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Learning Speaker-Activity-Conditioned WavLM Speaker Embeddings with Real Conversational Data
End-to-end neural diarization with vector clustering (EEND-VC) is a strong framework for long-form conversational diarization, where speaker embeddings are used to link local speaker decisions across windows. Conventional EEND-VC systems extract these embeddings by cutting out regions assigned to ea
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