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Cracking the code of the social cognition of face and voice with reverse-correlation methods| title | Cracking the code of the social cognition of face and voice with reverse-correlation methods |
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| start_date | 2025/01/23 |
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| schedule | 14h-16h |
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| online | no |
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| location_info | salle des Colloques |
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| summary | Reverse correlation is a powerful psychophysical method able to uncover what stimulus features are used by observers in perceptual decisions. Although reverse correlation was traditionally restricted to low-level stimulus dimension (e.g. edge detection in abstract images), recent signal-processing advances have extended the approach to the perception of speech and faces, sparking interest in the affective and social-cognitive sciences. In this talk, I present a set of recent studies where we used these methods to explore (1) the perception of speech prosody in healthy (L1 and L2 listeners) and patient populations (right-hemisphere stroke survivors); and (2) the perception of facial features of emotional expressions in humans and machines (i.e. AI explainability). In addition, I will introduce CLEESE, PALIN and JONES (©2018-2024), a set of open-source, and interoperable, Python toolboxes we designed to facilitate the design, conduction and analysis of such experiments - in hope they can foster ideas for your own research questions. |
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| responsibles | Fournier |
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| submitted | published | | 2025/01/09 14:27 UTC |
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