Research off skill acquisition methods based on a schematization of bodily movement

基于身体运动图化的技能习得方法研究

• 批准号: 17500090
• 负责人: FUJINAMI Tsutomu
• 金额: $ 2.43万
• 依托单位: Japan Advanced Institute of Science and Technology
• 依托单位国家: 日本
• 项目类别: Grant-in-Aid for Scientific Research (C)
• 财政年份: 2005
• 资助国家: 日本
• 起止时间: 2005 至 2007
• 项目状态: 已结题
• 来源: https://kaken.nii.ac.jp/grant/KAKENHI-PROJECT-17500090/
• 关键词: Skill Acquisition; Expert; クラシック音楽; 歌唱; 身体技能; ダンス; 演奏; サンバ; サッカー; リズム; スキルサイエンス; 身体知

We have investigated how better we can give the learner some feedbacks on his or her bodily movements by controlling the granulity of instructions. We separated the subjects into three groups for our experiment to train them differently. The task was to learn to play a samba rhythm with shaker. The first group could know how close their arm movements are to the ones of an expert by referring to the auto correlation functions of their arm movements. The second group was only told whether their arm movements are correct. The third and last group was not given any feedback. As the result, the first group showed significantly better performance than the third one. The second group however showed no significant difference from the third one. We conclude that the direction in addition to the judgment helps the learner to master the skill. We have also investigated the vocal skill. We employed a professional singer specialized in classic music and asked her to sing differently. We found the vibration of her body to be significantly strong compared to the one when she sings without professional skills. We expect that it will greatly help the leaner acquire the vocal skill to show her the spectrum graph.

我们研究了如何通过控制指令的粒度来更好地向学习者提供有关其身体动作的反馈。我们将实验对象分为三组，对他们进行不同的训练。任务是学习用shaker演奏桑巴节奏。第一组可以通过参考手臂动作的自相关函数来知道自己的手臂动作与专家的手臂动作有多接近。第二组只被告知他们的手臂动作是否正确。第三组也是最后一组没有得到任何反馈。结果，第一组的表现明显优于第三组。然而，第二组与第三组没有显着差异。我们的结论是，除了判断之外，指导也有助于学习者掌握技能。我们还研究了发声技巧。我们聘请了一位专门研究古典音乐的专业歌手，并要求她以不同的方式演唱。我们发现，与她没有专业技能唱歌时相比，她身体的震动明显强烈。我们期望向学习者展示频谱图将极大地帮助学习者掌握发声技巧。

项目成果

Online Sensor Selection in Reinforcement Learning Environment

强化学习环境中的在线传感器选择

• DOI: 10.1541/ieejeiss.125.870
• 发表时间: 2005
• 作者: K. Ishikawa;Akito Sakurai;Tsutomu Fujinami;S. Kunifuji
• 通讯作者: S. Kunifuji

身体知創造に対する日本的アプローチ

日本的物理知识创造方法

• 发表时间: 2008
• 作者: Rameswer;Debnath;M.;Muramatsu;Haruhisa;Takahashi;藤波 努
• 通讯作者: 藤波 努

The Effect of American Football's Throwing on Pitting Forms in Baseball

美式橄榄球投掷对棒球进洞形式的影响

• 发表时间: 2006
• 作者: Kensaku;Aoyama;Daisuke Ichikwa;Tsutomu Fujinami
• 通讯作者: Tsutomu Fujinami

技の研究と人工知能

技术研究和人工智能

• 发表时间: 2006
• 作者: Kohei;Ishikawa;Tomoyuki;Yamamoto;Tsutomu;Fujinami;藤波 努
• 通讯作者: 藤波 努

Hierarchical organisation of coordinative structure in the skill of kneading

揉捏技艺协调结构的层次组织

• 发表时间: 2007
• 期刊: The 8^<th> Motor Control and Human Skill Conference N/A
• 作者: K.;Furukawa;古川 康一;Kohei Matsumura;T.Yamamoto
• 通讯作者: T.Yamamoto