期刊
EXPERT SYSTEMS
卷 32, 期 6, 页码 688-697出版社
WILEY
DOI: 10.1111/exsy.12106
关键词
speech spectrum; linear prediction; relative spectra analysis; cepstral analysis; Parkinson's disease
资金
- COLCIENCIAS [111556933858]
- CODI at Universidad de Antioquia
About 1% of people older than 65years suffer from Parkinson's disease (PD) and 90% of them develop several speech impairments, affecting phonation, articulation, prosody and fluency. Computer-aided tools for the automatic evaluation of speech can provide useful information to the medical experts to perform a more accurate and objective diagnosis and monitoring of PD patients and can help also to evaluate the correctness and progress of their therapy. Although there are several studies that consider spectral and cepstral information to perform automatic classification of speech of people with PD, so far it is not known which is the most discriminative, spectral or cepstral analysis. In this paper, the discriminant capability of six sets of spectral and cepstral coefficients is evaluated, considering speech recordings of the five Spanish vowels and a total of 24 isolated words. According to the results, linear predictive cepstral coefficients are the most robust and exhibit values of the area under the receiver operating characteristic curve above 0.85 in 6 of the 24 words.
作者
我是这篇论文的作者
点击您的名字以认领此论文并将其添加到您的个人资料中。
推荐
暂无数据