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科学领域:

  • 可穿戴技术是可穿戴的技术.
  • 声学感应 声学感应 声学感应
  • 人与计算机的互动.

背景情况:

  • 语音通信至关重要,但易受噪音和环境干扰的影响.
  • 现有的语音识别方法在具有挑战性的声学条件下扎.
  • 需要先进的传感器可靠的语音捕获和交互.

研究的目的:

  • 开发一种可穿戴的,无线的,灵活的皮肤附着声学传感器 (SAAS),用于强大的语音识别.
  • 在恶劣的声学环境中实现人机交互 (HMI).
  • 提高语音识别系统的准确性和可靠性.

主要方法:

  • 使用压电微加工超声波传感器 (PMUT) 进行高灵敏度和宽带宽传感.
  • 采用灵活的包装,以提高可穿戴性和适应性.
  • 将传感器数据与剩余网络 (ResNet) 深度学习架构集成,用于语音特征分类.

主要成果:

  • 该SAAS系统表现出高灵敏度 (-198 dB) 和宽带宽 (10 Hz-20 kHz).
  • 使用ResNet架构,喉语音特征分类准确度超过96%.
  • 完整的语音识别系统在识别日常句子时达到99.8%的准确性.

结论:

  • 在杂的环境中,SAAS为语音识别和HMI提供了可行的解决方案.
  • 传感器系统表现出稳定的性能,易于集成和低成本.
  • 在语音控制,先进的HMI和可穿戴电子产品方面,SAAS具有显著的应用潜力.