Work

Beyond Correlation: Acoustic Transformation Methods for the Experimental Study of Emotional Voice and Speech

Year: 2020

Type: article

Abstract: While acoustic analysis methods have become a commodity in voice emotion research, experiments that attempt not only to describe but to computationally manipulate expressive cues in emotional voice and speech have remained relatively rare. We give here a nontechnical overview of voice-transformation techniques from the audio signal-processing community that we believe are ripe for adoption in this context. We provide sound examples of what they can achieve, examples of experimental questions for which they can be used, and links to open-source implementations. We point at a number of methodological properties of these algorithms, such as being specific, parametric, exhaustive, and real-time, and describe the new possibilities that these open for the experimental study of the emotional voice.

Source: Emotion Review

DOI: 10.1177/1754073920934544

Authors: Pablo Arias, Laura Rachman, Marco Liuni, Jean-Julien Aucouturier

Institutions: Centre National de la Recherche Scientifique, Institut de Recherche et Coordination Acoustique Musique, Sorbonne Université, Sciences et Technologies de la Musique et du Son

Language: English

Topic: Emotion and Mood Recognition

Subfield: Experimental and Cognitive Psychology

Field: Psychology

Domain: Social Sciences

Open Access status: green

Funders: Agence Nationale de la Recherche, H2020 European Research Council

Award: G8995048360