Nissan Seminar: Deciphering pre-modern Japanese manuscripts: kuzushiji recognition systems and AI

Convener(s): Professor Jennifer Guest and Dr Chigusa Yamaura

Speaker(s): Dr Tarin Clanuwat, Project Assistant Professor, ROIS-DS Center for Open Data in the Humanities

These seminars will occur live and will not be recorded. Unauthorized recording is strictly prohibited.

Please click on the seminar title to register in advance and receive the meeting details.

“Deciphering premodern Japanese manuscripts: kuzushiji recognition systems and AI”

Abstract: Reading kuzushiji (cursive script) is an essential skill for the study of premodern Japan, but gaining kuzushiji proficiency can be a challenge. This talk will offer a brief introduction to approaches to learning how to decipher kuzushiji. Dr. Clanuwat will demonstrate how to use KuroNet, an artificial intelligence based kuzushiji recognition system used to transcribe premodern Japanese documents. She will also discuss current limitations and future possibilities in kuzushiji recognition systems. Finally she will introduce the Kuzushiji recognition smartphone app “Miwo”. The name “Miwo” comes from the fourteenth chapter of The Tale of Genji , “Miwotsukushi”, referring to waterway markers. Just as the Miwotsukushi is a guide for boats in the sea, the Miwo app aims to act as a guide for reading kuzushiji materials

Dr. Tarin Clanuwat is a project assistant professor at ROIS-DS Center for Open Data in the Humanities. She received her PhD from the Graduate school of Letters Arts and Sciences at Waseda University, where she specialized in Kamakura-era Tale of Genji commentaries. In 2018, she developed an AI-based kuzushiji recognition model called KuroNet. In 2019, she hosted a Kaggle machine learning competition for kuzushiji recognition which attracted over 300 machine learning researchers and engineers from around the world. Her AI and kuzushiji research won the Information Processing Society of Japan Yamashita Memorial Research Award. Her Kuzushiji recognition smartphone application won the ACT-X AI Powered Innovation and Creation research grant from Japan Science and Technology Agency.