Interspeech 2005 2005
DOI: 10.21437/interspeech.2005-92
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Correlating student acoustic-prosodic profiles with student learning in spoken tutoring dialogues

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Cited by 6 publications
(2 citation statements)
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“…For both RMS and f0 we calculated the max, min, and mean value over each turn. Neither measure was normalized, partly because normalization of these features had not been helpful in previous work [12]. Mean RMS was also used in the convergence study of Coulston et al [1].…”
Section: Acoustic/prosodic Convergencementioning
confidence: 99%
“…For both RMS and f0 we calculated the max, min, and mean value over each turn. Neither measure was normalized, partly because normalization of these features had not been helpful in previous work [12]. Mean RMS was also used in the convergence study of Coulston et al [1].…”
Section: Acoustic/prosodic Convergencementioning
confidence: 99%
“…Fuente: Adaptación dePlutchik (1980).Para el desarrollo de un sistema de software que reconozca emociones, resulta conveniente elegir un modelo con un número pequeño de emociones básicas. Ekman en su trabajo sobre análisis facial de expresiones (1999) describe un subconjunto de emociones que incluye sorpresa, miedo, alegría, enojo, disgusto/desprecio e interés, las cuales han sido utilizadas en sistemas tutores inteligentes que poseen capacidad para reconocer y tratar emociones y/o afectos(Arroyo et al, 2009;D'Mello et al, 2009;Forbes-Riley & Litman, 2009;D'Mello et al, 2011).…”
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