DAVID: An open-source platform for real-time transformation of infra-segmental emotional cues in running speech

We present an open-source software platform that transforms emotional cues expressed by speech signals using audio effects like pitch shifting, inflection, vibrato, and filtering. The emotional transformations can be applied to any audio file, but can also run in real time, using live input from a m...

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Veröffentlicht in:Behavior research methods Jg. 50; H. 1; S. 323 - 343
Hauptverfasser: Rachman, Laura, Liuni, Marco, Arias, Pablo, Lind, Andreas, Johansson, Petter, Hall, Lars, Richardson, Daniel, Watanabe, Katsumi, Dubal, Stéphanie, Aucouturier, Jean-Julien
Format: Journal Article
Sprache:Englisch
Veröffentlicht: New York Springer US 01.02.2018
Springer Nature B.V
Psychonomic Society, Inc
Schlagworte:
Behavioral Science and Psychology
Cognitive Psychology
Cognitive science
Comparative Language Studies and Linguistics
Computer and Information Sciences
Computer Science
Computer Simulation
Cues
Data- och informationsvetenskap (Datateknik)
Emotions
Experiments
Female
Frequency
Human Computer Interaction
Humaniora och konst
Humanities and the Arts
Humans
Interpersonal Relations
Intonation
Jämförande språkvetenskap och allmän lingvistik
Language
Languages
Languages and Literature
Latency
Male
Människa-datorinteraktion (Interaktionsdesign)
Natural Sciences
Naturalness
Naturvetenskap
Nervous system
Nonverbal Communication - psychology
Pitch
Psychology
Real time
Social situations
Software
Sound
Speech
Speech Perception
Språk och litteratur
Transformation
Verbal Behavior
Emotional transformations
Infra-segmental cues
Software
Voice
Real-time
Nonverbal behavior
ISSN:1554-3528, 1554-351X, 1554-3528
Online-Zugang:Volltext
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Beschreibung
Zusammenfassung:We present an open-source software platform that transforms emotional cues expressed by speech signals using audio effects like pitch shifting, inflection, vibrato, and filtering. The emotional transformations can be applied to any audio file, but can also run in real time, using live input from a microphone, with less than 20-ms latency. We anticipate that this tool will be useful for the study of emotions in psychology and neuroscience, because it enables a high level of control over the acoustical and emotional content of experimental stimuli in a variety of laboratory situations, including real-time social situations. We present here results of a series of validation experiments aiming to position the tool against several methodological requirements: that transformed emotions be recognized at above-chance levels, valid in several languages (French, English, Swedish, and Japanese) and with a naturalness comparable to natural speech.
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SourceType-Scholarly Journals-1
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ISSN:1554-3528
1554-351X
1554-3528
DOI:10.3758/s13428-017-0873-y