Research on a dual-element array sound source signal separation method based on compressed sensing theory

Dong Wan; Peilin Su; Qiang Kong

doi:10.1117/12.3034206

13 June 2024 Research on a dual-element array sound source signal separation method based on compressed sensing theory

Dong Wan, Peilin Su, Qiang Kong

Proceedings Volume 13180, International Conference on Image, Signal Processing, and Pattern Recognition (ISPP 2024); 131802Q (2024) https://doi.org/10.1117/12.3034206
Event: International Conference on Image, Signal Processing, and Pattern Recognition (ISPP 2024), 2024, Guangzhou, China

Abstract

Through bionic learning of the human auditory system, sound source signal separation methods have made great progress. However, it is still difficult to use low-element arrays for signal separation in complex environments. In order to solve this challenge, this paper proposes a dual-element array sound source signal separation method based on compressed sensing theory based on the time-frequency masking technology, sound level difference and sound source azimuth correspondence map and greedy algorithm to achieve different azimuth sound source signals. of separation. Through theoretical analysis and simulation experiments, the effectiveness, accuracy and robustness of the proposed method are verified, and new ideas and methods are provided for further development in the field of subsequent signal separation, which has certain theoretical and practical application value.

(2024) Published by SPIE. Downloading of the abstract is permitted for personal use only.

Citation Download Citation

Dong Wan, Peilin Su, and Qiang Kong "Research on a dual-element array sound source signal separation method based on compressed sensing theory", Proc. SPIE 13180, International Conference on Image, Signal Processing, and Pattern Recognition (ISPP 2024), 131802Q (13 June 2024); https://doi.org/10.1117/12.3034206

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