Speaker change detection with privacy-preserving audio cues

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Speaker change detection with privacy-preserving audio cues
In this paper we investigate a set of privacy-sensitive audio features for speaker change detection (SCD) in multiparty conversations. These features are based on three different principles: characterizing the excitation source information using linear prediction residual, characterizing subband spectral information shown to contain speaker information, and characterizing the general shape of the spectrum. Experiments show that the performance of the privacy-sensitive features is comparable or better than that of the state-of-theart full-band spectral-based features, namely, mel frequency cepstral coefficients, which suggests that socially acceptable ways of recording conversations in real-life is feasible. Categories and Subject Descriptors H.3.1 [Information Storage and Retrieval]: Content Analysis and Indexing General Terms Human Factors Keywords Modeling social interactions, Multiparty conversations, Speaker change detection, Privacy-sensitive features
Sree Hari Krishnan Parthasarathi, Mathew Magimai-D
Added 26 May 2010
Updated 26 May 2010
Type Conference
Year 2009
Where ICMI
Authors Sree Hari Krishnan Parthasarathi, Mathew Magimai-Doss, Daniel Gatica-Perez, Hervé Bourlard
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