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E.V. Chistova, A.O. Shelmanov, I.V. Smirnov Natural language dialogue modelling with deep learning |
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Abstract. Building natural language dialogue systems that can converse coherently with user is an actual problem of artificial intelligence. This paper presents an overview of the open-domain generative neural network dialogue models. The main problems of constructing dialogue models based on machine learning and methods for their solution are considered. An experimental comparison of the vanilla neural network encoder-decoder model with its attention mechanism modification was carried out on the Russian-language data. Keywords: dialogue systems, natural language processing, natural language generation, neural networks, artificial intelligence, deep learning, encoder-decoder model. PP. 105-115. DOI: 10.14357/20790279190110 References 1. Ritter A., Cherry C., Dolan W.B. Data-driven response generation in social media //Proceedings of the conference on empirical methods in natural language processing. – Association for Computational Linguistics, 2011. – P. 583-593. 2. Sordoni A. et al. 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