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Author Spotlight: Deciphering the Cognitive and Neural Mechanisms of Gesture in Communication
Published on: January 26, 2024
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GeSTICS: Un corpus multimodal para el estudio de la síntesis de gestos en interacciones de dos partes con habla
Gaoussou Youssouf Kebe1, Mehmet Deniz Birlikci1, Auriane Boudin2
1Carnegie Mellon University, Pittsburgh, Pennsylvania, USA.
Proceedings of the ... ACM International Conference on Intelligent Virtual Agents. IVA (Conference)
|December 31, 2025
Resumen
El conjunto de datos GeSTICS captura datos multimodales de entrevistas deportivas para modelar cómo los factores individuales y situacionales influyen en los gestos y expresiones faciales co-discurso para una mejor comunicación de agentes virtuales.
Sus antecedentes:
- La interacción humana-agente eficaz requiere comportamientos no verbales realistas.
- Los conjuntos de datos existentes a menudo carecen de señales contextuales integrales como factores individuales y situacionales.
- Modelar la interacción de señales verbales, no verbales y contextuales es crucial para gestos co-discurso y expresiones faciales naturales.
Conclusiones:
- El conjunto de datos GeSTICS proporciona un recurso valioso para el estudio de la comunicación multimodal.
- La comprensión de los factores contextuales es clave para mejorar la generación de comportamiento no verbal en la interacción humano-agente.
- El conjunto de datos y el código de análisis están disponibles públicamente para avanzar en la investigación en agentes virtuales e interacción humano-robot.
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