Building a Buzzer-quiz Answering System
Naoya Sugiura, Kosuke Yamada, Ryohei Sasano, Koichi Takeda, Katsuhiko Toyama
Abstract
A buzzer quiz is a genre of quiz in which multiple players simultaneously listen to a quiz being read aloud and respond it by buzzing in as soon as they can predict the answer. Because incorrect answers often result in penalties, a buzzer-quiz answering system must not only predict the answer from only part of a question but also estimate the predicted answer’s accuracy. In this paper, we introduce two types of buzzer-quiz answering systems: (1) a system that directly generates an answer from part of a question by using an autoregressive language model; and (2) a system that first reconstructs the entire question by using an autoregressive language model and then determines the answer according to the reconstructed question. We then propose a method to estimate the accuracy of the answers for each system by using the internal scores of each model.- Anthology ID:
- 2023.acl-srw.29
- Volume:
- Proceedings of the 61st Annual Meeting of the Association for Computational Linguistics (Volume 4: Student Research Workshop)
- Month:
- July
- Year:
- 2023
- Address:
- Toronto, Canada
- Editors:
- Vishakh Padmakumar, Gisela Vallejo, Yao Fu
- Venue:
- ACL
- SIG:
- Publisher:
- Association for Computational Linguistics
- Note:
- Pages:
- 194–199
- Language:
- URL:
- https://aclanthology.org/2023.acl-srw.29
- DOI:
- 10.18653/v1/2023.acl-srw.29
- Cite (ACL):
- Naoya Sugiura, Kosuke Yamada, Ryohei Sasano, Koichi Takeda, and Katsuhiko Toyama. 2023. Building a Buzzer-quiz Answering System. In Proceedings of the 61st Annual Meeting of the Association for Computational Linguistics (Volume 4: Student Research Workshop), pages 194–199, Toronto, Canada. Association for Computational Linguistics.
- Cite (Informal):
- Building a Buzzer-quiz Answering System (Sugiura et al., ACL 2023)
- PDF:
- https://preview.aclanthology.org/ingest-acl-2023-videos/2023.acl-srw.29.pdf