ACM.įernandez-Delgado, M., Cernadas, E., Barro, S., & Amorim, D. In Proceedings of the conference on Wireless Health (p. EchoWear: smartwatch technology for voice and speech treatments of patients with Parkinson’s disease. C., Abtahi, M., Mahler, L., & Mankodiya, K. Influence of sampling rate on accuracy and reliability of acoustic voice analysis. A comparison of multiple classification methods for diagnosis of Parkinson disease. Prentice-hall Englewood Cliffs, NJ.ĭas, R. Multirate digital signal processing volume 18. Assessment of Parkinson’s disease with imaging. Classification of Parkinson’s disease by using voice measurements. In Automatic Speech Recognition and Understanding (ASRU), 2011 IEEE Workshop on (pp. Detection of persons with Parkinson’s disease by acoustic, vocal, and prosodic analysis. Technol., 70.īocklet, T., Noth, E., Stemmer, G., Ruzickova, H., & Rusz, J. Voice analysis for detecting persons with Parkinson’s disease using PLP and VQ. Sites-masterCatalog_Harman/default/dwa4360d70/pdfs/AKG_C214_ Manual.pdf.
#Cepstral voices 6.2 serials professional#
C214 professional large-diaphragm condenser microphone. In the next part, we focus on the second one and try to reveal the optimal selection of sampling rate based on six metrics, especially for Parkinson’s disease. Besides, sampling rate may be an essential aspect that determines the cost of sampling device. Second, when pathological voice often shows signs in the high frequency band, the selection of sampling rate will be critical in order to capture the discriminative information for the screening of pathological voice. Thus, the influence of environmental SNR should be deeply researched further. It should be noted that particular attention on the environmental SNR is meaningful since the real acoustic environment for pathological voice analysis is more diverse and complex. When voices are recorded with large amount of noise around, indicating a low environmental SNR, the pathological characteristics may be mixed with noise and the pathological voice analysis under this circumstance will be adversely affected. 37, 1568–1572, 2010), a pathological voice often displays signs in the high frequency band, coinciding with the frequency range where numerous types of noise may lie. In particular, the influence of SNR (signal-to-noise ratio) and sampling rate during recording are two key factors that require investigation.įirstly, according to previous literature (Das, Expert Syst. In pathological voice analysis, voice acquisition is of great importance since the quality of the voice has great impacts on the performance of voice analysis.
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