Papers with speaker classification

2 papers
Towards Neural Speaker Modeling in Multi-Party Conversation: The Task, Dataset, and Models (L18-1)

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Challenge: Existing methods for speaker modeling are based on hand-crafted statistics and ad hoc to a certain application.
Approach: They propose to use speaker classification as a surrogate task for general speaker modeling and collect massive data to facilitate research in this direction.
Outcome: The proposed models outperform the existing models and are feasible with speaker identity information.
TellWhisper: Tell Whisper Who Speaks When (2026.acl-long)

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Challenge: Existing approaches decouple temporal modeling and speaker modeling when addressing 'when' and 'who' . a new framework that couples temporal structure with speaker dynamics is proposed to address these limitations .
Approach: They propose a framework that couples temporal and speaker identity within the speech encoder . they propose TS-RoPE, a time-speaker rotary positional encoding that partitions Query/Key channels into temporal, speaker subspaces and applies region-specific rotations to align "when" and "who" cues in selfattention.
Outcome: The proposed framework couples temporal structure with speaker dynamics in speech encoder . it uses frame-level speaker activity to estimate speaker-activity estimates .

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