Empathy and Distress Prediction using Transformer Multi-output Regression and Emotion Analysis with an Ensemble of Supervised and Zero-Shot Learning Models
Flor Miriam Del Arco, Jaime Collado-Montañez, L. Alfonso Ureña, María-Teresa Martín-Valdivia
Abstract
This paper describes the participation of the SINAI research group at WASSA 2022 (Empathy and Personality Detection and Emotion Classification). Specifically, we participate in Track 1 (Empathy and Distress predictions) and Track 2 (Emotion classification). We conducted extensive experiments developing different machine learning solutions in line with the state of the art in Natural Language Processing. For Track 1, a Transformer multi-output regression model is proposed. For Track 2, we aim to explore recent techniques based on Zero-Shot Learning models including a Natural Language Inference model and GPT-3, using them in an ensemble manner with a fine-tune RoBERTa model. Our team ranked 2nd in the first track and 3rd in the second track.- Anthology ID:
- 2022.wassa-1.23
- Volume:
- Proceedings of the 12th Workshop on Computational Approaches to Subjectivity, Sentiment & Social Media Analysis
- Month:
- May
- Year:
- 2022
- Address:
- Dublin, Ireland
- Editors:
- Jeremy Barnes, Orphée De Clercq, Valentin Barriere, Shabnam Tafreshi, Sawsan Alqahtani, João Sedoc, Roman Klinger, Alexandra Balahur
- Venue:
- WASSA
- SIG:
- Publisher:
- Association for Computational Linguistics
- Note:
- Pages:
- 239–244
- Language:
- URL:
- https://aclanthology.org/2022.wassa-1.23
- DOI:
- 10.18653/v1/2022.wassa-1.23
- Cite (ACL):
- Flor Miriam Del Arco, Jaime Collado-Montañez, L. Alfonso Ureña, and María-Teresa Martín-Valdivia. 2022. Empathy and Distress Prediction using Transformer Multi-output Regression and Emotion Analysis with an Ensemble of Supervised and Zero-Shot Learning Models. In Proceedings of the 12th Workshop on Computational Approaches to Subjectivity, Sentiment & Social Media Analysis, pages 239–244, Dublin, Ireland. Association for Computational Linguistics.
- Cite (Informal):
- Empathy and Distress Prediction using Transformer Multi-output Regression and Emotion Analysis with an Ensemble of Supervised and Zero-Shot Learning Models (Del Arco et al., WASSA 2022)
- PDF:
- https://preview.aclanthology.org/naacl24-info/2022.wassa-1.23.pdf
- Data
- CARER