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Advances in Human-Computer Interaction
Volume 2010, Article ID 782802, 15 pages
Research Article

Segmenting into Adequate Units for Automatic Recognition of Emotion-Related Episodes: A Speech-Based Approach

1Pattern Recognition Laboratory, Friedrich-Alexander-Universität Erlangen-Nürnberg (FAU), D-91058 Erlangen, Germany
2ESAT, Katholieke Universiteit Leuven, B-3001 Leuven, Belgium
3Institute for Human-Machine Communication, Technische Universität München (TUM), D-80333 Munich, Germany

Received 1 April 2009; Accepted 12 December 2009

Academic Editor: Elisabeth Andre

Copyright © 2010 Anton Batliner et al. This is an open access article distributed under the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.


We deal with the topic of segmenting emotion-related (emotional/affective) episodes into adequate units for analysis and automatic processing/classification—a topic that has not been addressed adequately so far. We concentrate on speech and illustrate promising approaches by using a database with children's emotional speech. We argue in favour of the word as basic unit and map sequences of words on both syntactic and ‘‘emotionally consistent” chunks and report classification performances for an exhaustive modelling of our data by mapping word-based paralinguistic emotion labels onto three classes representing valence (positive, neutral, negative), and onto a fourth rest (garbage) class.