Interactive In-Meeting Speaker Correction with Human Feedback 事件

Interactive In-Meeting Speaker Correction with Human Feedback arXiv:2509.18377v2 Announce Type: replace Abstract: Most automatic speech processing systems operate in ``open loop'' mode without user feedback about who said what, yet human-in-the-loop workflows can potentially enable higher accuracy. We propose an LLM-assisted in-meeting speaker correction system that lets users fix speaker attribution errors through brief corrective feedback. After performing streaming ASR and diarization, the s