Template-free Data-to-Text Generation of Finnish Sports News
This addresses the problem of generating realistic sports news from data for Finnish ice hockey, though it is incremental as it focuses on adapting existing methods to a specific domain and language.
The researchers tackled the challenge of automated data-to-text news generation for Finnish ice hockey by developing a corpus edited for end-to-end training, resulting in generated text judged by journalists as relatively close to a viable product.
News articles such as sports game reports are often thought to closely follow the underlying game statistics, but in practice they contain a notable amount of background knowledge, interpretation, insight into the game, and quotes that are not present in the official statistics. This poses a challenge for automated data-to-text news generation with real-world news corpora as training data. We report on the development of a corpus of Finnish ice hockey news, edited to be suitable for training of end-to-end news generation methods, as well as demonstrate generation of text, which was judged by journalists to be relatively close to a viable product. The new dataset and system source code are available for research purposes at https://github.com/scoopmatic/finnish-hockey-news-generation-paper.