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Understanding human expression: Data-driven approaches and machine learning tools| title | Understanding human expression: Data-driven approaches and machine learning tools |
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| start_date | 2023/04/18 |
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| schedule | 16h |
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| online | yes |
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| visio | https://ucl.zoom.us/j/94073423112?pwd=TWRGNVVTRFhuZ0dOalE0SnpOQ0xFdz09 |
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| location_info | On Zoom |
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| summary | In this talk, I will discuss theoretical and computational advances that allow researchers to make better use of behavioral data such as vocalizations (laughs, sighs, "huhs", etc.), speech prosody (the tune, rhythm, and timbre of speech), and facial expressions, alone and combined with language. These signals are found to play a vital role in human communication and can be used to improve our understanding of social interaction, health and wellness, personality, and culture. |
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| responsibles | Esposito |
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Workflow history| from state (1) | to state | comment | date |
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| submitted | published | | 2023/04/18 12:03 UTC |
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