乒乓球教练系统基于多式联通大型语言模型,并具有乒乓球知识库
Wenlong Ma1, Yang Liu2, Qing Yi3
1School of Physical Education, Shanghai University of Sport, Shanghai, China.
PloS one
|February 13, 2025
概括
本研究介绍了一种人工智能乒乓球教练系统,该系统使用多模式大语言模型精确指导初学者. 该系统准确地识别了常见的错误,提高了训练效率,促进了运动.
科学领域:
- 运动科学 运动科学 运动科学
- 人工智能的人工智能
- 人与计算机的交互
背景情况:
- 乒乓球是全球流行的一项运动,促进身体和精神健康.
- 开始的乒乓球运动员往往难以识别和纠正常见的错误.
研究的目的:
- 为初学者开发一个人工智能乒乓球教练系统.
- 提供精确的培训指导和匹配策略.
- 利用多模大型语言模型 (MLLMs) 和专门的知识库.
主要方法:
- 使用视觉识别和运动捕捉技术.
- 雇佣了先进的MLLM,与全面的乒乓球知识库相结合.
- 开发了一个准确识别初学者错误的系统.
主要成果:
- 人工智能系统在识别与手臂相关的错误 (73%) 和与球衣相关的错误 (82%) 中取得了高精度.
- 在提供针对常见错误的有针对性的培训指导方面表现出有效性.
结论:
- 人工智能乒乓球教练系统具有成本效益,易于部署.
- 为提高训练效率和运动员表现提供了显著的潜力.
- 未来的工作包括提高脚动作识别和为高级玩家提供服务.
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