Privacy-sensitive audio features for conversational speech processing
ACM SIGMultimedia Records（2012）
摘要
AbstractThe work described in this thesis takes place in the context of capturing real-life audio for the analysis of spontaneous social interactions. Towards this goal, we wish to capture conversational and ambient sounds using portable audio recorders. Analysis of conversations can then proceed by modeling the speaker turns and durations produced by speaker diarization. However, a key factor against the ubiquitous capture of real-life audio is privacy. Particularly, recording and storing raw audio would breach the privacy of people whose consent has not been explicitly obtained.
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关键词
raw audio,speaker turn,real-life audio,ubiquitous capture,speaker diarization,conversational speech processing,spontaneous social interaction,portable audio recorder,privacy-sensitive audio feature,key factor,speech recognition,social interaction,speech processing,residual,linear prediction
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