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The objective is to analyze vocal dysperiodicities in connected speech produced by dysphonic speakers. The analysis involves a variogram-based method that enables tracking instantaneous vocal dysperiodicities. The dysperiodicity trace is summarized by means of the signal-to-dysperiodicity ratio, which has been shown to correlate strongly with the perceived(More)
Several studies have shown that the amplitude of the first rahmonic peak (R1) in the cepstrum is an indicator of hoarse voice quality. The cepstrum is obtained by taking the inverse Fourier Transform of the log-magnitude spectrum. In the present study, a number of spectral analysis processing steps are implemented, including period-synchronous and(More)
The aim of the presentation is to investigate acoustic analysis of connected speech by means of an average-equalized and energy-equalized variogram to extract vocal dysperiodicities. The variogram enables positioning a current and a lagged analysis frame in adjacent speech cycles to track inter-cycle dysperiodicities. Average and energy equalization of the(More)
The objective of the presentation is to report experiments involving the automatic classification of disordered connected speech into binary (normal, pathological) or multiple (modal, moderately hoarse, severely hoarse) categories. The multicategory classification according to the perceived degree of hoarseness is considered to be clinically meaningful and(More)
this paper presents the design and implementation of a clinical workstation software for analyzing voice disorders. the software is developed by using Java technology and MysQl database system. a variety of vocal cues, e.g. jitter and shimmer, that describe irregularities of speech cycles in sustained vowels can be automatically derived by the system. for(More)
Covariance data are required to assess uncertainties in design parameters in several nuclear applications. The error estimation of calculated quantities relies on the nuclear data uncertainty information available in the basic nuclear data libraries, such as the US Evaluated Nuclear Data Library, ENDF/B. The uncertainty files in the ENDF/B library are(More)
The objective of the presentation is to report experiments involving the automatic classification of disordered connected speech into multiple (modal, moderately hoarse, severely hoarse) categories. Support vector machines, used for the classification, have been fed with temporal signal-to-dysperiodicity ratios, the first rahmonic amplitude as well as(More)