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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Main Authors: | A-Hyeon Jo, Keun-Chang Kwak |
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Format: | Article |
Language: | English |
Published: |
IEEE
2025-01-01
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Series: | IEEE Access |
Subjects: | |
Online Access: | https://ieeexplore.ieee.org/document/10854478/ |
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