Automatic Rating of Hoarseness by Text-based Cepstral and Prosodic Evaluation

被引:0
|
作者
Haderlein, Tino [1 ,2 ]
Moers, Cornelia [3 ]
Moebius, Bernd [4 ]
Noeth, Elmar [1 ]
机构
[1] Univ Erlangen Nurnberg, Pattern Recognit Lab Informat 5, Martensstr 3, D-91058 Erlangen, Germany
[2] Univ Erlangen Nurnberg, Dept Phoniatr & Pedaudiol, D-91054 Erlangen, Germany
[3] Univ Bonn, Dept Speech & Commun, D-53115 Bonn, Germany
[4] Univ Saarland, Dept Computat Linguist & Phonet Postfach, D-66041 Saarbrcken, Germany
来源
关键词
CONTINUOUS SPEECH; SUSTAINED VOWELS; VOCAL QUALITY; DYSPHONIA; VOICE; PARAMETERS; SEVERITY;
D O I
暂无
中图分类号
TP18 [人工智能理论];
学科分类号
081104 ; 0812 ; 0835 ; 1405 ;
摘要
The standard for the analysis of distorted voices is perceptual rating of read-out texts or spontaneous speech. Automatic voice evaluation, however, is usually done on stable sections of sustained vowels. In this paper, text-based and established vowel-based analysis are compared with respect to their ability to measure hoarseness and its subclasses. 73 hoarse patients (48.3 +/- 16.8 years) uttered the vowel /e/ and read the German version of the text "The North Wind and the Sun". Five speech therapists and physicians rated roughness, breathiness, and hoarseness according to the German RBH evaluation scheme. The best human-machine correlations were obtained for measures based on the Cepstral Peak Prominence (CPP; up to vertical bar r vertical bar = 0.73). Support Vector Regression (SVR) on CPP-based measures and prosodic features improved the results further to r approximate to 0.8 and confirmed that automatic voice evaluation should be performed on a text recording.
引用
收藏
页码:573 / 580
页数:8
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