Speech emotion representation : A method to convert discrete to dimensional emotional models for emotional inference multimodal frameworks

Computer-Human interaction is more frequent now than ever before, thus the main goal of this research area is to improve communication with computers, so it becomes as natural as possible. A key aspect to achieve such interaction is the affective component often missing from last decade developments...

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Detalles Bibliográficos
Autores principales: Elkfury, Fernando, Ierache, Jorge Salvador
Formato: Objeto de conferencia
Lenguaje:Inglés
Publicado: 2021
Materias:
Ciencias Informáticas
Emotions
Multimodal Framework
Affective computing
Acceso en línea:http://sedici.unlp.edu.ar/handle/10915/125145
Aporte de:
SEDICI (UNLP) de Universidad Nacional de La Plata
id I19-R120-10915-125145
record_format dspace
institution Universidad Nacional de La Plata
institution_str I-19
repository_str R-120
collection SEDICI (UNLP)
language Inglés
topic Ciencias Informáticas
Emotions
Multimodal Framework
Affective computing
spellingShingle Ciencias Informáticas
Emotions
Multimodal Framework
Affective computing
Elkfury, Fernando
Ierache, Jorge Salvador
Speech emotion representation : A method to convert discrete to dimensional emotional models for emotional inference multimodal frameworks
topic_facet Ciencias Informáticas
Emotions
Multimodal Framework
Affective computing
description Computer-Human interaction is more frequent now than ever before, thus the main goal of this research area is to improve communication with computers, so it becomes as natural as possible. A key aspect to achieve such interaction is the affective component often missing from last decade developments. To improve computer human interaction in this paper we present a method to convert discrete or categorical data from a CNN emotion classifier trained with Mel scale spectrograms to a two-dimensional model, pursuing integration of the human voice as a feature for emotional inference multimodal frameworks. Lastly, we discuss preliminary results obtained from presenting audiovisual stimuli to different subject and comparing dimensional arousal-valence results and it’s SAM surveys.
format Objeto de conferencia
Objeto de conferencia
author Elkfury, Fernando
Ierache, Jorge Salvador
author_facet Elkfury, Fernando
Ierache, Jorge Salvador
author_sort Elkfury, Fernando
title Speech emotion representation : A method to convert discrete to dimensional emotional models for emotional inference multimodal frameworks
title_short Speech emotion representation : A method to convert discrete to dimensional emotional models for emotional inference multimodal frameworks
title_full Speech emotion representation : A method to convert discrete to dimensional emotional models for emotional inference multimodal frameworks
title_fullStr Speech emotion representation : A method to convert discrete to dimensional emotional models for emotional inference multimodal frameworks
title_full_unstemmed Speech emotion representation : A method to convert discrete to dimensional emotional models for emotional inference multimodal frameworks
title_sort speech emotion representation : a method to convert discrete to dimensional emotional models for emotional inference multimodal frameworks
publishDate 2021
url http://sedici.unlp.edu.ar/handle/10915/125145
work_keys_str_mv AT elkfuryfernando speechemotionrepresentationamethodtoconvertdiscretetodimensionalemotionalmodelsforemotionalinferencemultimodalframeworks
AT ierachejorgesalvador speechemotionrepresentationamethodtoconvertdiscretetodimensionalemotionalmodelsforemotionalinferencemultimodalframeworks
bdutipo_str Repositorios
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