Asymmetries of the vocal folds and vocal fold vibration are key features underlying unilateral vocal fold motion impairment (VFMI). The knowledge of what particular asymmetries contribute to breathy voice and which asymmetries must be eliminated to re-establish normal voice will be important to improving evaluation and treatment of VFMI. It was hypothesized that several structural and vibratory asymmetries should lead to predictable changes in the glottal area, flow, and acoustic waveforms, and subsequently a perceived breathy voice quality. The purpose of this project was threefold: 1) to determine how specific vocal fold structural and vibratory asymmetries alter vocal function and perceived voice quality, 2) to determine the improvement in vocal function and voice quality in an abnormal voice with elimination of individual asymmetries, and 3) to develop a battery of vocal function measures that vary with dysphonia in a predictable manner. The approach was to use a computational kinematic model of vocal fold vibration that allows for differential left/right control of parameters such as vocal fold adduction, medial surface bulging, vibratory nodal point, phase, amplitude of vibration, and fundamental frequency. The resultant signals were subjected to aerodynamic and acoustic measurement as well as perceptual rating of voice quality. Results revealed that the degree of vocal process separation was the most influential parameter tested, though asymmetry of bulging, nodal point ratio, and starting phase worsened normal voice quality. Conversely, increased symmetry of bulging, nodal point ratio, amplitude of vibration and starting phase improved disordered voice quality. The amount of improvement to disordered voices varied based on the number of other asymmetries present. None of the six vocal function measures tested were primarily responsive to one particular model parameter, though four measures generally decreased as vocal process separation increased: maximum flow declination rate (MFDR), spectral slope (B0-B2), cepstral peak prominence (CPP), and harmonics-to-noise ratio (HNR). Two of the measures, MFDR and CPP, co-varied with each of the five parameters and robustly correlated with perceived severity.

The human voice is a product of an intricate biophysical system. The complexity of this system enables a rich variety of possible sounds, but at the same time poses great challenges for quantitative voice analysis. For example, the vocal folds can vibrate in several different ways, leading to variations in the acoustic output. Because the vocal folds are relatively inaccessible, such variations are often difficult to account for. This work proposes a novel method for extracting non-invasively information on the vibratory state of the human vocal folds. Such information is important for creating a more complete voice analysis scheme. Invasive methods are undesirable because they often disturb the subjects and/or the studied phenomena, and they are also impractical in terms of accessibility and cost. A useful frame of reference for voice analysis is the Voice Range Profile (VRP). The 3 dimensional form of the VRP can be used to depict any phonatory metric over the 2 dimensional plane defined by the fundamental frequency of phonation (x-axis) and the sound pressure level (y-axis). The primary goal of this work was to incorporate information on the vibratory state of the vocal folds into the Voice Range Profile (e.g., as a color change). For this purpose, a novel method of analysis of the electroglottogram (EGG) was developed, using techniques from machine learning (clustering) and nonlinear time series analysis (sample entropy estimation). The analysis makes no prior assumptions on the nature of the EGG signal and does not rely on its absolute amplitude or frequency. Unlike time-domain methods, which typically define thresholds for quantifying EGG cycle metrics, the proposed method uses information from the entire cycle of each period. The analysis was applied in a variety of experimental conditions (constant vowel with different vibratory states, constant vibratory state and different vowels, constant vowel and vibratory state with varying lung volume) and the magnitude of effect on the EGG short-term spectrum was estimated for each of these conditions. It was found that the short-term spectrum of the EGG signal sufficed to discriminate between different phonatory configurations, such as modal and falsetto voice. It was found also that even supposedly purely articulatory changes could be traced in the spectrum of the EGG signal. Finally, possible pedagogical and clinical applications of the method are discussed. / <p>QC 20140609</p> / FonaDyn

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This thesis consists of five articles and a summary. Thethesis deals with methods for measuring properties of thevoice. The methods are all computer-based, but utilisedifferent approaches for measuring different aspects of thevoice. Paper I introduces the Visual Sort and Rate (VSR) method forperceptual rating of voice quality. The method is based on theVisual Analogue Scale (VAS), but simultaneously shows allstimuli as icons along the VAS on the computer screen. As thelistener places similar-sounding stimuli close to each otherduring the rating process, comparing stimuli becomeseasier. Paper II introduces the correlogram. Fundamental frequencyF0 sometimes cannot be strictly defined, particularly forperturbed voice signals. The method displays multipleconsecutive correlation functions in a grey scale image. Thus,the correlogram avoids selecting a single F0 value. Rather itpresents an unbiased image of periodicity, allowing theinvestigator to select among several candidates, ifappropriate. PaperIII introduces a method for detection of phonation tobe utilised in voice accumulators. The method uses twomicrophones attached near the subject’s ears. Phase andamplitude relations of the microphone signals are used to forma phonation detector. The output of the method can be used tomeasure phonation time, speaking time and fundamental frequencyof the subject, as well as sound pressure level of both thesubject’s voicing and the ambient sounds. Paper IV introduces a method for Fourier analysis ofhigh-speed laryngoscopic imaging. The data from the consecutiveimages are re-arranged to form time-series that reflect thetime-variation of light intensity in each pixel. Each of thesetime series is then analysed by means of Fouriertransformation, such that a spectrum for each pixel isobtained. Several ways of displaying these spectra aredemonstrated. Paper V examines a test set-up for simultaneous recording ofairflow, intra-oral pressure, electro-glottography, audio andhigh-speed imaging. Data are analysed with particular focus onsynchronisation between glottal area and inverse filteredairflow. Several methodological aspects are also examined, suchas the difficulties in synchronising high-speed imaging datawith the other signals. / QC 20100609