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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Vydáno v:Behavior research methods Ročník 50; číslo 1; s. 323 - 343
Hlavní autoři: Rachman, Laura, Liuni, Marco, Arias, Pablo, Lind, Andreas, Johansson, Petter, Hall, Lars, Richardson, Daniel, Watanabe, Katsumi, Dubal, Stéphanie, Aucouturier, Jean-Julien
Médium: Journal Article
Jazyk:angličtina
Vydáno: New York Springer US 01.02.2018
Springer Nature B.V
Psychonomic Society, Inc
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ISSN:1554-3528, 1554-351X, 1554-3528
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Abstract 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.
AbstractList 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.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.
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.
Author Hall, Lars
Lind, Andreas
Liuni, Marco
Johansson, Petter
Dubal, Stéphanie
Aucouturier, Jean-Julien
Watanabe, Katsumi
Richardson, Daniel
Rachman, Laura
Arias, Pablo
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Issue 1
Keywords Emotional transformations
Infra-segmental cues
Software
Voice
Real-time
Nonverbal behavior
Language English
License Distributed under a Creative Commons Attribution 4.0 International License: http://creativecommons.org/licenses/by/4.0
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Snippet We present an open-source software platform that transforms emotional cues expressed by speech signals using audio effects like pitch shifting, inflection,...
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StartPage 323
SubjectTerms 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
Title DAVID: An open-source platform for real-time transformation of infra-segmental emotional cues in running speech
URI https://link.springer.com/article/10.3758/s13428-017-0873-y
https://www.ncbi.nlm.nih.gov/pubmed/28374144
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https://www.proquest.com/docview/1884168353
https://hal.science/hal-01450511
https://pubmed.ncbi.nlm.nih.gov/PMC5809549
Volume 50
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