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Communication Dans Un Congrès Année : 2022

Annotation of expressive dimensions on a multimodal French corpus of political interviews

Résumé

We present a French corpus of political interviews labeled at the utterance level according to expressive dimensions such as Arousal. This corpus consists of 7.5 hours of high-quality audiovisual recordings with transcription. At the time of this publication, 1 hour of speech was segmented into short utterances, each manually annotated in Arousal. Our segmentation approach differs from similar corpora and allows us to perform an automatic Arousal prediction baseline by building a speech-based classification model. Although this paper focuses on the acoustic expression of Arousal, it paves the way for future work on conflictual and hostile expression recognition as well as multimodal architectures.
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Dates et versions

hal-04259166 , version 1 (20-12-2023)

Licence

Paternité - Pas d'utilisation commerciale

Identifiants

  • HAL Id : hal-04259166 , version 1

Citer

Jules Cauzinille, Marc Evrard, Nikita Kiselov, Albert Rilliard. Annotation of expressive dimensions on a multimodal French corpus of political interviews. First Workshop on Natural Language Processing for Political Sciences (PoliticalNLP), Jun 2022, Marseille (FR), France. pp.91-97. ⟨hal-04259166⟩
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