[4J1-GS-6d] 言語メディア処理：自然言語処理(1/2)

[4J1-GS-6d-04] Edit Distance Based Curriculum Learning for Style Transfer

〇Sora Kadotani¹, Tomoyuki Kajiwara², Yuki Arase¹, Makoto Onizuka¹ (1. Osaka University, 2. Ehime University)

Keywords:machine translation, deep learning

Style transfer is a natural language processing task that transforms the expressions of an input sentence while retaining the meaning of an input sentence. We attempt to improve the quality of style transfer by using curriculum learning. Curriculum learning is a method that designs a training process starting from easy training samples to difficult training samples. We propose edit distance as a measure to determine the difficulty of transformation. Experiments on formality style transfer showed that our model improves the quality of style transfer.