Multimodal Emotion Recognition Using Feature Fusion: An LLM-Based Approach-Reference-Cited by-同舟云学术

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Multimodal Emotion Recognition Using Feature Fusion: An LLM-Based Approach

Published:2024 Issue: Volume:12 Page:108052-108071
ISSN:2169-3536
Container-title:IEEE Access
language:
Short-container-title:IEEE Access

Author:

Chandraumakantham Omkumar¹^ORCID,Gowtham N.¹^ORCID,Zakariah Mohammed²^ORCID,Almazyad Abdulaziz³^ORCID

Affiliation:

1. School of Computer Science and Engineering, Vellore Institute of Technology- Chennai Campus, Chennai, India

2. Department of Computer Sciences and Engineering, College of Applied Science, King Saud University, Riyadh, Saudi Arabia

3. Department of Computer Engineering, College of Computer and Information Sciences, King Saud University, Riyadh, Saudi Arabia

Funder

Researchers Supporting Program at King Saud University

Publisher

Institute of Electrical and Electronics Engineers (IEEE)

Link

http://xplorestaging.ieee.org/ielx8/6287639/10380310/10591796.pdf?arnumber=10591796

Reference28 articles.

1. Emotion quantification and classification using the neutrosophic approach to deep learning

2. Exploring deep learning algorithm to model emotions recognition from speech

3. Speech emotion recognition system using gender dependent convolution neural network

4. Unveiling embedded features in Wav2vec2 and HuBERT msodels for Speech Emotion Recognition

5. Disruptive situation detection on public transport through speech emotion recognition

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