Style transfer in NLP: a framework and multilingual analysis with Friends TV series
Maria Tikhonova, Elina Telesheva, Sergey Mirzoev, Polina Tarantsova, Stanislav Petrov, Alena Fenogenova · 2021
Style transfer is an important and a rapidly developing of Natural Language Processing. This days more and more methods and models are proposed which allow us to generate text in predefined style. In this paper we propose a framework for style transfer of “Friends” TV series. The trained models are able to mimic one of 6 main characters of this famous TV-series in English and Russian. We also present a dialogue dataset of “Friends” subtitles in English and its Russian automatic translation. In addition to that we perform a multilingual comparison of “Friends” style transfer in the two considered languages.