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此摘要是机器生成的。

本研究介绍了一个强大的语音命令识别系统,用于工业4.0.0. 该框架提高了准确性和噪声排斥,改善了生产线上的人机交互.

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科学领域:

  • 人与机器人的交互
  • 工业自动化 工业自动化
  • 语音技术 语言技术

背景情况:

  • 语音是人机交互 (HRI) 中的一个关键沟通道.
  • 工业4.0环境需要高效准确的语音命令识别.
  • 挑战包括平衡命令准确性与噪音和不相关的语音拒绝.

研究的目的:

  • 提出一个模块化框架,以优化语音命令识别在工业环境中的准确性和稳定性.
  • 尽量减少对广泛的工业数据集的需求.
  • 在杂的生产线环境中提高可靠性.

主要方法:

  • 开发了一种高效的指挥识别模块,使用实验室数据与合成样本进行增强.
  • 实现了对上下文敏感的数据增强和动态噪声注入,以获得稳定性.
  • 集成了一个关键词发现模块,在检测到预定义的关键词时激活识别.

主要成果:

  • 该系统在命令识别和噪声拒绝方面都显示出高回忆率.
  • 使用来自杂工业环境的真实世界样本进行评估.
  • 在苛刻的工业应用中得到证实的有效性.

结论:

  • 拟议的模块化框架有效地解决了在工业4.0中的语音命令识别挑战.
  • 该系统在准确性和噪声排斥方面实现了高性能.
  • 这种方法提高了工业生产线的生产率和效率.