2004 Fiscal Year Final Research Report Summary
Study on Probabilistic Control Mechanism for Establishing Harmonic Cognitive State between Human and Systems
| Project/Area Number |
14208033
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| Research Category |
Grant-in-Aid for Scientific Research (A)
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| Allocation Type | Single-year Grants |
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| Section | 一般 |
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| Research Field |
Intelligent informatics
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| Research Institution | NATIONAL INSTITUTE OF ADVANCED INDUSTRIAL SCIENCE AND TECHNOLOGY |
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Principal Investigator |
ASOH Hideki National Institute of Advanced Industrial Science and Technology, Information Technology Research Institute, Senior Research Scientist, 情報技術研究部門, 主任研究員 (10344194)
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| Co-Investigator(Kenkyū-buntansha) |
ASANO Futoshi National Institute of Advanced Industrial Science and Technology, Information Technology Research Institute, Group Leader, 情報技術研究部門, 研究グループ長 (00231895)
MOTOMURA Yoichi National Institute of Advanced Industrial Science and Technology, Digital Human Research Center, Senior Research Scientist, デジタルヒューマン研究センター, 主任研究員 (30358171)
AKIBA Tomoyoshi Toyohashi University of Technology, Department of Information and Computer Sciences, Associate Professor, 情報工学系, 助教授 (00356346)
ITOU Katsunobu Nagoya University, Department of Media Science, Graduate School of Information Science, Associate Professor, 工学部, 助教授 (30356472)
HAYAMIZU Satoru Gifu University, Department of Information Science, Graduate School of Engineering, Professor, 工学部, 教授 (90345794)
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| Project Period (FY) |
2002 – 2004
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| Keywords | Human Interface / Dialog System / Dialog Control / Probabilistic Inference / Bayesian Network / Cognitive Harmonic State |
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| Research Abstract |
We conducted research aiming to establish harmonic cognitive state between human and information systems based on statistical techniques, and achieved the following results.
1.We proposed a statistical method of detecting and tracking moving users' speech events using a microphone array,. The method was evaluated with data acquired in real office environment 85% correct rate for speech interval estimation was achieved.
2.We proposed a method of modeling users' utterances in the question answering task which include fixed phrases. We applied the proposed method to a speech-driven question answering system and confirmed that the accuracy of recognizing spoken questions and the task achievement rate were improved significantly. We also proposed a method to collect spontaneously spoken queries for speech-driven information retrieval systems. Using the method we collected spoken queries under the task of NTCIR-3 and NTCIR-4 information retrieval.
3.We proposed a statistical method of estimating users' knowledge level for interactive visitor guide systems. We collected dialog data for 12 users through the Wizard of Oz method. We evaluated the performance of the estimation method for the problem of discriminating users into 4 classes. The correct rate about 87% was achieved.
4.We collected natural spoken dialog of 20 users for the task of controlling home electronic systems. We transcribed and labeled the speech data. These result supports that the statistical methods based on dynamic Bayesian networks are effective for estimating users' status in the various interaction tasks. Future works include improving the estimation methods and evaluating with collected data in detail, investigating the way of using the estimated state for systems decision making and answering, and constructing various dialog systems.
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Research Products
(26 results)
