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.
이용수
초록· 키워드
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In this study, the most stable portion was identified using 5% moving window during /a/ sustained phonation in normal and pathologic voice signals and the perturbation values were compared between normal and pathologic voices at the mid-point and at the most stable portion using moving window, respectively.
The results revealed that some severe pathologic voice signals can be eligible for perturbation analysis by identifying the most stable portion with Err less than 10. In addition, the perturbation acoustic parameters did not differentiate the pathologic voice signals from the normal voice signals when the mid-point was selected to measure the perturbation analysis(p>0.05). However, significantly higher %shimmer and lower SNR values were observed in pathologic voices (p<0.05) when the most stable portion was selected by moving window. In conclusion, moving window could identify the most stable portion objectively which can allow toget the minimum perturbation values (%jitter, %shimmer) and maximum SNR values. Thus, moving window technique can be applicable for more reliable and accurate perturbation acoustic analysis.
The results revealed that some severe pathologic voice signals can be eligible for perturbation analysis by identifying the most stable portion with Err less than 10. In addition, the perturbation acoustic parameters did not differentiate the pathologic voice signals from the normal voice signals when the mid-point was selected to measure the perturbation analysis(p>0.05). However, significantly higher %shimmer and lower SNR values were observed in pathologic voices (p<0.05) when the most stable portion was selected by moving window. In conclusion, moving window could identify the most stable portion objectively which can allow toget the minimum perturbation values (%jitter, %shimmer) and maximum SNR values. Thus, moving window technique can be applicable for more reliable and accurate perturbation acoustic analysis.
목차
ABSTRACT
1. Introduction
2. Methods
3. Results
4. Discussion and conclusion
References
참고문헌 (13)
참고문헌 신청
1. [학술지(정기간행물)] - Mehta, D.D. / 2008 / Voice assessment : updates on perceptual, acoustic, aerodynamic, and endoscopic imaging methods / Current Opinion in Otolaryngology & Head and Neck Surgery 16 (3) : 211 ~ 215
2. [학술지(정기간행물)] - Milenkovic, P. / 1987 / Least mean square measures of voice perturbation / Journal of Speech and Hearing Research 30 : 529 ~ 538
3. [학술지(정기간행물)] - Feijoo, S. / 1990 / Short-term stability measures for the evaluation of vocal quality / Journal of Speech and Hearing Research 33 : 324 ~ 334
4. [단행본] - Titze, I. / 1995 / Workshop on acoustic voice analysis : Summary statement / National Center for Voice and Speech, Denver, CO
5. [학술지(정기간행물)] - Zhang, Y. / 2005 / Comparison of nonlinear dynamic methods and perturbation methods for voice analysis / Journal of Acoustic Society of America 118 : 2551 ~ 2560
2. [학술지(정기간행물)] - Milenkovic, P. / 1987 / Least mean square measures of voice perturbation / Journal of Speech and Hearing Research 30 : 529 ~ 538
3. [학술지(정기간행물)] - Feijoo, S. / 1990 / Short-term stability measures for the evaluation of vocal quality / Journal of Speech and Hearing Research 33 : 324 ~ 334
4. [단행본] - Titze, I. / 1995 / Workshop on acoustic voice analysis : Summary statement / National Center for Voice and Speech, Denver, CO
5. [학술지(정기간행물)] - Zhang, Y. / 2005 / Comparison of nonlinear dynamic methods and perturbation methods for voice analysis / Journal of Acoustic Society of America 118 : 2551 ~ 2560
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UCI(KEPA) : I410-ECN-0101-2012-701-003653773