A modular two-speaker ASR pipeline combining DiariZen diarization and DiCoW target-speaker Whisper achieves 16.75% micro-average tcpWER/CER and second place in the MLC-SLM challenge Task 2.
These models achieve remarkable accuracy by leveraging mas- sive training data [7, 8] and scaling up model parameters [9]
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BUT System for the MLC-SLM Challenge
A modular two-speaker ASR pipeline combining DiariZen diarization and DiCoW target-speaker Whisper achieves 16.75% micro-average tcpWER/CER and second place in the MLC-SLM challenge Task 2.