Automatic emotion recognition using prosodic parameters

@inproceedings{Luengo2005AutomaticER,
  title={Automatic emotion recognition using prosodic parameters},
  author={Iker Luengo and Eva Navas and Inma Hern{\'a}ez and Jon S{\'a}nchez},
  booktitle={INTERSPEECH},
  year={2005}
}
This paper presents the experiments made to automatically identify emotion in an emotional speech database for Basque. Three different classifiers have been built: one using spectral features and GMM, other with prosodic features and SVM and the last one with prosodic features and GMM. 86 prosodic features were calculated and then an algorithm to select the most relevant ones was applied. The first classifier gives the best result with a 98.4% accuracy when using 512 mixtures, but the… CONTINUE READING
Highly Cited
This paper has 105 citations. REVIEW CITATIONS

From This Paper

Figures, tables, and topics from this paper.

Citations

Publications citing this paper.
Showing 1-10 of 66 extracted citations

105 Citations

051015'08'11'14'17
Citations per Year
Semantic Scholar estimates that this publication has 105 citations based on the available data.

See our FAQ for additional information.

Similar Papers

Loading similar papers…