Arabic Multiclass Emotional Analysis Using a Bidirectional GRU-LSTM Deep Model on Twitter-Reference-Cited by-同舟云学术

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Arabic Multiclass Emotional Analysis Using a Bidirectional GRU-LSTM Deep Model on Twitter

Published:2024-05-16 Issue: Volume:3 Page:1-5
ISSN:
Container-title:2024 4th International Conference on Innovative Research in Applied Science, Engineering and Technology (IRASET)
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Author:

Elfaik Hanane¹,Nfaoui El Habib²

Affiliation:

1. Chouaib Doukkali University,LAROSERI Laboratory, Faculty of Sciences,Department of Computer Science,El Jadida,Morocco

2. Sidi Mohamed Ben Abdellah University,LISAC Laboratory, Faculty of Sciences Dhar EL Mahraz,Department of Computer Science,Fez,Morocco

Publisher

IEEE

Link

http://xplorestaging.ieee.org/ielx8/10548014/10548010/10548363.pdf?arnumber=10548363

Reference32 articles.

1. The Affect Dilemma for Artificial Agents: Should We Develop Affective Artificial Agents?

2. A Survey of Autonomous Human Affect Detection Methods for Social Robots Engaged in Natural HRI

3. Leveraging feature-level fusion representations and attentional bidirectional RNN-CNN deep models for Arabic affect analysis on Twitter

4. AraVec: A set of Arabic Word Embedding Models for use in Arabic NLP

5. Describing the emotional states that are expressed in speech

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