ELISA Nist RT03 Broadcast News Speaker Diarization Experiments
作者： Daniel Moraru , Sylvain Meignier , Corinne Fredouille , Laurent Besacier , Jean-François Bonastre
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摘要: This paper presents the ELISA consortium activities in automatic speaker diarization (also known as segmentation) during NIST Rich Transcription (RT) 2003 evaluation. The experiments were achieved on real broadcast news data (HUB4), framework of consortium. firstly shows interest segmentation acoustic macro classes (like gender or bandwidth) a front-end processing for segmentation/diarization task. impact this prior is evaluated terms performance. Secondly, two different approaches from CLIPS and LIA laboratories are presented possibilities combining them investigated. system submitted primary obtained second lower error rate compared to other RT03-participant systems. Another secondary outperformed best (i.e. it lowest rate).
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