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A Verbal Interaction Measure Using Acoustic Signal Correlation for Dyadic Cooperation Support

Part of the Advances in Intelligent Systems and Computing book series (AISC, volume 219)

Abstract

We introduce a method for detecting whether two users are engaged in focused interaction using a windowed correlation measure on their acoustic signals, assuming that a continued exchange of verbal turns contributes to anticorrelation of acoustic activity. We tested our method with manually annotated transitions between focused and unfocused interaction stemming from experiments on AR-based cooperation within a research project on alignment in communication. The results show that a high degree and extended duration of speech activity anticorrelation reliably indicates focused interaction, and might thus be a valuable asset for situation-aware technical systems.

Keywords

situation awareness collaboration speech activity data mining multiscale analysis correlation 

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Copyright information

© Springer International Publishing Switzerland 2013

Authors and Affiliations

  1. 1.Bielefeld UniversityBielefeldGermany

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