Speech-based Emotion Recognition and Speaker Identiﬁcation: Static vs. Dynamic Mode of Speech Representation
In this paper we present the performance of diﬀerent machine learning algorithms for the problems of speech-based Emotion Recognition (ER) and Speaker Identiﬁcation (SI) in static and dynamic modes of speech signal representation. We have used a multi-corporal, multi-language approach in the study. 3 databases for the problem of SI and 4 databases for the ER task of 3 diﬀerent languages (German, EnglishandJapanese)havebeenusedinourstudyto evaluatethemodels.Morethan45 machinelearning algorithms were applied to these tasks in both modes and the results alongside discussion are presented here.