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hi Anton Yelchin thanks for taking interesting our paper style transfer from non parallel text by cross alignment at nips 2017 language is rich and powerful we can express the same meaning in many different ways it can be brief or verbose cloak wheel or professional polite or impolite and people have their different personal styles can we train machines to perform this task given a sentence rewrite it in another stone say Shakespeare style or Trumpamp;#39;s tell this is an important step towards real language understanding and it has wide applications such as to design personalized chatbots and to appropriately convey a message ing to different social contexts instead of using massive amounts of parallel data we only assume access to two non parallel corpora x1 x2 of different styles y1 y2 and we want to transfer between them we learn an encoder e that encodes a sentence x2 a style independent content representation Z and a generate G that generates us and has acts from a demon snail