The Effect of Segment Selection on Acoustic Analysis

Abstract

Objective/Hypothesis-Acoustic analysis is a commonly used method for quantitatively measuring vocal fold function. Voice signals are analyzed by selecting a waveform segment and using various algorithms to arrive at parameters such as jitter, shimmer, and signal-to-noise ratio (SNR). Accurate and reliable methods for selecting a representative vowel segment have not been established. Study Design-Prospective repeated measures experimentMethods-We applied a moving window method by isolating consecutive, overlapping segments of the raw voice signal from onset through offset. Ten normal voice signals were analyzed using acoustic measures calculated from the moving window. The location and value of minimum perturbation/maximum SNR was compared across individuals. The moving window method was compared with data from the whole vowel excluding onset and offset, the mid-vowel and the visually selected steadiest portion of the voice signal. Results-Resultsshowed that the steadiest portion of the waveforms, as defined by minimum perturbation and maximum SNR values, was not consistent across individuals. Perturbation and nonlinear dynamic values differed significantly based on what segment of the waveform was used. Other commonly used segments selection methods resulted in significantly higher perturbation values and significantly lower SNR values than those determined by the moving window method (p<0.001).Conclusions-The selection of a sample for acoustic analysis can introduce significant inconsistencies into the analysis procedure. The moving window technique may provide more accurate and reliable acoustic measures by objectively identifying the steadiest segment of the voice sample.

The Effect of the Speech Task Characteristics on Perceptual Judgment of Mild to Moderate Dysphonia: A Methodological Study

“…Among the trials using sustained vowels, some authors removed the onset/attack of the signal while others assessed the perceptual voice quality on the entire signal. Regarding the fact that the voice onset may contain important data for the perceptual assessment [12, 28], removing of the voice onset could reduce the severity of the perceptual grade attributed to the voice sample. In this, paper, although we removed the onset of the sustained vowel, we show higher scores of GRBASI components when based on sustained vowel than when based on connected speech.…”

A Measure of the Auditory-perceptual Quality of Strain from Electroglottographic Analysis of Continuous Dysphonic Speech: Application to Adductor Spasmodic Dysphonia

“…The direction of change in SO was consistent between the current work and the prior works, namely that the SO was more negative with less strained voice, and less negative with more strained voice within the same subject. It is not straightforward to explain the direction of change in SO in terms of the difference in vocal fold vibratory kinematics between a strained voice and an unstrained voice, as there may be simultaneous changes in the level of vocal fold adduction, convergence, medial surface bulging, and vertical phasing 25 that can affect the SO in opposite directions. Nevertheless, a plausible hypothesis can be formulated as follows.…”

“…24 Finally, analysis of continuous speech in principle avoids the significant inconsistencies introduced by the manual selection of a sustained vowel segment for analysis. 25 There is, however, a knowledge gap on how the EGG signal in continuous speech is best handled. The calculation of EGG waveform parameters beyond CQ is affected by the substantial DC drift in continuous speech due to laryngeal movement relative to the skin-fixed electrodes.…”

The Impact of Nasalance on Cepstral Peak Prominence and Harmonics‐to‐Noise Ratio

“…CPP was obtained from each segment by visual confirmation of the waveform indicating the onset and offset of each speaking task. The onsets and offsets of >200 ms of the samples were removed for reliability of acoustic analysis . Each sample then underwent automatic analysis by the ADSV software.…”