Abstract
This study examines how differences in human vocabulary affect reading time. Specifically, we assumed vocabulary to be the random effect of research participants when applying a generalized linear mixed model to the ratings of participants in the word familiarity survey. Thereafter, we asked the participants to take part in a self-paced reading task to collect their reading times. Through fixed effect of vocabulary when applying a generalized linear mixed model to reading time, we clarified the tendency that vocabulary differences give to reading time.- Anthology ID:
- 2022.lrec-1.555
- Volume:
- Proceedings of the Thirteenth Language Resources and Evaluation Conference
- Month:
- June
- Year:
- 2022
- Address:
- Marseille, France
- Editors:
- Nicoletta Calzolari, Frédéric Béchet, Philippe Blache, Khalid Choukri, Christopher Cieri, Thierry Declerck, Sara Goggi, Hitoshi Isahara, Bente Maegaard, Joseph Mariani, Hélène Mazo, Jan Odijk, Stelios Piperidis
- Venue:
- LREC
- SIG:
- Publisher:
- European Language Resources Association
- Note:
- Pages:
- 5178–5187
- Language:
- URL:
- https://aclanthology.org/2022.lrec-1.555
- DOI:
- Cite (ACL):
- Masayuki Asahara. 2022. Reading Time and Vocabulary Rating in the Japanese Language: Large-Scale Japanese Reading Time Data Collection Using Crowdsourcing. In Proceedings of the Thirteenth Language Resources and Evaluation Conference, pages 5178–5187, Marseille, France. European Language Resources Association.
- Cite (Informal):
- Reading Time and Vocabulary Rating in the Japanese Language: Large-Scale Japanese Reading Time Data Collection Using Crowdsourcing (Asahara, LREC 2022)
- PDF:
- https://preview.aclanthology.org/nschneid-patch-2/2022.lrec-1.555.pdf
- Code
- masayu-a/bccwj-spr2
- Data
- Natural Stories