Computer-assisted Speaker Diarization: How to Evaluate Human Corrections
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Active LearningFace RecognitionOptical Character Recognition (OCR)speaker-diarizationSpeaker DiarizationSpeaker IdentificationSpeaker RecognitionSimilar Papers 제목 키워드 기반
Self-supervised learning for audio-visual speaker diarization
Speaker diarization, which is to find the speech segments of specific speakers, has been widely used in human-centered applications such as video conferences or human-computer interaction systems. In this paper, we propo…
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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-meet…
Towards Measuring and Scoring Speaker Diarization Fairness
Speaker diarization, or the task of finding "who spoke and when", is now used in almost every speech processing application. Nevertheless, its fairness has not yet been evaluated because there was no protocol to study it…
FairnessSentencespeaker-diarizationSpeaker DiarizationSpeaker Diarization with Lexical Information
This work presents a novel approach for speaker diarization to leverage lexical information provided by automatic speech recognition. We propose a speaker diarization system that can incorporate word-level speaker turn p…
Automatic Speech RecognitionAutomatic Speech Recognition (ASR)Clusteringspeaker-diarization+3Neural Speaker Diarization with Speaker-Wise Chain Rule
Speaker diarization is an essential step for processing multi-speaker audio. Although an end-to-end neural diarization (EEND) method achieved state-of-the-art performance, it is limited to a fixed number of speakers. In …
speaker-diarizationSpeaker Diarization