In this paper, we present a database of emotional speech intended to be open-sourced and used for synthesis and generation purpose. It contains data for male and female actors in English and a male actor in French. The database covers 5 emotion classes so it could be suitable to build synthesis and voice transformation systems with the potential to control the emotional dimension in a continuous way. We show the data's efficiency by building a simple MLP system converting neutral to angry speech style and evaluate it via a CMOS perception test. Even though the system is a very simple one, the test show the efficiency of the data which is promising for future work.
Also similar to the previous ones, the GEMEP database @cite_7 is a collection of 10 French-speaking actors, recorded uttering 15 different emotional expressions at three levels of intensity, in three different ways: improvised sentences, pseudo-speech, and nonverbal affect bursts. This database counts a total of 1260 audio files. It was also validated through perception tests.
@cite_7
2329093554
Research on the perception of emotional expressions in faces and voices is exploding in psychology, the neurosciences, and affective computing. This article provides an overview of some of the major emotion expression (EE) corpora currently available for empirical research and introduces a new, dynamic, multimodal corpus of emotion expressions, the Geneva Multimodal Emotion Portrayals Core Set (GEMEP-CS). The design features of the corpus are outlined and justified, and detailed validation data for the core set selection are presented and discussed. Finally, an associated database with microcoded facial, vocal, and body action elements, as well as observer ratings, is introduced.