Speaker-Reasoner: Scaling Interaction Turns and Reasoning Patterns for Timestamped Speaker-Attributed ASR

• URL: http://arxiv.org/abs/2604.03074v1
• Date: Fri, 03 Apr 2026 14:52:20 GMT
• Title: Speaker-Reasoner: Scaling Interaction Turns and Reasoning Patterns for Timestamped Speaker-Attributed ASR
• Abstract summary: Speaker-Reasoner is an end-to-end Speech LLM with agentic multi-turn temporal reasoning.<n>Speaker-Reasoner achieves consistent improvements over strong baselines on AliMeeting and AISHELL-4 datasets.
• Score: 18.90091826363701
• License: http://arxiv.org/licenses/nonexclusive-distrib/1.0/
• Abstract: Transcribing and understanding multi-speaker conversations requires speech recognition, speaker attribution, and timestamp localization. While speech LLMs excel at single-speaker tasks, multi-speaker scenarios remain challenging due to overlapping speech, backchannels, rapid turn-taking, and context window constraints. We propose Speaker-Reasoner, an end-to-end Speech LLM with agentic multi-turn temporal reasoning. Instead of single-pass inference, the model iteratively analyzes global audio structure, autonomously predicts temporal boundaries, and performs fine-grained segment analysis, jointly modeling speaker identity, gender, timestamps, and transcription. A speaker-aware cache further extends processing to audio exceeding the training context window. Trained with a three-stage progressive strategy, Speaker-Reasoner achieves consistent improvements over strong baselines on AliMeeting and AISHELL-4 datasets, particularly in handling overlapping speech and complex turn-taking.

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