Detail of Publication
| Text Language | Japanese |
|---|---|
| Authors | Riku Higashimura, Andrew W. Vargo, Motoi Iwata, Koichi Kise |
| Title | Unknown Word Estimation Based on Mobile Learners’ Reading Behavior |
| Journal | FIT2022 |
| Presentation number | CK-002 |
| Number of Pages | 4 pages |
| Location | 慶応義塾大学 矢上キャンパス |
| Reviewed or not | Not reviewed |
| Presentation type | Oral |
| Month & Year | September 2022 |
| Abstract | Vocabulary acquisition is a fundamental component of learning a new language. The widespread use of smartphones allows language learners more flexibility in their daily schedules. In order to acquire new vocabulary, words whose meanings are unknown to the individual learner (hereafter referred to as "unknown words") must be included in the language learning process in some way. A simple method for estimating unknown words in a document is to use the frequency of occurrence, which indicates the difficulty level of the word. However, this method may result in missing unknown words. In this study, we aim to improve the accuracy of unknown word estimation by using reading behavior data obtained from smartphone sensors and taking into account the reading behavior of individual learners. |
- Following files are available.
- Entry for BibTeX
@InCollection{Higashimura2022, author = {Riku Higashimura and Andrew W. Vargo and Motoi Iwata and Koichi Kise}, title = {Unknown Word Estimation Based on Mobile Learners’ Reading Behavior}, booktitle = {FIT2022}, year = 2022, month = sep, presenID = {CK-002}, numpages = {4}, location = {慶応義塾大学 矢上キャンパス} }