Abstract
Using technology for analysis of human emotion is a relatively nascent research area. There are several types of data where emotion recognition can be employed, such as - text, images, audio and video. In this paper, the focus is on emotion recognition in text data. Emotion recognition in text can be performed from both written comments and from conversations. In this paper, the dataset used for emotion recognition is a list of comments. While extensive research is being performed in this area, the language of the text plays a very important role. In this work, the focus is on the Dravidian language of Tamil. The language and its script demands an extensive pre-processing. The paper contributes to this by adapting various pre-processing methods to the Dravidian Language of Tamil. A CNN method has been adopted for the task at hand. The proposed method has achieved a comparable result.- Anthology ID:
- 2022.dravidianlangtech-1.9
- Volume:
- Proceedings of the Second Workshop on Speech and Language Technologies for Dravidian Languages
- Month:
- May
- Year:
- 2022
- Address:
- Dublin, Ireland
- Editors:
- Bharathi Raja Chakravarthi, Ruba Priyadharshini, Anand Kumar Madasamy, Parameswari Krishnamurthy, Elizabeth Sherly, Sinnathamby Mahesan
- Venue:
- DravidianLangTech
- SIG:
- Publisher:
- Association for Computational Linguistics
- Note:
- Pages:
- 58–63
- Language:
- URL:
- https://aclanthology.org/2022.dravidianlangtech-1.9
- DOI:
- 10.18653/v1/2022.dravidianlangtech-1.9
- Cite (ACL):
- Judith Jeyafreeda Andrew. 2022. JudithJeyafreedaAndrew@TamilNLP-ACL2022:CNN for Emotion Analysis in Tamil. In Proceedings of the Second Workshop on Speech and Language Technologies for Dravidian Languages, pages 58–63, Dublin, Ireland. Association for Computational Linguistics.
- Cite (Informal):
- JudithJeyafreedaAndrew@TamilNLP-ACL2022:CNN for Emotion Analysis in Tamil (Andrew, DravidianLangTech 2022)
- PDF:
- https://preview.aclanthology.org/nschneid-patch-3/2022.dravidianlangtech-1.9.pdf