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arXiv · 2409.05034

TF-Mamba: A Time-Frequency Network for Sound Source Localization

Yang Xiao·Rohan Kumar Das
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Abstract

Sound source localization (SSL) determines the position of sound sources using multi-channel audio data. It is commonly used to improve speech enhancement and separation. Extracting spatial features is crucial for SSL, especially in challenging acoustic environments. Recently, a novel structure referred to as Mamba demonstrated notable performance across various sequence-based modalities. This study introduces the Mamba for SSL tasks. We consider the Mamba-based model to analyze spatial features from speech signals by fusing both time and frequency features, and we develop an SSL system called TF-Mamba. This system integrates time and frequency fusion, with Bidirectional Mamba managing both time-wise and frequency-wise processing. We conduct the experiments on the simulated and real datasets. Experiments show that TF-Mamba significantly outperforms other advanced methods. The code will be publicly released in due course.

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Yang Xiao, Rohan Kumar Das. 2025-05-20. TF-Mamba: A Time-Frequency Network for Sound Source Localization. https://arxiv.org/abs/2409.05034

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