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In this presentation, Boom Hong from Northwestern Polytechnical University introduces the team's work on a challenge related to conversational speech recognition. The presentation consists of five parts, starting with a brief introduction to the challenges. The CSSD challenge focuses on recognizing short phrases crucial for semantic understanding in conversations. It utilizes an open-source dataset, RMC, which contains 118 hours of Mandarin Chinese conversational speech recorded via telephones at a 16k sampling rate. The challenge emphasizes the difficulty posed by frequent speaker changes, complicating delegation tasks. The methodology includes a directation system evaluated at the sentence level, highlighting the importance of short phrases.
