| Project/Area Number |
19K23361
|
|---|
| Research Category |
Grant-in-Aid for Research Activity Start-up
|
| Allocation Type | Multi-year Fund |
|---|
| Review Section |
0110:Psychology and related fields
|
|---|
| Research Institution | The University of Tokyo |
|---|
Principal Investigator |
Tsuji Sho 東京大学, ニューロインテリジェンス国際研究機構, 講師 (30850490)
|
|---|
| Project Period (FY) |
2019-08-30 – 2021-03-31
|
| Project Status |
Completed (Fiscal Year 2020)
|
| Budget Amount *help |
¥2,860,000 (Direct Cost: ¥2,200,000、Indirect Cost: ¥660,000)
Fiscal Year 2020: ¥1,430,000 (Direct Cost: ¥1,100,000、Indirect Cost: ¥330,000)
Fiscal Year 2019: ¥1,430,000 (Direct Cost: ¥1,100,000、Indirect Cost: ¥330,000)
|
|---|
| Keywords | day-long recordings / language acquisition / supervised learning / unsupervised learning / language structure / social constructivism / 言語発達 |
|---|
| Outline of Research at the Start |
How are infants capable of learning language with a speed and efficiency unrivaled even by state-of-the-art AI systems? Their use of social-communicative cues has been suggested as crucial. However, little is known about the actual composition of infants’ social-communicative environment. The present project measures and analyzes 6-18 months-old infants’ social-communicative input in an ecologically valid setting and assesses its impact on
key language outcomes.
|
| Outline of Final Research Achievements |
The present project aimed to create an infrastructure to measure and analyze infants social-communicative environment across cultures. As a first step, we developed a framework to extract such data from the input in a unified way and to link it to known learning algorithms. As a second step, we proposed to collect infant data and apply our framework. Although we were able to do some pilot data collection, due to the pandemic we were not able to collect a full dataset in Japan. Instead, we moved on to the cross-linguistic part of the project and applied our framework to Tseltal, a language spoken spoken in a smallscale, subsistence farming community in Mexico. These data reveal a high quantity of input that could be used to extract language structure, but less input that would permit the learner to link this structure to events or entities in the surrounding world. Together, this approach will allow us to make precise recommendations for future large-scale empirical research.
|
| Academic Significance and Societal Importance of the Research Achievements |
How infants learn language so well is still an unresolved mystery. Day-long audio recordings offer a glimpse into infants’ environments. We developed an analysis framework for such data, which will allow a better understanding of how environmental cues interact for successful language acquisition.
|
