文章自動生成の主な手法における非構造データ量と処理時間についての一考察

抄録

Recent developments in deep learning have been remarkable, from the field of image processing to the field of speech recognition and natural language processing has been penetrated and developed. In this study, we first picked up the following three main approaches to implement sentence generation. 1) Markov chain, 2) automatic summary, 3) sentence generation by deep learning (RNN / LSTM / GAN). As a subject, it was commonly seen that the connection between sentence and sentence was unnatural. We tried the connection between natural sentences and sentences which are also applicable in practice by the above three methods and considered countermeasures.