Abstract
Fifty-one subjects representing diverse laryngeal etiologies recorded /a/ and /i/ to provide a study sample of 102 vowel sounds. Listeners categorized each vowel on the basis of four voice types (normal, breathy, hoarse, unclassified) and evaluated the degree of vocal abnormality on a 7-point scale. In addition to spectrographic noise (SN) classification, several acoustic measures based on period variability were entered into a multiple regression analysis for the prediction of vocal severity across and within voice types. In general, spectrographic noise and curvilinear derivatives of the period standard deviation (PSD) provided the best predictions of disorder severity. Different variables were the major predictors for different voice types. Several variables used in previous studies were inefficient as predictors of severity.
| Original language | English |
|---|---|
| Pages (from-to) | 230-240 |
| Number of pages | 11 |
| Journal | Journal of Speech and Hearing Research |
| Volume | 30 |
| Issue number | 2 |
| State | Published - Jan 1 1987 |
| Externally published | Yes |
Fingerprint
ASJC Scopus subject areas
- Otorhinolaryngology
Cite this
Prediction of vocal severity within and across voice types. / Wolfe, V. I.; Steinfatt, Thomas.
In: Journal of Speech and Hearing Research, Vol. 30, No. 2, 01.01.1987, p. 230-240.Research output: Contribution to journal › Article
}
TY - JOUR
T1 - Prediction of vocal severity within and across voice types
AU - Wolfe, V. I.
AU - Steinfatt, Thomas
PY - 1987/1/1
Y1 - 1987/1/1
N2 - Fifty-one subjects representing diverse laryngeal etiologies recorded /a/ and /i/ to provide a study sample of 102 vowel sounds. Listeners categorized each vowel on the basis of four voice types (normal, breathy, hoarse, unclassified) and evaluated the degree of vocal abnormality on a 7-point scale. In addition to spectrographic noise (SN) classification, several acoustic measures based on period variability were entered into a multiple regression analysis for the prediction of vocal severity across and within voice types. In general, spectrographic noise and curvilinear derivatives of the period standard deviation (PSD) provided the best predictions of disorder severity. Different variables were the major predictors for different voice types. Several variables used in previous studies were inefficient as predictors of severity.
AB - Fifty-one subjects representing diverse laryngeal etiologies recorded /a/ and /i/ to provide a study sample of 102 vowel sounds. Listeners categorized each vowel on the basis of four voice types (normal, breathy, hoarse, unclassified) and evaluated the degree of vocal abnormality on a 7-point scale. In addition to spectrographic noise (SN) classification, several acoustic measures based on period variability were entered into a multiple regression analysis for the prediction of vocal severity across and within voice types. In general, spectrographic noise and curvilinear derivatives of the period standard deviation (PSD) provided the best predictions of disorder severity. Different variables were the major predictors for different voice types. Several variables used in previous studies were inefficient as predictors of severity.
UR - http://www.scopus.com/inward/record.url?scp=0023240601&partnerID=8YFLogxK
UR - http://www.scopus.com/inward/citedby.url?scp=0023240601&partnerID=8YFLogxK
M3 - Article
C2 - 3599955
AN - SCOPUS:0023240601
VL - 30
SP - 230
EP - 240
JO - Journal of Speech, Language, and Hearing Research
JF - Journal of Speech, Language, and Hearing Research
SN - 1092-4388
IS - 2
ER -