Abstract
Existing English-teaching chatbots rarely incorporate empathy explicitly in their feedback, but empathetic feedback could help keep students engaged and reduce learner anxiety. Toward this end, we propose the task of negative emotion detection via audio, for recognizing empathetic feedback opportunities in language learning. We then build the first spoken English-teaching chatbot with adaptive, empathetic feedback. This feedback is synthesized through automatic prompt optimization of ChatGPT and is evaluated with English learners. We demonstrate the effectiveness of our system through a preliminary user study.- Anthology ID:
- 2024.bea-1.4
- Volume:
- Proceedings of the 19th Workshop on Innovative Use of NLP for Building Educational Applications (BEA 2024)
- Month:
- June
- Year:
- 2024
- Address:
- Mexico City, Mexico
- Editors:
- Ekaterina Kochmar, Marie Bexte, Jill Burstein, Andrea Horbach, Ronja Laarmann-Quante, Anaïs Tack, Victoria Yaneva, Zheng Yuan
- Venue:
- BEA
- SIG:
- SIGEDU
- Publisher:
- Association for Computational Linguistics
- Note:
- Pages:
- 34–53
- Language:
- URL:
- https://aclanthology.org/2024.bea-1.4
- DOI:
- Cite (ACL):
- Li Siyan, Teresa Shao, Julia Hirschberg, and Zhou Yu. 2024. Using Adaptive Empathetic Responses for Teaching English. In Proceedings of the 19th Workshop on Innovative Use of NLP for Building Educational Applications (BEA 2024), pages 34–53, Mexico City, Mexico. Association for Computational Linguistics.
- Cite (Informal):
- Using Adaptive Empathetic Responses for Teaching English (Siyan et al., BEA 2024)
- PDF:
- https://preview.aclanthology.org/nschneid-patch-5/2024.bea-1.4.pdf