How Would You Reproduce a Synthetic Sound of an Ellipse in Water ? A Phenomenological Investigation of Pre-reflexive Contents of Consciousness - Archive ouverte HAL
Chapitre D'ouvrage Année : 2021

How Would You Reproduce a Synthetic Sound of an Ellipse in Water ? A Phenomenological Investigation of Pre-reflexive Contents of Consciousness

Résumé

This article describes a listening experiment based on elicitation interviews that aims at describing the conscious experience of a subject submitted to a perceptual stimulation. As opposed to traditional listening experiments in which subjects are generally influenced by closed or suggestive questions and limited to predefined, forced choices, elicitation interviews make it possible to get a deeper insight into the listener's perception, in particular to the pre-reflexive content of the conscious experiences. Inspired by previous elicitation interviews during which subjects passively listened to sounds, this experience is based on an active task during which the subjects were asked to reproduce a sound with a stylus on a graphic tablet that controlled a synthesis model. The reproduction was followed by an elicitation interview. The trace of the graphic gesture as well as the answers recorded during the interview were then analyzed. Results revealed that the subjects varied their focus towards both the evoked sound source, and intrinsic sound properties and also described their sensations induced by the experience.
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Dates et versions

hal-03324621 , version 1 (23-08-2021)

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Jean Vion-Dury, Marie Degrandi, Gaëlle Mougin, Thomas Bordonné, Sølvi Ystad, et al.. How Would You Reproduce a Synthetic Sound of an Ellipse in Water ? A Phenomenological Investigation of Pre-reflexive Contents of Consciousness. Richard Kronland-Martinet Sølvi Ystad Mitsuko Aramaki. Perception, Representations, Image, Sound, Music, 14th International Symposium, CMMR 2019, Marseille, France, October 14–18, 2019, Revised Selected Papers, 12631, pringer Nature Switzerland AG, pp.726, 2021, Lecture Notes in Computer Science, 978-3-030-70209-0. ⟨10.1007/978-3-030-70210-6⟩. ⟨hal-03324621⟩
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