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Automatic Topic-Based Sentence Generation in Russian

Student: Samoylenko Igor

Supervisor: Timofey Arkhangelskiy

Faculty: Faculty of Humanities

Educational Programme: Language Theory and Computational Linguistics (Master)

Year of Graduation: 2017

This work is devoted to the development of software for automatic generation of sentences in Russian. A recurrent neural network is used as the main generation tool. LSTM-network is used to generate a pattern containing grammatical tags, and a separate sub-script uses the corpus dictionary to make a topic-based lexical choice. The output sentences for the most part are meaningless, but they show good results in grammatical connectivity.

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