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Papers

Automated Chess Commentator Powered by Neural Chess Engine

2019-09-23 · ACL 2019 7 · Hongyu Zang, Zhiwei Yu, Xiaojun Wan

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.

📄 PDF Abstract BibTeX arXiv:1909.10413

Code (2)

zhyack/SCC 공식 구현 tf
errmeier/NLP-project pytorch

Tasks

Text Generation

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