Publication | Closed Access
The ELISA consortium approaches in broadcast news speaker segmentation during the NIST 2003 rich transcription evaluation
50
Citations
7
References
2004
Year
Unknown Venue
Nist 2003EngineeringAutomatic Speaker SegmentationRich Transcription EvaluationElisa Consortium ActivitiesSpeech RecognitionNatural Language ProcessingPhoneticsSpeaker DiarizationRobust Speech RecognitionVoice RecognitionHealth SciencesElisa Consortium ApproachesElisa ConsortiumSpeech CommunicationSpeech TechnologySpeech AnalysisMulti-speaker Speech RecognitionSpeech ProcessingSpeech PerceptionSpeaker Recognition
The paper presents the ELISA consortium activities in automatic speaker segmentation, also known as speaker diarization, during the NIST rich transcription (RT), 2003, evaluation. The experiments were conducted on real broadcast news data (HUB4). Two different approaches from the CLIPS and LIA laboratories are presented and different possibilities of combining them are investigated, in the framework of the ELISA consortium. The system submitted as an ELISA primary system obtained the second lowest segmentation error rate compared to the other RT03-participant primary systems. Another ELISA system submitted as a secondary system outperformed the best primary system and obtained the lowest speaker segmentation error rate.
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