Papers

Enhanced Deep Speech Separation in Clustered Ad Hoc Distributed Microphone Environments

International Conference
작성자
이지현
작성일
2024-06-13 11:23
조회
94
Authors : Jihyun Kim, Stijn Kindt, Nilesh Madhu, Hong-Goo Kang

Year : 2024

Publisher / Conference : INTERSPEECH

Research area : Speech Signal Processing, Source Separation

Presentation : Poster

Ad-hoc distributed microphone environments, where microphone locations and numbers are unpredictable, present a challenge to traditional deep learning models, which typically require fixed architectures. To tailor deep learning models to accommodate arbitrary array configurations, the Transform-Average-Concatenate (TAC) layer was previously introduced. In this work, we integrate TAC layers with dual-path transformers for speech separation from two simultaneous talkers in realistic settings. However, the distributed nature makes it hard to fuse information across microphones efficiently. Therefore, we explore the efficacy of blindly clustering microphones around sources of interest prior to enhancement. Experimental results show that this deep cluster-informed approach significantly improves the system’s capacity to cope with the inherent variability observed in ad-hoc distributed microphone environments.
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