Abstract
In this paper, we explore a new approach for automated chess commentary generation, which aims to generate chess commentary texts in different categories (e.g., description, comparison, planning, etc.). We introduce a neural chess engine into text generation models to help with encoding boards, predicting moves, and analyzing situations. By jointly training the neural chess engine and the generation models for different categories, the models become more effective. We conduct experiments on 5 categories in a benchmark Chess Commentary dataset and achieve inspiring results in both automatic and human evaluations.- Anthology ID:
- P19-1597
- Volume:
- Proceedings of the 57th Annual Meeting of the Association for Computational Linguistics
- Month:
- July
- Year:
- 2019
- Address:
- Florence, Italy
- Editors:
- Anna Korhonen, David Traum, Lluís Màrquez
- Venue:
- ACL
- SIG:
- Publisher:
- Association for Computational Linguistics
- Note:
- Pages:
- 5952–5961
- Language:
- URL:
- https://aclanthology.org/P19-1597
- DOI:
- 10.18653/v1/P19-1597
- Cite (ACL):
- Hongyu Zang, Zhiwei Yu, and Xiaojun Wan. 2019. Automated Chess Commentator Powered by Neural Chess Engine. In Proceedings of the 57th Annual Meeting of the Association for Computational Linguistics, pages 5952–5961, Florence, Italy. Association for Computational Linguistics.
- Cite (Informal):
- Automated Chess Commentator Powered by Neural Chess Engine (Zang et al., ACL 2019)
- PDF:
- https://preview.aclanthology.org/nschneid-patch-3/P19-1597.pdf
- Code
- zhyack/SCC + additional community code