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Automated Chess Commentator Powered by Neural Chess Engine

2019-09-23ACL 2019Code Available0· sign in to hype

Hongyu Zang, Zhiwei Yu, Xiaojun Wan

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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.

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