Host: The Japanese Society for Artificial Intelligence
Name : The 33rd Annual Conference of the Japanese Society for Artificial Intelligence, 2019
Number : 33
Location : [in Japanese]
Date : June 04, 2019 - June 07, 2019
Reading ancient documents is one of fundamental works on the study of national literature. However, due to the use of kuzushi-ji (classical cursive handwriting characters) in the ancient documents, it requires a lot of knowledge and labor to read. This paper uses an End-to-End method with attention mechanism to recognize the continuous kuzushi-ji in phrases. Compared with the traditional recognition model with Connectionist Temporal Classification (CTC), our approach can get higher accuracy of recognition. The method can recognize phrases written by kana (47 different characters) with the accuracy 78.92% and recognize phrases containing both kanji (63 different characters) and kana with accuracy 59.80%.
