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Creating open-domain chatbots requires large amounts of conversational dataand related benchmark tasks to evaluate them. Standardized evaluation tasks arecrucial for creating automatic evaluation metrics for model development;otherwise, comparing the models would require resource-expensive humanevaluation. While chatbot challenges have recently managed to provide aplethora of such resources for English, resources in other languages are notyet available. In this work, we provide a starting point for Finnishopen-domain chatbot research. We describe our collection efforts to create theFinnish chat conversation corpus FinChat, which is made available publicly.FinChat includes unscripted conversations on seven topics from people ofdifferent ages. Using this corpus, we also construct a retrieval-basedevaluation task for Finnish chatbot development. We observe that off-the-shelfchatbot models trained on conversational corpora do not perform better thanchance at choosing the right answer based on automatic metrics, while humanscan do the same task almost perfectly. Similarly, in a human evaluation,responses to questions from the evaluation set generated by the chatbots arepredominantly marked as incoherent. Thus, FinChat provides a challengingevaluation set, meant to encourage chatbot development in Finnish.

FinChat: Corpus and evaluation setup for Finnish chat conversations on everyday topics