Abstract
This paper presents our approach for the WASSA 2023 Empathy, Emotion and Personality Shared Task. Empathy and distress are human feelings that are implicitly expressed in natural discourses. Empathy and distress detection are crucial challenges in Natural Language Processing that can aid our understanding of conversations. The provided dataset consists of several long-text examples in the English language, with each example associated with a numeric score for empathy and distress. We experiment with several BERT-based models as a part of our approach. We also try various ensemble methods. Our final submission has a Pearson’s r score of 0.346, placing us third in the empathy and distress detection subtask.- Anthology ID:
- 2023.wassa-1.52
- Volume:
- Proceedings of the 13th Workshop on Computational Approaches to Subjectivity, Sentiment, & Social Media Analysis
- Month:
- July
- Year:
- 2023
- Address:
- Toronto, Canada
- Editors:
- Jeremy Barnes, Orphée De Clercq, Roman Klinger
- Venue:
- WASSA
- SIG:
- Publisher:
- Association for Computational Linguistics
- Note:
- Pages:
- 564–568
- Language:
- URL:
- https://aclanthology.org/2023.wassa-1.52
- DOI:
- 10.18653/v1/2023.wassa-1.52
- Cite (ACL):
- Tanmay Chavan, Kshitij Deshpande, and Sheetal Sonawane. 2023. PICT-CLRL at WASSA 2023 Empathy, Emotion and Personality Shared Task: Empathy and Distress Detection using Ensembles of Transformer Models. In Proceedings of the 13th Workshop on Computational Approaches to Subjectivity, Sentiment, & Social Media Analysis, pages 564–568, Toronto, Canada. Association for Computational Linguistics.
- Cite (Informal):
- PICT-CLRL at WASSA 2023 Empathy, Emotion and Personality Shared Task: Empathy and Distress Detection using Ensembles of Transformer Models (Chavan et al., WASSA 2023)
- PDF:
- https://preview.aclanthology.org/ingest-acl-2023-videos/2023.wassa-1.52.pdf