Fast Subnetwork Selection for Speech Enhancement in Wireless Acoustic Sensor Networks

Instead of using the entire wireless acoustic sensor network (WASN), selecting the most informative subnetwork can achieve a good speech enhancement performance while keeping a low resource cost. In this paper, a fast subnetwork selection method is derived for the delay-and-sum beamformer, which is...

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Bibliographic Details
Published in2023 8th International Conference on Signal and Image Processing (ICSIP) pp. 900 - 904
Main Authors Hu, De, Wang, Xu, Liu, Rui, Bao, Feilong
Format Conference Proceeding
LanguageEnglish
Published IEEE 08.07.2023
Subjects
Acoustic sensors
beamformers
Costs
Energy consumption
Image processing
Speech enhancement
Subnetwork selection
wireless acoustic sensor network
Wireless communication
Wireless sensor networks
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Summary:Instead of using the entire wireless acoustic sensor network (WASN), selecting the most informative subnetwork can achieve a good speech enhancement performance while keeping a low resource cost. In this paper, a fast subnetwork selection method is derived for the delay-and-sum beamformer, which is also suitable for other existing speech enhancement algorithms. Inspired by the energy efficiency in wireless communication theory, the best subset of WASN is determined by maximizing a novel cost function that simultaneously considers the output signal-to-noise ratio (SNR) and the energy consumption. Then, a Dinkelbach-based solver is presented to obtain the optimal solution rapidly. Experimental results show that the proposed method achieves a better trade-off between performance and energy usage.
DOI:10.1109/ICSIP57908.2023.10271019