AI Research
Transsion's Speaker-Attributed Multilingual ASR System for the MLC-SLM 2026 Challenge
Advancing multi-speaker transcription through an integrated cascaded framework for global languages.
This paper presents the Transsion Speech Team submission to Task 1 of the MLC-SLM 2026 Challenge, which focuses on speaker-attributed transcription for multilingual conversational speech. We propose a cascaded framework consisting of three components: a speaker diarization module...
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ArXiv CS.CL
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ArXiv CS.CL
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This research optimizes conversational AI by integrating speaker attribution with multilingual transcription in a unified framework. It represents a significant step toward making voice-based interfaces more accurate and usable for diverse, global populations.
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