Evidence map›Paper›PMID 28374144›Full record

ArticleBehavior research methods2018

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

Laura Rachman, Marco Liuni, Pablo Arias, Andreas Lind, Petter Johansson, Lars Hall, Daniel Richardson, Katsumi Watanabe, Stéphanie Dubal, Jean-Julien Aucouturier

Abstract read
In one paragraph

Article in Behavior research methods, 2018. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 15 papers.

0numbers the graph read from it
0cells of the map it votes in
15citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

15 citing papers in PubMed.

  1. Article
  2. Aligning the smiles of dating dyads causally increases attraction.Proceedings of the National Academy of Sciences of the United States of America · 2024
    Article
  3. Article
  4. The Emerging Science of Interacting Minds.Perspectives on psychological science : a journal of the Association for Psychological Science · 2024
    Article
  5. Article
  6. Article
  7. Article
  8. The shallow of your smile: the ethics of expressive vocal deep-fakes.Philosophical transactions of the Royal Society of London. Series B, Biological sciences · 2022
    Article
  9. Even violins can cry: specifically vocal emotional behaviours also drive the perception of emotions in non-vocal music.Philosophical transactions of the Royal Society of London. Series B, Biological sciences · 2021
    Article
  10. Article
  11. Review
  12. Article
  13. Article
  14. Article
  15. Article
4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

10 authors.

Laura RachmanScience & Technology of Music and Sound (STMS), UMR 9912 (CNRS/IRCAM/UPMC), 1 place Stravinsky, 75004, Paris, France. rachman.laura@gmail.com.
Marco LiuniScience & Technology of Music and Sound (STMS), UMR 9912 (CNRS/IRCAM/UPMC), 1 place Stravinsky, 75004, Paris, France.
Pablo AriasScience & Technology of Music and Sound (STMS), UMR 9912 (CNRS/IRCAM/UPMC), 1 place Stravinsky, 75004, Paris, France.
Andreas LindLund University Cognitive Science, Lund University, Lund, Sweden.
Petter JohanssonLund University Cognitive Science, Lund University, Lund, Sweden.
Lars HallLund University Cognitive Science, Lund University, Lund, Sweden.
Daniel RichardsonDepartment of Experimental Psychology, University College London, London, UK.
Katsumi WatanabeDepartment of Intermedia Art and Science, Faculty of Science and Engineering, Waseda University, Tokyo, Japan.
Stéphanie DubalInserm U 1127, CNRS UMR 7225, Sorbonne Universités UPMC Univ Paris 06 UMR S 1127, Institut du Cerveau et de la Moelle épinière (ICM), Social and Affective Neuroscience (SAN) Laboratory, Paris, France.
Jean-Julien AucouturierScience & Technology of Music and Sound (STMS), UMR 9912 (CNRS/IRCAM/UPMC), 1 place Stravinsky, 75004, Paris, France.

Funding

European Research Council 335536
6 · The paper itself

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.

Indexed as

CuesEmotionsInterpersonal RelationsSpeechVerbal BehaviorComputer SimulationFemaleHumansLanguageMaleNonverbal CommunicationSpeech PerceptionEmotional transformationsInfra-segmental cuesNonverbal behaviorReal-timeSoftwareVoice

Identifiers

PMID28374144
PMCPMC5809549

What OpenQuestion holds

Textmetadata
LicenceCC BY
Read underepoch 390

Registered trials

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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.