A single-channel speech enhancement method for fiber microphones integrating OMLSA and TQWT

By combining OMLSA and TQWT to develop a single-channel speech enhancement method for fiber optic microphones, the noise suppression problem of fiber optic microphones in low signal-to-noise ratio environments is solved, and efficient enhancement of speech signals and quality fidelity are achieved.

CN119785808BActive Publication Date: 2025-09-16CHINA THREE GORGES UNIV
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Patent Information

Application Number
CN202411871991.0
Authority / Receiving Office
CN · China
Patent Type
Patents(China)
Current Assignee / Owner
Filing Date
2024-12-18
Publication Date
2025-09-16
Estimated Expiration
2044-12-18

AI Technical Summary

Technical Problem

The existing single-channel speech enhancement algorithm has poor noise suppression effect in fiber optic microphone applications, especially in low signal-to-noise ratio conditions where there is a lot of residual noise. In addition, improper TQWT parameter settings affect the enhancement effect and make it difficult to effectively suppress low-frequency noise.

Method used

The method of fusing OMLSA and TQWT is adopted. After preliminary enhancement by the OMLSA algorithm, the segmented signal-to-noise ratio is used to determine whether further TQWT processing is needed. The TQWT parameters are optimized with the basis pursuit sparsification technology to achieve efficient enhancement of the speech signal.

Benefits of technology

Under the premise of ensuring voice quality, it effectively reduces residual noise, improves the signal-to-noise ratio, saves computing resources, and achieves efficient enhancement of the fiber optic microphone signal.

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Abstract

A single-channel speech enhancement method for a fiber optic microphone that integrates OMLSA and TQWT is proposed. The collected speech signal is first framed, and OMLSA speech enhancement is performed on each frame. The segmented signal-to-noise ratio is used as a judgment criterion to determine whether TQWT is needed to remove residual noise. The reconstruction error is used to select the optimal values ​​of the parameters Q factor and redundancy r required for TQWT decomposition to ensure that the most suitable set of wavelet coefficients is obtained for the decomposition of the speech signal. A threshold is adaptively selected based on each wavelet coefficient, and the wavelet coefficients are sparsed using basis pursuit. The final enhanced speech signal is reconstructed through the sparse wavelet coefficients. Compared with denoising using only OMLSA, the method of the present invention can further effectively suppress residual noise on this basis, thereby improving the speech enhancement effect.
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