본 논문에서는 먼저 language translation 모델을 활용해서 문장의 latent representation 더 잘 배울 수 있도록 하였습니다. 특히 이 latent representation 내에 stylistic 한 정보가 없도록 학습하고자 하였습니다.
이후 adversarial generation 을 사용해서 우리가 원하는 style로 문장을 생성할 수 있는 모델을 제안합니다.
sentiment, gender and political slant 테스크로 실험을 진행하였고 automatic와 manual 평가에서 meaning preservation and fluency 에서 의미있는 성능 향상이 있었습니다.
Abstract (요약) 🕵🏻♂️
Style transfer is the task of rephrasing the text to contain specific stylistic properties without changing the intent or affect within the context. This paper introduces a new method for automatic style transfer. We first learn a latent representation of the input sentence which is grounded in a language translation model in order to better preserve the meaning of the sentence while reducing stylistic properties. Then adversarial generation techniques are used to make the output match the desired style. We evaluate this technique on three different style transformations: sentiment, gender and political slant. Compared to two state-of-the-art style transfer modeling techniques we show improvements both in automatic evaluation of style transfer and in manual evaluation of meaning preservation and fluency.
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여러 논문들에서 참조가 되고 있는 back-translation 기법입니다. 이 기법이 어떻게 이루어 져 있는지 알아 볼 수 있습니다.
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Abstract (요약) 🕵🏻♂️
Style transfer is the task of rephrasing the text to contain specific stylistic properties without changing the intent or affect within the context. This paper introduces a new method for automatic style transfer. We first learn a latent representation of the input sentence which is grounded in a language translation model in order to better preserve the meaning of the sentence while reducing stylistic properties. Then adversarial generation techniques are used to make the output match the desired style. We evaluate this technique on three different style transformations: sentiment, gender and political slant. Compared to two state-of-the-art style transfer modeling techniques we show improvements both in automatic evaluation of style transfer and in manual evaluation of meaning preservation and fluency.
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레퍼런스의 URL을 알려주세요! 🔗
https://www.aclweb.org/anthology/P18-1080.pdf