What is it about?
The ability to identify emotions in texts is essential since they serve as the main method of communication between humans and computers in chat rooms, forums, blogs, product reviews, and other social media sites like Facebook, Twitter, and YouTube. This work focuses on implementing a model of a system to detect the emotions from Malayalam text. Research on emotion analysis in Malayalam is still in its infancy compared to English, as it is difficult to obtain a preprocessed Malayalam dataset because of its agglutinative and free word order structure.
Featured Image
Why is it important?
Our work focus on transformer-based model to handle large Malayalam datasets with greater accuracy. This work is the novel application of recent DL techniques and more advanced transformer-based algorithms in detecting emotions in Malayalam text.
Perspectives
Created a Malayalam emotion recognition dataset, which is helpful to future research work in this area.
Remesh Babu K R
Govt. Engineering College Idukki, Kerala, India
Our work is the first ever application of learning-based techniques to detect emotions from Malayalam text. We have utilized the traditional ML , recent DL and most advanced transformer-based approaches to extract emotions. We also compared our models with the SOTA English models to prove the effectiveness of the proposed models.
Anuja K
Read the Original
This page is a summary of: Emotion Detection System for Malayalam Text using Deep Learning and Transformers, ACM Transactions on Asian and Low-Resource Language Information Processing, May 2024, ACM (Association for Computing Machinery),
DOI: 10.1145/3663475.
You can read the full text:
Contributors
The following have contributed to this page
