Beyond correlation: acoustic transformation methods for the experimental study of emotional voice and speech

Autor: Laura Rachman, Pablo Arias, Jean-Julien Aucouturier, Marco Liuni
Přispěvatelé: Sciences et Technologies de la Musique et du Son (STMS), Institut de Recherche et Coordination Acoustique/Musique (IRCAM)-Sorbonne Université (SU)-Centre National de la Recherche Scientifique (CNRS), Perception et design sonores (STMS-PDS), Institut de Recherche et Coordination Acoustique/Musique (IRCAM)-Sorbonne Université (SU)-Centre National de la Recherche Scientifique (CNRS)-Institut de Recherche et Coordination Acoustique/Musique (IRCAM)-Sorbonne Université (SU)-Centre National de la Recherche Scientifique (CNRS), Alta Voce SAS
Jazyk: angličtina
Rok vydání: 2020
Předmět:
Zdroj: Emotion Review
Emotion Review, 2020, ⟨10.1177/1754073920934544⟩
DOI: 10.1177/1754073920934544⟩
Popis: 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.
Databáze: OpenAIRE