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Research of Emotion and Intention Understanding Based on Human Action Analysis and Its Application to Man-machine Communication

Research of Emotion and Intention Understanding Based on Human Action Analysis and Its Application to Man-machine Communication
基于人类行为分析的情感和意图理解研究及其在人机交流中的应用
批准号:
14208037
负责人:
ARIKI Yasuo
金额:
$32.36万
依托单位国家:
日本
项目类别:
Grant-in-Aid for Scientific Research (A)
财政年份:
2002
资助国家:
日本
项目状态:
已结题
起止时间:
2002 至 2004

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中文摘要
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英文摘要
In order to realize symbiotic machines with human beings, we studied a communication method focusing on body action habits and the inside emotion, based on data mining, image recognition, speech recognition and emotion information processing.1 Studies on rule discovery from motion data and quality analysis of emotion (Uehara)It is difficult to retrieve the motion data unless the human action is organized or structured in terms of their contents when the large amount of motion data is stored like digital archives. To solve this problem, motion data is presented as motion locus in the three-dimensional space, and the motion speed and the posture are analyzed. Through this analysis, we compared the motion skills and discovered the features of high degree of skills. Using the action data captured by the motion capture system Eva, we extracted the intrinsic features of the respective motion and the distinguished features compared with other motions.2 Intention understanding by integrating human action, emotion, speech and image recognition (Ariki, Kumano)It is possible to analyze intentions in terms of how it is expressed with action, speech, image and emotion through the studies of action, speech, image and emotion integration. From this point, we especially analyzed the intention based on the action and emotion. For example, when a user asks by speaking who is he and by pointing his face displayed on the large screen in the room like a classroom, the system integrates the speech recognition, pointing action and face recognition. We also analyzed the emotion to estimate the intention.
期刊论文(44)
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会议论文
Masayuki Nakamura: "Improvement of Boosting Algorithm by Modifying the Weighting Rule"Annals of Mathematics and Artificial Intelligence, Kluwer Academic Publishers. (未定). (2004)
Masayuki Nakamura:“通过修改加权规则改进增强算法”,《数学与人工智能年鉴》,Kluwer 学术出版社(待定)。
DOI: --
发表时间:
期刊:
影响因子: --
作者: []
通讯作者:
DOI: 10.1023/b:amai.0000018577.32783.d2
发表时间: 2004-05
期刊: Annals of Mathematics and Artificial Intelligence
影响因子: 1.2
作者: [Masayuki Nakamura;Hiroki Nomiya;K. Uehara]
通讯作者: Masayuki Nakamura;Hiroki Nomiya;K. Uehara
Combination of GMM Based Speech Estimation Method and Temporal Domain SVD Based Speech Enhancement for Noise Robust Speech Recognition
基于 GMM 的语音估计方法和基于时域 SVD 的语音增强相结合用于噪声鲁棒语音识别
DOI: --
发表时间: 2005
期刊: IEICE Transactions on Information and Systems Vol.J88-D-II, No.2
影响因子: --
作者: [M.Harada, T.Nagao ほか全9名, Masakiyo Fujimoto]
通讯作者: Masakiyo Fujimoto
STRUCTURING BASEBALL LIVE GAMES BASED ON SPEECH RECOGNITION USINGTASK DEPENDENT KNOWLEDGE AND EMOTION STATE RECOGNITION
使用任务相关知识和情绪状态识别基于语音识别构建棒球现场比赛
DOI: --
发表时间: 2005
期刊: International Conference on Acoustics, Speech and Signal Processing (ICASSP2005)
影响因子: --
作者: [C.Matsuoka, K.Nishihara, Masahito Kumano, Atsushi Sako]
通讯作者: Atsushi Sako
44
    Object Recognition by Deep Neural Network with Knowledge Graph Embedding - Proposal for Semantic Object Projection -
    • 批准号:
      17K00236
    • 项目类别:
      Grant-in-Aid for Scientific Research (C)
    • 资助金额:
      $2.91万
    • 财政年份:
      2017
    • 负责人:
      ARIKI Yasuo
    • 依托单位:
    Study on Human-Machine Communication and Learning through Content-Awareness
    • 批准号:
      26280059
    • 项目类别:
      Grant-in-Aid for Scientific Research (B)
    • 资助金额:
      $8.99万
    • 财政年份:
      2014
    • 负责人:
      ARIKI Yasuo
    • 依托单位:
    Study on Language generation and learning from videos
    • 批准号:
      24650084
    • 项目类别:
      Grant-in-Aid for Challenging Exploratory Research
    • 资助金额:
      $2.41万
    • 财政年份:
      2012
    • 负责人:
      ARIKI Yasuo
    • 依托单位:
    海外基金