2022 Fiscal Year Research-status Report
Natural language generation of trend descriptions for pedagogic purposes
| Project/Area Number |
22K00792
|
|---|
| Research Institution | The University of Aizu |
|---|
Principal Investigator |
BLAKE John 会津大学, コンピュータ理工学部, 上級准教授 (80635954)
|
|---|
| Co-Investigator(Kenkyū-buntansha) |
Pyshkin Evgeny 会津大学, コンピュータ理工学部, 上級准教授 (50794088)
|
|---|
| Project Period (FY) |
2022-04-01 – 2025-03-31
|
| Keywords | NLG / trend descriptions / describing graphs / intelligent CALL |
|---|
| Outline of Annual Research Achievements |
A corpus of trend descriptions was compiled and manually analyzed to identify rhetorical patterns. The initial codebase of the description generator was created. We are still working on enabling examplars and practice descriptions to be generated at three different difficulty levels. An automated workflow incorporating AI-generated video explanations that are moderated by language experts has been trialled. A preliminary set of explanation videos has been created for piloting purposes.
|
| Current Status of Research Progress |
Current Status of Research Progress
2: Research has progressed on the whole more than it was originally planned.
Reason
We have been able to follow our timeline set at the outset. The codebase will continue to be improved throughout the project, but the fundamental design and the core functions has been completed.
|
| Strategy for Future Research Activity |
A more sophisticated combination of rule-based and probabilistic parsing will be used to create a powerful NLG pipeline. This pipeline will draw on published research to provide users with access to cutting-edge research in NLG. At the end of this year, we expect to deploy an online version for testing purposes.
|
| Causes of Carryover |
The difference is only 1,320 yen. This can be used to pay a student worker.
|
Research Products
(6 results)
