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Telling self-defining memories: An acoustic study of natural emotional speech productions
Delvaux, Véronique; Lavallée, Audrey; Degouis, Fanny et al.
2022In Proceedings of the Annual Conference of the International Speech Communication Association, INTERSPEECH, 2022-September, p. 1337 - 1341
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Keywords :
autobiographical memory; emotion encoding; emotion regulation; emotions; self-defining memories; speech production; Acoustic parameters; Autobiographical memory; Emotion; Emotion encoding; Emotion regulations; Emotional speech; Encodings; Load regulations; Self-defining memory; Speech production; Language and Linguistics; Human-Computer Interaction; Signal Processing; Software; Modeling and Simulation
Abstract :
[en] Vocal cues in emotion encoding are rarely studied based on real-life, naturalistic emotional speech. In the present study, 20 speakers (10 male, 10 female) aged 25 to 35 were recorded while orally telling 5 successive self-defining autobiographic memories (SDM). By definition, this task is highly emotional, although emotional load and emotion regulation are expected to vary across SDM. Seven acoustic parameters were extracted: MeanF0, MedianFo, StandardDeviationF0, MinF0, MaxF0, Duration and SpeechRate. All SDM were manually transcribed, then their emotional lexicon was analysed using Emotaix. First, speech productions were examined in reference with SDM characteristics (specificity, integrative meaning and affective valence) as determined by 3 independent investigators. Results showed that overall the speech parameters did not change over the time course of the experiment, or as a function of integrative meaning. Specific memories were recounted at a higher speech rate and at greater length than non specific ones. SDM with positive affective valence were shorter and included less variability in fundamental frequency than negative SDM. Second, emotionally-charged (positive vs. negative; high vs. low arousal) vs. emotionally-neutral utterances as to Emotaix classification were compared over all SDM. Only a few significant effects were observed, which led us to discuss the role of emotion regulation in the SDM task.
Disciplines :
Neurosciences & behavior
Languages & linguistics
Author, co-author :
Delvaux, Véronique  ;  Université de Mons - UMONS > Faculté de Psychologie et des Sciences de l'Education > Service de Métrologie et Sciences du langage
Lavallée, Audrey;  University of Lille, SCALab, UMR, CNRS 9193, France ; UMONS, Department of Legal Psychology, Mons, Belgium
Degouis, Fanny  ;  Université de Mons - UMONS > Faculté de Psychologie et des Sciences de l'Education > Service de Psychopathologie légale
Saloppé, Xavier;  University of Lille, SCALab, UMR, CNRS 9193, France ; Research Center in Social Defense, Tournai, Belgium ; Psychiatric Hospital, Saint-Amand-les-Eaux, France
Pham hoang, Thierry  ;  Université de Mons - UMONS > Faculté de Psychologie et des Sciences de l'Educatio > Service de Psychopathologie légale
Nandrino, Jean-Louis;  University of Lille, SCALab, UMR, CNRS 9193, France
Language :
English
Title :
Telling self-defining memories: An acoustic study of natural emotional speech productions
Publication date :
2022
Event name :
Interspeech 2022
Event place :
Incheon, Kor
Event date :
18-09-2022 => 22-09-2022
Audience :
International
Journal title :
Proceedings of the Annual Conference of the International Speech Communication Association, INTERSPEECH
ISSN :
2308-457X
eISSN :
1990-9772
Publisher :
International Speech Communication Association
Volume :
2022-September
Pages :
1337 - 1341
Peer reviewed :
Peer reviewed
Research unit :
P362 - Métrologie et Sciences du langage
Research institute :
R350 - Institut de recherche en sciences et technologies du langage
Funders :
Amazon - Science
Apple
et al.
Hyundai
Kakaoenterprise
LG AI Research
Funding text :
The authors wish to thank the organisms supporting the Memantemo project: the French Agence Nationale de la Recherche (ANR-11-EQPX-0023), the FEDER SCV-IrDIVE European program, the Hauts-de-France Region and the University of Mons. Special thanks to Florian Sanssen for his valuable contribution to data collection.
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since 12 January 2023

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