Reading Time and Vocabulary Rating in the Japanese Language: Large-Scale Japanese Reading Time Data Collection Using Crowdsourcing

Masayuki Asahara


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:
Bibkey:
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)
Copy Citation:
PDF:
https://aclanthology.org/2022.lrec-1.555.pdf
Code
 masayu-a/bccwj-spr2
Data
Natural Stories