| Project/Area Number |
22K00510
|
|---|
| Research Category |
Grant-in-Aid for Scientific Research (C)
|
| Allocation Type | Multi-year Fund |
|---|
| Section | 一般 |
|---|
| Review Section |
Basic Section 02060:Linguistics-related
|
|---|
| Research Institution | The University of Aizu |
|---|
Principal Investigator |
Perkins Jeremy 会津大学, コンピュータ理工学部, 上級准教授 (30725635)
|
|---|
| Project Period (FY) |
2022-04-01 – 2026-03-31
|
| Project Status |
Granted (Fiscal Year 2022)
|
| Budget Amount *help |
¥1,950,000 (Direct Cost: ¥1,500,000、Indirect Cost: ¥450,000)
Fiscal Year 2025: ¥390,000 (Direct Cost: ¥300,000、Indirect Cost: ¥90,000)
Fiscal Year 2024: ¥260,000 (Direct Cost: ¥200,000、Indirect Cost: ¥60,000)
Fiscal Year 2023: ¥650,000 (Direct Cost: ¥500,000、Indirect Cost: ¥150,000)
Fiscal Year 2022: ¥650,000 (Direct Cost: ¥500,000、Indirect Cost: ¥150,000)
|
|---|
| Keywords | peak delay / pitch accent / f0 / consonant f0 effects / cue conflicts |
|---|
| Outline of Research at the Start |
This research investigates whether pitch accent peak delay occurs in Tokyo Japanese words with voiced consonants. Peak delay occurs after voiced consonants in Kyungsang Korean, which like Tokyo Japanese, has pitch accent. However, in Kyungsang Korean, pitch also plays an important role in distinguishing consonants in addition to pitch accent. On the other hand, in Tokyo Japanese, pitch does not play as important a role in distinguishing consonants compared to Kyungsang Korean. As such, if peak delay is observed in Tokyo Japanese, it may occur to a lesser degree and less consistently.
|
| Outline of Annual Research Achievements |
The research was delayed by one year because of a previous project, which was itself delayed by one year due to COVID-19. The previous research project was concluded successfully, with Korean data collected and analyzed. Two papers were written from these results, both accepted for publication and presentation at ICPhS 2023 in Prague. The first paper was an acoustic analysis of the plain and tense fricatives, showing that release duration and spectral tilt differed; also, psychoacoustic roughness was analyzed, showing that it performed equally well as spectral tilt in identifying Korean tense obstruents. The second paper was written jointly with Prof. Yu Yan, a Computer Scientist whose knowledge on machine learning allowed us to use the random forest machine learning technique to test which acoustic cues were necessary and sufficient to identify the three Korean obstruent types (tense, lax and aspirated).
|
| Current Status of Research Progress |
Current Status of Research Progress
4: Progress in research has been delayed.
Reason
The previous project was delayed due to COVID-19 and so 2022 was spent working on it, instead of this project.
|
| Strategy for Future Research Activity |
I plan to start preparing for data collection of Tokyo Japanese and Fukushima Japanese speakers in June and July 2023.
|
