Automatic classification of emotions via global and local prosodic features on a multilingual emotional database
Antonio Origlia, Natural Language Processing Group, Department of Physical Sciences, “Federico II” University, Naples, Italy
Vincenzo Galatà, Laboratory of Phonetics, Department of Linguistics, University of Calabria, Italy
Bogdan Ludusan, Natural Language Processing Group, Department of Physical Sciences, “Federico II” University, Naples, Italy
In this paper we introduce the €motion database, a multilingual emotional database consisting of emotional sentences elicited in four European languages: Italian, French, English and German. Along with this, a new set of features, containing both global and local prosodic features, for automatic classification of emotions is presented and their appropriateness for this task tested. The results obtained on a monolingual emotional database are comparable with the state of the art results previously obtained.