Speech Emotion Recognition using Context-Aware Dilated Convolution Network
Author:
Affiliation:
1. Kyungpook National University,Graduate School of Electronics and Electrical Engineering,Daegu,Republic of Korea
2. Kyungpook National University,School of Electronics and Electrical Engineering,Daegu,Republic of Korea
Publisher
IEEE
Link
http://xplorestaging.ieee.org/ielx7/9943568/9943554/09943771.pdf?arnumber=9943771
Reference18 articles.
1. Speech emotion recognition model based on Bi-GRU and Focal Loss
2. Dilated causal convolution with multi-head self attention for sensor human activity recognition
3. Emotion Recognition from Raw Speech using Wavenet
4. Mlt-dnet: Speech emotion recognition using 1d dilated cnn based on multi-learning trick approach;kwon;Expert Systems with Applications,2021
5. End-to-end speech emotion recognition using a novel context-stacking dilated convolution neural network
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1. Dilated Causal Convolution Based Human Activity Recognition Using Voxelized Point Cloud Radar Data;2024 International Conference on Artificial Intelligence in Information and Communication (ICAIIC);2024-02-19
2. A review on speech emotion recognition: A survey, recent advances, challenges, and the influence of noise;Neurocomputing;2024-02
3. Bimodal Speech Emotion Recognition using Fused Intra and Cross Modality Features;2023 Fourteenth International Conference on Ubiquitous and Future Networks (ICUFN);2023-07-04
4. Speech Emotion Recognition Based on Two-Stream Deep Learning Model Using Korean Audio Information;Applied Sciences;2023-02-08
5. Deep Learning Approaches for Bimodal Speech Emotion Recognition: Advancements, Challenges, and a Multi-Learning Model;IEEE Access;2023
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