  This paper describes our audio-quality-based multi-strategy approach for the
audio-visual target speaker extraction (AVTSE) task in the Multi-modal
Information based Speech Processing (MISP) 2023 Challenge. Specifically, our
approach adopts different extraction strategies based on the audio quality,
striking a balance between interference removal and speech preservation, which
benifits the back-end automatic speech recognition (ASR) systems. Experiments
show 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 the
challenge.
