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

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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Bibliographic Details
Main Authors: A-Hyeon Jo, Keun-Chang Kwak
Format: Article
Language:English
Published: IEEE 2025-01-01
Series:IEEE Access
Subjects:
Feature-map fusion
Korean speech data
speech emotion recognition
temporal convolutional network
pretrained convolutional neural networks
Online Access:https://ieeexplore.ieee.org/document/10854478/
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https://ieeexplore.ieee.org/document/10854478/

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