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This paper describes our audio-quality-based multi-strategy approach for theaudio-visual target speaker extraction (AVTSE) task in the Multi-modalInformation based Speech Processing (MISP) 2023 Challenge. Specifically, ourapproach adopts different extraction strategies based on the audio quality,striking a balance between interference removal and speech preservation, whichbenifits the back-end automatic speech recognition (ASR) systems. Experimentsshow that our approach achieves a character error rate (CER) of 24.2% and 33.2%on the Dev and Eval set, respectively, obtaining the second place in thechallenge.

An audio-quality-based multi-strategy approach for target speaker extraction in the MISP 2023 Challenge