The relevance of feature type for the automatic classification of emotional user states: Low level descriptors and functionals

Björn Schuller, Anton Batliner, Dino Seppi, Stefan Steidl, Thurid Vogt, Johannes Wagner, Laurence Devillers, Laurence Vidrascu, Noam Amir, Loic Kessous, Vered Aharonson

Research output: Chapter in Book/Report/Conference proceedingConference contributionpeer-review

29 Scopus citations

Abstract

In this paper, we report on classification results for emotional user states (4 classes, German database of children interacting with a pet robot). Six sites computed acoustic and linguistic features independently from each other, following in part different strategies. A total of 4244 features were pooled together and grouped into 12 low level descriptor types and 6 functional types. For each of these groups, classification results using Support Vector Machines and Random Forests are reported for the full set of features, and for 150 features each with the highest individual Information Gain Ratio. The performance for the different groups varies mostly between ≈ 50% and ≈ 60%.

Original languageEnglish
Title of host publicationInternational Speech Communication Association - 8th Annual Conference of the International Speech Communication Association, Interspeech 2007
PublisherUnavailable
Pages881-884
Number of pages4
ISBN (Print)9781605603162
StatePublished - 2007
Event8th Annual Conference of the International Speech Communication Association, Interspeech 2007 - Antwerp, Belgium
Duration: 27 Aug 200731 Aug 2007

Publication series

NameInternational Speech Communication Association - 8th Annual Conference of the International Speech Communication Association, Interspeech 2007
Volume2
ISSN (Electronic)1990-9772

Conference

Conference8th Annual Conference of the International Speech Communication Association, Interspeech 2007
Country/TerritoryBelgium
CityAntwerp
Period27/08/0731/08/07

Keywords

  • Automatic classification
  • Emotional user states
  • Feature types
  • Functionals

Fingerprint

Dive into the research topics of 'The relevance of feature type for the automatic classification of emotional user states: Low level descriptors and functionals'. Together they form a unique fingerprint.

Cite this