지원사업
학술연구/단체지원/교육 등 연구자 활동을 지속하도록 DBpia가 지원하고 있어요.
커뮤니티
연구자들이 자신의 연구와 전문성을 널리 알리고, 새로운 협력의 기회를 만들 수 있는 네트워킹 공간이에요.
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The purposes of this study were to identify acoustic parameters of connected speech and to contribute to acoustic analysis of dysphonic voice about patient"s natural speech voice as well as sustained phonation of vowels. Acoustic parameters of sentences included LTAS (long-term average spectrum) mean and spectral slope over frequence ranges such as 0-4㎑, 0-6㎑, 0-8㎑, 0-12.5㎑ as well as HNR. Acoustic parameters of the vowel ‘a’ included jitter, RAP, shimmer, NHR, and HNR. Based on ‘G’ of GRBAS for the severity of dysphonia, two experienced raters judged and classified as four groups including controls, mild, moderate and severe dysphonic group. Connected speech was two sentences extracted from ‘stroll’ passage. Parameters of the vowel and LTAS mean of the sentences were measured by CSL. The spectral slope of the sentences and HNR of the vowel and the sentences were measured by Praat. Data were statistically analyzed by Spearman correlation and Kruskal-Wallis test using SPSS 12.0.
The results of this study are as follows: First, jitter, RAP, shimmer and NHR were significantly different between the groups. Second, for several frequencies, LTAS mean and spectral slope of the sentences were significantly different between the groups. Third, the HNR of the sentences were significantly different between the groups. Forth, there was a presence of correlation between HNR and NHR of the vowel and HNR of the sentences. Accordingly, this study concluded that LTAS, spectral slope, and HNR were predictive parameters of connected speech voice for dysphonic voice.
The results of this study are as follows: First, jitter, RAP, shimmer and NHR were significantly different between the groups. Second, for several frequencies, LTAS mean and spectral slope of the sentences were significantly different between the groups. Third, the HNR of the sentences were significantly different between the groups. Forth, there was a presence of correlation between HNR and NHR of the vowel and HNR of the sentences. Accordingly, this study concluded that LTAS, spectral slope, and HNR were predictive parameters of connected speech voice for dysphonic voice.
목차
ABSTRACT
1. 서론
2. 연구 방법
3. 결과
4. 토의
참고문헌
참고문헌 (25)
참고문헌 신청
1. [학술지(정기간행물)] - Awan, S. N / 2006 / Toward the development of an objective index of dysphonia severity: A four-factor model / Clinical Linguistics and Phonetics 20 : 35 ~ 49
2. [인터넷자원] - Boersma, P / / Praat
3. [학술지(정기간행물)] - De Krom, G / 1995 / Some spectral correlates of pathological breathy and rough voice quality for different types of vowel fragments / Journal of Speech and Hearing Research 38 : 794 ~ 811
4. [학술지(정기간행물)] - Eadie, T. L / 2005 / Classification of Dysphonic Voice: Acoustic and Auditory-Perceptual Measures / Journal of Voice 19 (1) : 1 ~ 14
5. [학술지(정기간행물)] - Eadie T. L / 2010 / The Effect of Musical Background on Judgments of Dysphonia / Journal of Voice 24 (1) : 93 ~ 101
2. [인터넷자원] - Boersma, P / / Praat
3. [학술지(정기간행물)] - De Krom, G / 1995 / Some spectral correlates of pathological breathy and rough voice quality for different types of vowel fragments / Journal of Speech and Hearing Research 38 : 794 ~ 811
4. [학술지(정기간행물)] - Eadie, T. L / 2005 / Classification of Dysphonic Voice: Acoustic and Auditory-Perceptual Measures / Journal of Voice 19 (1) : 1 ~ 14
5. [학술지(정기간행물)] - Eadie T. L / 2010 / The Effect of Musical Background on Judgments of Dysphonia / Journal of Voice 24 (1) : 93 ~ 101
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UCI(KEPA) : I410-ECN-0101-2013-701-001385023