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Exploiting intra-conversation variability for speaker diarization
111
Citations
9
References
2011
Year
Unknown Venue
EngineeringHealth SciencesData ScienceCorpus LinguisticsMulti-speaker Speech RecognitionSpeaker DiarizationRobust Speech RecognitionSpeech ProcessingFactor AnalysisConversation AnalysisVoice RecognitionPrincipal Component AnalysisSpeech PerceptionLinguisticsSpeech CommunicationSpeaker RecognitionSpeech Recognition
In this paper, we propose a new approach to speaker diarization based on the Total Variability approach to speaker verification. Drawing on previous work done in applying factor analysis priors to the diarization problem, we arrive at a simplified approach that exploits intra-conversation variability in the Total Variability space through the use of Principal Component Analysis (PCA). Using our proposed methods, we demonstrate the ability to achieve state-of-the-art performance (0.9% DER) in the diarization of summed-channel telephone data from the NIST 2008 SRE. Index Terms: speaker diarization, factor analysis, Total Variability, principal component analysis
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