开发和评估一个语音与噪音比率反系统的开发和评估
概括
这项研究引入了一种新的语音与噪音比率反 (SNF) 系统,以帮助患有帕金森病 (PD) 的患者提高声高. 该系统有效地提高了用户的语音强度,在杂的环境中增强了沟通.
科学领域:
- 神经学 神经学
- 语音语言病理学 语言病理学
- 生物医学工程 生物医学工程
背景情况:
- 帕金森病 (PD) 经常导致声高降低,损害语音可理解性,特别是在杂的环境中.
- 对于患有PD的人来说,有效的沟通至关重要,但低听力症却是一个重大挑战.
研究的目的:
- 为患有帕金森病的人开发和评估辅助语音与噪音比率反 (SNF) 系统.
- 在具有挑战性的声学环境中增强声响和语音可理解性.
主要方法:
- 使用双耳麦克风和移动应用程序开发实时SNF系统.
- 实现基于连贯性的自己的语音检测 (OVD) 和语音信号噪声比 (SNR) 估计算法.
- 通过在各种环境条件下进行电声学和主观测试来评估性能.
主要成果:
- 通过适当的值设置,OVD算法成功地将用户的声音与背景噪声区分开来.
- 主观测试证实,SNF系统在操作过程中显著增加了用户的语音强度.
- 该系统在各种环境条件下证明了其有效性.
结论:
- 开发的SNF系统是一个可行的辅助工具,用于患有帕金森病的个体,他们经历了声音的降低.
- 实时SNR反可以有效地促使用户增加语音强度,从而改善沟通.
- 这项技术有望提高PD患者的生活质量.
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