EAT2seq: A generic framework for controlled sentence transformation without task-specific training

25 Feb 2019Tommi GröndahlN. Asokan

We present EAT2seq: a novel method to architect automatic linguistic transformations for a number of tasks, including controlled grammatical or lexical changes, style transfer, text generation, and machine translation. Our approach consists in creating an abstract representation of a sentence's meaning and grammar, which we use as input to an encoder-decoder network trained to reproduce the original sentence... (read more)

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