Reconocimiento automático de emociones utilizando parámetros prosódicos

1. Luengo Gil, Iker
2. Navas Cordón, Eva
3. Hernáez Rioja, Inmaculada
4. Sánchez de la Fuente, Jon

Esportatu

Esportatu

×

MLA

modern-language-association

APA

apa

Chicago

chicago-fullnote-bibliography

Harvard

harvard-cite-them-right

Vancouver

vancouver-author-date

---

RIS BibTex

Esportatu

×

Dokumentua ezin da beste atari batetik esportatu.

Testu osoa

lock_openRUA externo

DIALNET GOOGLE SCHOLAR lock_openRUA editor

Beste argitalpen batzuk: Procesamiento del lenguaje natural

Laburpena

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 classifier built with the best 6 prosodic features achieves an accuracy of 92.3% in spite of its simplicity, showing that prosodic information is very useful to identify emotions

Datuen iturria: Dialnet