定制智能手机声学处理算法与健康和失调声音中的Prat之间的比较
Andres F Llico1, Savannah N Shanley2, Aaron D Friedman3
1Department of Biomedical Engineering, University of Cincinnati, Cincinnati, Ohio.
Journal of voice : official journal of the Voice Foundation
|September 10, 2023
概括
智能手机算法在语音分析方面与Pratt有很强的共识,但对于严重失声的声音,建议谨慎,因为在平均基本频率 (fo) 和最大发音时间 (MPT) 测量中可能存在错误.
科学领域:
- 语音科学是一种语言科学.
- 声学分析 声学分析
- 数字健康数字健康
背景情况:
- 声学语音分析对于诊断和监测声学病理至关重要.
- 传统的分析依赖于专门的软件,如Praat.
- 移动技术为可访问的语音评估提供了潜力.
研究的目的:
- 将来自自定义智能手机算法的声学测量与Prat.的测量进行比较.
- 为了评估智能手机算法的准确性,在一系列的声音病理.
主要方法:
- 从56名成年人 (健康和失声) 收集了语音样本,他们执行了持续的元音,最大音调和彩虹段落任务.
- 使用Prat和智能手机算法提取了平均基本频率 (fo),最大发声时间 (MPT) 和 cepstral峰值突出度 (CPP).
- 使用线性回归来评估关系并确定异常值.
主要成果:
- 在智能手机和Praat措施之间观察到高相关性 (r2 = 0.68-0.98).
- 在塞普斯特拉峰值突出度 (CPP) 值中发现了一致的偏移.
- 智能手机算法显示,在严重失声的声音中,平均fo和MPT的准确性降低了.
结论:
- 拟议的智能手机算法提供了与临床标准可比的测量结果.
- 临床医生应谨慎对待严重失声的声音,因为特定测量的潜在不准确性.
- 为了在所有语音类型中实现最佳性能,需要进一步完善算法.
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