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Simulating realistic speech overlaps improves multi-talker ASR

By Muqiao Yang and others
Multi-talker automatic speech recognition (ASR) has been studied to generate transcriptions of natural conversation including overlapping speech of multiple speakers. Due to the difficulty in acquiring real conversation data with high-quality human transcriptions, a na\"ive simulation of multi-talker speech by randomly mixing multiple utterances was conventionally used for model training.... Show more
November 17, 2022
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Simulating realistic speech overlaps improves multi-talker ASR
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