2011 Fiscal Year Final Research Report
Self-initiated Communication Learning Mechanism by Integrating Situation, Image, and Language
Project/Area Number |
22650026
|
Research Category |
Grant-in-Aid for Challenging Exploratory Research
|
Allocation Type | Single-year Grants |
Research Field |
Intelligent informatics
|
Research Institution | Kyoto University |
Principal Investigator |
NISHIDA Toyoaki 京都大学, 大学院・情報学研究科, 教授 (70135531)
|
Research Collaborator |
大本 義正
岡田 将吾
YASSER Mohammad
名渕 博人
伊豆蔵 拓也
坂本 佳愛
|
Project Period (FY) |
2010 – 2011
|
Keywords | 学習 / 知識獲得 / 言語・非言語コミュニケーション |
Research Abstract |
This research addresses fundamental aspects of a self-initiated mechanism for learning verbal-nonverbal communication integrating situations, images, and language. The result consists of the architecture for empathic agents, a method for extracting verbal-nonverbal associations from multi-modal interaction data and its application to creating agent communication behavior patterns, learning instruction patterns and task structure by incremental acquisition of behavior rules, and algorithms for self-initiated learning by mimicking.
|
-
-
-
-
-
-
-
-
-
-
-
-
-
[Remarks] 受賞December 21, 2011. Yasser Mohammad and Toyoaki Nishida received SII2011 Best Paper Award(Control) from 2011 IEEE/SICE International Symposium on System Integration, December 20-22, 2011, Kyoto Japan. Yasser Mohammad and Toyoaki Nishida, On Comparing SSA-based Change Point Discovery Algorithms, IEEE SII 2011, 938-945.