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arXiv · 2307.15400

The FlySpeech Audio-Visual Speaker Diarization System for MISP Challenge 2022

Li Zhang·Huan Zhao·Yue Li·Bowen Pang·Yannan Wang·Hongji Wang·Wei Rao·Qing Wang·Lei Xie
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Abstract

This paper describes the FlySpeech speaker diarization system submitted to the second \textbf{M}ultimodal \textbf{I}nformation Based \textbf{S}peech \textbf{P}rocessing~(\textbf{MISP}) Challenge held in ICASSP 2022. We develop an end-to-end audio-visual speaker diarization~(AVSD) system, which consists of a lip encoder, a speaker encoder, and an audio-visual decoder. Specifically, to mitigate the degradation of diarization performance caused by separate training, we jointly train the speaker encoder and the audio-visual decoder. In addition, we leverage the large-data pretrained speaker extractor to initialize the speaker encoder.

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Li Zhang, Huan Zhao, Yue Li, Bowen Pang, Yannan Wang, Hongji Wang, Wei Rao, Qing Wang, Lei Xie. 2023-07-28. The FlySpeech Audio-Visual Speaker Diarization System for MISP Challenge 2022. https://arxiv.org/abs/2307.15400

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