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DASHA: Diarization-Aware Speech-LLM ASR for Healthcare in Code-Switched Indic Doctor-Patient Conversations
Extracting patients' medical conditions from recorded primary-care conversations requires knowing who said what, which is difficult when speech is far-field, spontaneous, overlapping and code-switched. We study this problem on DISPLACE-M, a corpus of Hindi--English (Hinglish) doctor--patient convers
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