| Summary: | 碩士 === 國立臺灣大學 === 資訊工程學研究所 === 107 === Natural language generation has been a popular field with lots of quality works published based on generative adversarial network (GAN) or varia- tional autoencoder (VAE). However, rephrasing with condition is a problem that few people focus on. In this work, the problem is formally defined as ”rephrase a sentence with given condition, and the generated sentence should be similar to the origin sentence and it should satisfy the given condition”. Moreover, we propose a conditional model based on sentence-VAE to solve the problem. The model is trained as an autoencoder, but we can control the condition of the generated sentence. And, it inherits the nature of autoencoder that the generated sentences would be similar to the input sentence. With experiment results supported, the model can solve the problem with quality sentences.
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