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1. #COMPARITIVE NOREM FOR PRAAT PERTURBATION MEASURES SOFTWARE#
2. #COMPARITIVE NOREM FOR PRAAT PERTURBATION MEASURES PROFESSIONAL#

#COMPARITIVE NOREM FOR PRAAT PERTURBATION MEASURES SOFTWARE#

Furthermore, correlation analyses show weak to moderate proportional relationships between the two systems and weak to strong proportional relationships between the two programs. The samples were analyzed by four different types of software programs that perform acoustical evaluation one open source software (Praat) and three commercial ones (Multi Dimensional Voice Program MDVP by Kay Elemetrics VoiceStudio by Seegnal and Dr. Results: Results indicate statistically significant differences between the two systems and programs, with the Multi-Dimensional Voice Program yielding consistently higher measures than Praat. Unidimensional cepstral acoustic measures such as cepstral peak prominence (CPP) 68. Methods: Correlations and inferential statistics for seven perturbation measures (absolute jitter, percent jitter, relative average perturbation, pitch perturbation quotient, shimmer in decibels, percent shimmer, and amplitude perturbation quotient) in 50 subjects with various voice disorders are presented. The Praat computer program will be used to calculate CPPS, the AVQI and H1-H2 ratio from the recordings 66.

#COMPARITIVE NOREM FOR PRAAT PERTURBATION MEASURES PROFESSIONAL#

In the present study, perturbation measures provided by two computer systems (a purpose-built professional voice analysis apparatus and a personal computer-based system for acoustic voice assessment) and two computer programs (Multi-Dimensional Voice Program and Praat) were compared. In this paper we examined the human voice of 20 adults (20 smokers and 20 non-smokers) to determine the effects of cigarette smoking on formants frequency, pitch, shimmer and jitter based on 3 Amazigh language vowels (A, I, U). The assessment of voice perturbation is influenced by several factors, including the type of recording equipment used and the measurement extraction algorithm applied. Background/Aims: Frequency and amplitude perturbations are inherent in voice acoustic signals.