Development of Language Ability Measurement System (KOTOBAKARI) using Voice Recognition
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- Miyabe Mai
- Faculty of Business Administration and Information, Tokyo University of Science, Suwa
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- Shikata Shuko
- Graduate School of Human and Environmental Studies, Kyoto University
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- Kubo Kay
- Center for Japanese Language and Culture, Osaka University
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- Aramaki Eiji
- Center for Frontier Science and Technolopgy, Nara Institute of Science and Technology
Bibliographic Information
- Other Title
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- 音声認識を用いた言語能力自動測定システム“言秤”の構築
- オンセイ ニンシキ オ モチイタ ゲンゴ ノウリョク ジドウ ソクテイ システム"ゲンハカリ"ノ コウチク
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Abstract
<p>There is a growing need for automatic measurements of language ability. With increase in the aging population, the number of older adults with dementia is expected to increase. Language disorder is considered one of the most fundamental symptom with which dementia can be detected. The identification of language defects particular to dementia symptoms may contribute to the early detection of dementia. Currently, many foreign students learn Japanese at educational institutions, which are required to provide appropriate evaluations to their students. However, differences occur because evaluators judge the language abilities of foreign students subjectively. The measured results from an automatic language ability measurement system could be used for objective evaluations. Although traditional studies manually measured language abilities, such methods are often costly. In this study, we propose the automatic language ability measurement system, “KOTOBAKARI,” as an alternative to traditional manual measurement methods. This system is expected to reduce the cost and time of measuring the language ability using the following steps: (1) voice recognition to obtain text data and (2) quantitative indicators for automated language ability measurement. We verify the capacity of voice recognition to measure language ability by comparing language ability to a threshold value and by assessing language ability score changes. The experimental results show that it is difficult to judge language ability by threshold value comparison, using our system. On the contrary, the language ability score of some individuals, measured with our system, was correlated with the correct score. This result indicates that these individuals can use our system to assess language ability changes by continuous measurements. </p>
Journal
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- Journal of Natural Language Processing
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Journal of Natural Language Processing 25 (1), 33-56, 2018-02-15
The Association for Natural Language Processing
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Details
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- CRID
- 1390282679453451136
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- NII Article ID
- 130006734202
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- NII Book ID
- AN10472659
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- ISSN
- 21858314
- 13407619
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- NDL BIB ID
- 028852227
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- Text Lang
- ja
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- Data Source
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- JaLC
- NDL
- Crossref
- CiNii Articles
- KAKEN
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- Abstract License Flag
- Disallowed