ISCA Archive Interspeech 2005
ISCA Archive Interspeech 2005

Low-dimensional feature space derivation for emotion recognition

Jaroslaw Cichosz, Krzysztof Slot

An objective of the paper was to determine a set of low-dimensional feature spaces that provide high emotion recognition rates. Candidates for target feature spaces were randomly drawn from a broad pool of speech signal parameters that comprised both commonly used characteristics and newly introduced features. As a result, several four-dimensional feature spaces that provide the highest emotion classification rates (68%) on Polish language database, which we used in experiments, were identified.

doi: 10.21437/Interspeech.2005-320

Cite as: Cichosz, J., Slot, K. (2005) Low-dimensional feature space derivation for emotion recognition. Proc. Interspeech 2005, 477-480, doi: 10.21437/Interspeech.2005-320

  author={Jaroslaw Cichosz and Krzysztof Slot},
  title={{Low-dimensional feature space derivation for emotion recognition}},
  booktitle={Proc. Interspeech 2005},