech enhancement applications. In this paper, we propose to implement the BBSS algorithm in the wavelet-domain. The proposed backward wavelet BBSS (WBBSS) algorithm is then used in speech enhancement application when important crosstalk interferences are presents. The new WBBSS algorithm shows better performances in terms of convergence speed and steady state in comparison with the classical BBSS one. The performances properties of the proposed algorithm are evaluated in term of segmental SNR (SegSNR), segmental mean square error (SegMSE), and cepstral distance (CD) criteria. The obtained results have confirmed the best performance of the proposed WBBSS algorithm in a lot of situations when blind noisy observations are available.
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Citations
Speech Enhancement Based on LWT and Artificial Neural Network and Using MMSE Estimate of Spectral Amplitude
Mourad Talbi,Riadh Baazaoui,Med Salim Bouhlel +2 more
- 29 Mar 2021
TL;DR: The performance of the proposed speech enhancement technique is justified by the computations of the Signal to Noise Ratio (SNR), Segmental SNR (SSNR) and Perceptual Evaluation of Speech Quality (PESQ).
MIMO beamforming system for speech enhancement in realistic environment with multiple noise sources
TL;DR: The performance of the proposed MIMO approach was validated under a realistic environment with real noise sources and the noise signals in the upper path are subtracted from the estimated noises in the lower path to recover an enhanced speech signal.
A new speech enhancement adaptive algorithm based on fullband–subband MSE switching
TL;DR: A new fullband–subband switching adaptive speech enhancement algorithm, based on mean square error estimation, able to automatically switch between two adaptive filtering algorithms, where, the proposed switching mechanism leads to a significant improvement in the convergence speed performance of the proposed algorithm.
Application of Intelligent Speech Recognition Technology Based on Wavelet Algorithm in Chinese Oral Teaching
Jingsheng Zhai,Zhidan Zhou,Lei Zhao +2 more
- 27 Feb 2024
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•Journal Article
Speech enhancement using a minimum mean square error short-time spectral amplitude estimator
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