Summary of the paper

Title Sudachi: a Japanese Tokenizer for Business
Authors Kazuma Takaoka, Sorami Hisamoto, Noriko Kawahara, Miho Sakamoto, Yoshitaka Uchida and Yuji Matsumoto
Abstract This paper presents Sudachi, a Japanese tokenizer and its accompanying language resources for business use. Tokenization, or morphological analysis, is a fundamental and important technology for processing a Japanese text, especially for industrial applications. However, we often face many obstacles for Japanese tokenization, such as the inconsistency of token unit in different resources, notation variations, discontinued maintenance of the resources, and various issues with the existing tokenizer implementations. In order to improve this situation, we develop a new tokenizer and a dictionary with features such as multi-granular output for different purposes and normalization of notation variations. In addition to this, we are planning to continuously maintain our software and resource in long-term as a part of the company business. We release the resulting tokenizer software and language resources freely available to the public as an open source software. You can access them at
Topics Industrial Systems
Full paper Sudachi: a Japanese Tokenizer for Business
Bibtex @InProceedings{TAKAOKA18.8884,
  author = {Kazuma Takaoka and Sorami Hisamoto and Noriko Kawahara and Miho Sakamoto and Yoshitaka Uchida and Yuji Matsumoto},
  title = "{Sudachi: a Japanese Tokenizer for Business}",
  booktitle = {Proceedings of the Eleventh International Conference on Language Resources and Evaluation (LREC 2018)},
  year = {2018},
  month = {May 7-12, 2018},
  address = {Miyazaki, Japan},
  editor = {Nicoletta Calzolari (Conference chair) and Khalid Choukri and Christopher Cieri and Thierry Declerck and Sara Goggi and Koiti Hasida and Hitoshi Isahara and Bente Maegaard and Joseph Mariani and Hélène Mazo and Asuncion Moreno and Jan Odijk and Stelios Piperidis and Takenobu Tokunaga},
  publisher = {European Language Resources Association (ELRA)},
  isbn = {979-10-95546-00-9},
  language = {english}
Powered by ELDA © 2018 ELDA/ELRA