Detecting Group Turn Patterns in Conversations Using Audio-Video Change Scale-Space

Automatic analysis of conversations is important for extracting high-level descriptions of meetings. In this work, as an alternative to linguistic approaches, we develop a novel, purely bottom-up representation, constructed from both audio and video signals that help us characterize and build a rich...

Ausführliche Beschreibung

Bibliographische Detailangaben

Hauptverfasser:	Krishnan, RaviKiran, Sarkar, Sudeep
Format:	Tagungsbericht
Sprache:	eng
Schlagworte:	Bayesian methods Diamond-like carbon Meetings Mel frequency cepstral coefficient Principal component analysis Psychology Speech
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