Classification of Speech Emotion State Based on Feature Map Fusion of TCN and Pretrained CNN Model From Korean Speech Emotion Data

In this paper, we propose a method for designing a classification model of speech emotional state based on the feature-map fusion of temporal convolutional network (TCN) and the pretrained convolutional neural networks (CNN) from Korean speech database. For this purpose, the proposed approach is com...

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Detalhes bibliográficos

Principais autores:	A-Hyeon Jo, Keun-Chang Kwak
Formato:	Artigo
Idioma:	Inglês
Publicado em:	IEEE 2025-01-01
coleção:	IEEE Access
Assuntos:	Feature-map fusion Korean speech data speech emotion recognition temporal convolutional network pretrained convolutional neural networks
Acesso em linha:	https://ieeexplore.ieee.org/document/10854478/
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