Feature visualizer and detector for scientific texts
| Project/Area Number |
19K00850
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| Research Category |
Grant-in-Aid for Scientific Research (C)
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| Allocation Type | Multi-year Fund |
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| Section | 一般 |
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| Review Section |
Basic Section 02100:Foreign language education-related
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| Research Institution | The University of Aizu |
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Principal Investigator |
Blake John 会津大学, コンピュータ理工学部, 上級准教授 (80635954)
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| Co-Investigator(Kenkyū-buntansha) |
Mozgovoy Maxim 会津大学, コンピュータ理工学部, 上級准教授 (60571776)
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| Project Period (FY) |
2019-04-01 – 2023-03-31
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| Project Status |
Completed (Fiscal Year 2022)
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| Budget Amount *help |
¥3,900,000 (Direct Cost: ¥3,000,000、Indirect Cost: ¥900,000)
Fiscal Year 2021: ¥1,300,000 (Direct Cost: ¥1,000,000、Indirect Cost: ¥300,000)
Fiscal Year 2020: ¥1,300,000 (Direct Cost: ¥1,000,000、Indirect Cost: ¥300,000)
Fiscal Year 2019: ¥1,300,000 (Direct Cost: ¥1,000,000、Indirect Cost: ¥300,000)
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| Keywords | scientific writing / genre awareness raising / rhetorical features / language features / information structure / pedagogic tool / feature visualisation / genre awareness / NLP / visualization / grammatical explanations / contextualized grammar / academic writing / language processing / feature extraction / tense identification / feature visualization / lexical patterns / grammatical patterns / genre / nlp / iCALL |
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| Outline of Research at the Start |
This research aims to develop and evaluate an interactive online multimedia tool that can visualize the typical language features in scientific texts written in English. There are two functionalities. (1) The feature visualizer shows and explains commonly-used language features present in a corpus of fully-annotated short research articles. (2) The feature detector identifies core language features in texts submitted by users. This helps students compare their own writing to expected conventions in scientific writing.
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| Outline of Final Research Achievements |
We have developed Feature Detection and Feature Visualization tools. The Feature Visualization tool comprises an annotated dataset of short research articles and a bank of multimodal materials which are displayed in the user interface of the Feature Visualizer. Here users can visualize particular rhetorical or language aspects, e.g. modality, tense and cohesion. Users then have the option to display additional multimodal explanations to understand the specific rhetorical or language features. In addition, two Feature Detection tools were created that can process student-submitted work. The first colorizes finite verb phrases according to one of twelve pedagogic tenses. The main feature detection tool enables users to gain feedback on deep grammatical features, namely information structure. The end weight, the information focus and information flow are automatically annotated, helping learners differentiate between unmarked, highly frequent usage and marked, rare usage.
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| Academic Significance and Societal Importance of the Research Achievements |
The primary aim of this project is to develop an online resource that could assist Japanese writers of short research articles in the field of computer science to understand the prototypical generic features in such articles. This is envisaged to help them climb the cline of competence more quickly.
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Report
(5 results)
Research Products
(11 results)
