Glottal Area Waveform Research Articles

A Deep Learning Enhanced Novel Software Tool for Laryngeal Dynamics Analysis.

Purpose High-speed videoendoscopy (HSV) is an emerging, but barely used, endoscopy technique in the clinic to assess and diagnose voice disorders because of the lack of dedicated software to analyze the data. HSV allows to quantify the vocal fold oscillations by segmenting the glottal area. This challenging task has been tackled by various studies; however, the proposed approaches are mostly limited and not suitable for daily clinical routine. Method We developed a user-friendly software in C# that allows the editing, motion correction, segmentation, and quantitative analysis of HSV data. We further provide pretrained deep neural networks for fully automatic glottis segmentation. Results We freely provide our software Glottis Analysis Tools (GAT). Using GAT, we provide a general threshold-based region growing platform that enables the user to analyze data from various sources, such as in vivo recordings, ex vivo recordings, and high-speed footage of artificial vocal folds. Additionally, especially for in vivo recordings, we provide three robust neural networks at various speed and quality settings to allow a fully automatic glottis segmentation needed for application by untrained personnel. GAT further evaluates video and audio data in parallel and is able to extract various features from the video data, among others the glottal area waveform, that is, the changing glottal area over time. In total, GAT provides 79 unique quantitative analysis parameters for video- and audio-based signals. Many of these parameters have already been shown to reflect voice disorders, highlighting the clinical importance and usefulness of the GAT software. Conclusion GAT is a unique tool to process HSV and audio data to determine quantitative, clinically relevant parameters for research, diagnosis, and treatment of laryngeal disorders. Supplemental Material https://doi.org/10.23641/asha.14575533.

Voice Feature Selection to Improve Performance of Machine Learning Models for Voice Production Inversion

Estimation of physiological control parameters of the vocal system from the produced voice outcome has important applications in clinical management of voice disorders . Previously we developed a simulation-based neural network for estimation of vocal fold geometry, mechanical properties, and subglottal pressure from voice outcome features that characterize the acoustics of the produced voice. The goals of this study are to (1) explore the possibility of improving the estimation accuracy of physiological control parameters by including voice outcome features characterizing vocal fold vibration; and (2) identify voice feature sets that optimize both estimation accuracy and robustness to measurement noise. Feedforward neural networks are trained to solve the inversion problem of estimating the physiological control parameters of a three-dimensional body-cover vocal fold model from different sets of voice outcome features that characterize the simulated voice acoustics, glottal flow, and vocal fold vibration. A sensitivity analysis is then performed to evaluate the contribution of individual voice features to the overall performance of the neural networks in estimating the physiologic control parameters. While including voice outcome features characterizing vocal fold vibration increases estimation accuracy, it also reduces the network's robustness to measurement noise, due to high sensitivity of network performance to voice outcome features measuring the absolute amplitudes of the glottal flow and area waveforms, which are also difficult to measure accurately in practical applications. By excluding such glottal flow-based features and replacing glottal area-based features by their normalized counterparts, we are able to significantly improve both estimation accuracy and robustness to noise. We further show that similar estimation accuracy and robustness can be achieved with an even smaller set of voice outcome features by excluding features of small sensitivity.

Impact of the Paraglottic Space on Voice Production in an MRI-Based Vocal Fold Model

While the vocal fold is in direct contact anteriorly with the thyroid cartilage, posteriorly the vocal fold connects to the thyroid cartilage through a soft tissue layer in the paraglottic space. Currently the paraglottic space is often neglected in computational models of phonation, in which a fixed boundary condition is often imposed on the lateral surface of the vocal fold. The goal of this study was to investigate the effect of the paraglottic space on voice production in an MRI-based vocal fold model, and how this effect may be counteracted by vocal fold stiffening due to laryngeal muscle activation. Parametric simulation study using an MRI-based computational vocal fold model. The results showed that the presence of the paraglottic space increased the mean and amplitude of the glottal area waveform, decreased the phonation frequency and closed quotient. For the particular vocal fold geometry used in this study, the presence of the paraglottic space also reduced the occurrence of irregular vocal fold vibration. These effects of the paraglottic space became smaller with increasing paraglottic space stiffness and to a lesser degree with vocal fold stiffening. The results suggest that the paraglottic space may be neglected in qualitative evaluations of normal phonation, but needs to be included in simulations of pathological phonation or vocal fold posturing.

Modelling of Amplitude Modulated Vocal Fry Glottal Area Waveforms Using an Analysis-by-Synthesis Approach

The characterization of voice quality is important for the diagnosis of a voice disorder. Vocal fry is a voice quality which is traditionally characterized by a low frequency and a long closed phase of the glottis. However, we also observed amplitude modulated vocal fry glottal area waveforms (GAWs) without long closed phases (positive group) which we modelled using an analysis-by-synthesis approach. Natural and synthetic GAWs are modelled. The negative group consists of euphonic, i.e., normophonic GAWs. The analysis-by-synthesis approach fits two modelled GAWs for each of the input GAW. One modelled GAW is modulated to replicate the amplitude and frequency modulations of the input GAW and the other modelled GAW is unmodulated. The modelling errors of the two modelled GAWs are determined to classify the GAWs into the positive and the negative groups using a simple support vector machine (SVM) classifier with a linear kernel. The modelling errors of all vocal fry GAWs obtained using the modulating model are smaller than the modelling errors obtained using the unmodulated model. Using the two modelling errors as predictors for classification, no false positives or false negatives are obtained. To further distinguish the subtypes of amplitude modulated vocal fry GAWs, the entropy of the modulator’s power spectral density and the modulator-to-carrier frequency ratio are obtained.

Experimental modelling and human data of glottal area declination rate for vowel and semi-occluded vocal tract phonation

ObjectiveThe aim of this study was to investigate how the maximum area declination rate (MADR) of the glottis corresponds to the maximum velocity of the self-oscillating vocal folds just before their collision. The maximum velocity before collision is closely related to impact stress in the colliding vocal folds and, thus, it is an important indicator of vocal loading. MethodsHigh speed imaging data for a male subject and measurements of the glottal area waveforms performed on a physical 1:1 scaled model for phonation on vowel [u:] were compared with those obtained during a semi-occluded vocal tract which increases voice source-vocal tract interaction. Semi-occlusion was obtained by phonation through a glass resonance tube with the distal end in air or submerged 10 cm in water. ResultsThe results show that the area declination rate of the glottis, i.e., closing velocity, before the glottal closure is substantially lower than the MADR, and also lower in semi-occluded vocal tract phonation through a tube into air and into water than in vowel phonation. ConclusionsThe results suggest that MADR is not a reliable estimate of impact stress, and that impact stress in tube therapy is lower than in vowel phonation.

Interdependencies between acoustic and high-speed videoendoscopy parameters

In voice research, uncovering relations between the oscillating vocal folds, being the sound source of phonation, and the resulting perceived acoustic signal are of great interest. This is especially the case in the context of voice disorders, such as functional dysphonia (FD). We investigated 250 high-speed videoendoscopy (HSV) recordings with simultaneously recorded acoustic signals (124 healthy females, 60 FD females, 44 healthy males, 22 FD males). 35 glottal area waveform (GAW) parameters and 14 acoustic parameters were calculated for each recording. Linear and non-linear relations between GAW and acoustic parameters were investigated using Pearson correlation coefficients (PCC) and distance correlation coefficients (DCC). Further, norm values for parameters obtained from 250 ms long sustained phonation data (vowel /i/) were provided. 26 PCCs in females (5.3%) and 8 in males (1.6%) were found to be statistically significant (|corr.| ≥ 0.3). Only minor differences were found between PCCs and DCCs, indicating presence of weak non-linear dependencies between parameters. Fundamental frequency was involved in the majority of all relevant PCCs between GAW and acoustic parameters (19 in females and 7 in males). The most distinct difference between correlations in females and males was found for the parameter Period Variability Index. The study shows only weak relations between investigated acoustic and GAW-parameters. This indicates that the reduction of the complex 3D glottal dynamics to the 1D-GAW may erase laryngeal dynamic characteristics that are reflected within the acoustic signal. Hence, other GAW parameters, 2D-, 3D-laryngeal dynamics and vocal tract parameters should be further investigated towards potential correlations to the acoustic signal.

Influence of Loudness on Vocal Stability in the Male Passaggio

Vocal registers and the frequency region where registration events occur, the passaggio, have been in focus of scientific research for almost 200 years. In professional tenors, it has been shown before that singing across the passaggio avoiding a register shift and therefore using their stage voice above the passaggio (SVaP) is associated with greater vocal stability than a register change to the falsetto. However, it is unclarified how much different loudness conditions contribute to this vocal stability. Six professional tenors were asked to perform four pitch glides from A3 to A4 (220-440 Hz) on the vowel [i:]. These glides included (1) the passaggio from modal register to falsetto. The following glides into SVaP were performed under different loudness conditions, (2) mezzoforte (average loudness), (3) pianissimo (as quietly as possible), and (4) fortissimo (the loudest possible). During phonation, high speed videoendoscopy (HSV), electroglottography, and audio signals were recorded simultaneously. The glottal area waveform was derived based on the HSV material. Modal to falsetto transitions were associated with relatively low sound pressure level and rise of open quotients (OQ) for the falsetto. Transitions to SVaP showed a clear dependence on the intended loudness. The OQs were lower the louder the task was. There was no clear evidence that transitions with softer voice showed greater stability of vocal fold oscillation patterns than louder tasks. The vocal fold oscillation pattern show- differences among various loudness conditions within the tenors' passaggio but no clear differences with regard to oscillatory stability.

Synthesis and Analysis-By-Synthesis of Modulated Diplophonic Glottal Area Waveforms

Diplophonia is a type of disordered voice in which two simultaneous pitches are perceived. Most commonly in diplophonic voices, the vocal folds are divided into two parts that vibrate at different frequencies. The glottal area is the projected area of the space between the vocal folds. The glottal area in time is referred to as the glottal area waveform (GAW). The GAW is modeled for diplophonic voice by superimposing two partial GAWs (pGAWs) that are trains of single-peak pulses with different pulse frequencies, i.e., fundamental frequencies ( $f_o$ s). In current kinematic models of diplophonic vocal fold vibration, the pGAWs are assumed to be quasiperiodic. This assumption is mitigated here by modulating pulse-to-pulse cycle length and amplitude. Both random and deterministic modulations are considered. Deterministic modulations depend on the difference of the pGAWs’ instantaneous phases. Model GAWs are fitted to input GAWs using an analysis-by-synthesis approach which we refer to as ‘modulated pulse trains decomposition’ (MPD). MPD is shown to be applicable to diplophonic as well as to nondiplophonic types of dysphonia, which include multi-pulse patterns, random timing behaviours, and chaos. It is mostly robust against modulations but degraded by large random modulations. MPD is compared to a deep autoencoder neural network, and the WaveGlow neural network. In terms of time-domain fitting errors, MPD outperforms the other two approaches unless random modulations are large. MPD outperforms the best of the other two approaches by up to approximately 5 dB. For large random modulations, the deep autoencoder network achieves the smallest fitting errors. In terms of magnitude spectrum fitting errors, WaveGlow is superior except for natural input GAWs containing only nondiplophonic types of dysphonia. Also pulse timing errors are shown to be advantageous for MPD.

Spatial Segmentation for Laryngeal High-Speed Videoendoscopy in Connected Speech

This study proposes a new computational framework for automated spatial segmentation of the vocal fold edges in high-speed videoendoscopy (HSV) data during connected speech. This spatio-temporal analytic representation of the vocal folds enables the HSV-based measurement of the glottal area waveform and other vibratory characteristics in the context of running speech. HSV data were obtained from a vocally normal adult during production of the "Rainbow Passage." An algorithm based on an active contour modeling approach was developed for the analysis of HSV data. The algorithm was applied on a series of HSV kymograms at different intersections of the vocal folds to detect the edges of the vibrating vocal folds across the frames. This edge detection method follows a set of deformation rules for the active contours to capture the edges of the vocal folds through an energy optimization procedure. The detected edges in the kymograms were then registered back to the HSV frames. Subsequently, the glottal area waveform was calculated based on the area of the glottis enclosed by the vocal fold edges in each frame. The developed algorithm successfully captured the edges of the vocal folds in the HSV kymograms. This method led to an automated measurement of the glottal area waveform from the HSV frames during vocalizations in connected speech. The proposed algorithm serves as an automated method for spatial segmentation of the vocal folds in HSV data in connected speech. This study is one of the initial steps toward developing HSV-based measures to study vocal fold vibratory characteristics and voice production mechanisms in norm and disorder in the context of connected speech.

Modelling sagittal and vertical phase differences in a lumped and distributed elements vocal fold model

The quality and timbre of disordered voices heavily rely on the vibration properties of the vocal folds. We discuss the representation of sagittal phase differences in vocal fold oscillations through a numerical biomechanical model involving lumped elements as well as distributed elements, i.e., delay lines. A dynamic glottal source model is proposed in which the fold displacement along the vertical and the sagittal dimensions is modelled using delay lines. In contrast to other models, with which the reproduction of sagittal phase differences is impossible (e.g., in two-mass models) or not easy to control (e.g., in 3D 16-mass and multi-mass models in general), the one proposed here provides direct control over the amount of phase delay between folds’ oscillations at the posterior and anterior part of the glottis, i.e., the sagittal axis, and at the superior and inferior part of the glottis, i.e., the vertical axis, while keeping the dynamic model simple and computationally efficient. The model is assessed by addressing the reproduction of oscillatory patterns observed in high-speed videoendoscopic data, in which sagittal phase differences are observed. Also, timing asymmetry parameters observed in hemi glottal area waveforms (GAWs) are used for fitting.

Maximum and Minimum Phonatory Glottal Area before and after Treatment for Vocal Nodules.

Background: Vocal fold nodules (VFNs) are a challenge for otolaryngologists. Glottal area (GA) waveform analysis is an examination method used for assessing vocal fold vibration and function. However, GA in patients with VFNs has rarely been studied. This study investigated the maximum and minimum GA in VFN patients using modern waveform analysis combining ImageJ software and videostroboscopy. Methods: This study enrolled 42 patients newly diagnosed with VFN, 15 of whom received voice therapy and 27 of whom underwent surgery. Acoustic parameters and maximum phonation time (MPT) were recorded, and patients completed the Chinese Voice Handicap Index-10 (VHI-C10) before and after treatment. After videostroboscopy examination, the maximum and minimum GAs were calculated using ImageJ software. The GAs of patients with VFNs before and after surgery or voice therapy were analyzed. Results: The MPTs of the patients before and after voice therapy or surgery did not change significantly. VHI-C10 scores decreased after voice therapy but the decrease was nonsignificant (14.0 ± 8.44 vs. 9.40 ± 10.24, p = 0.222); VHI-C10 scores were significantly decreased after surgery (22.53 ± 7.17 vs. 12.75 ± 9.84, p = 0.038). Voice therapy significantly increased the maximum GA (5.58 ± 2.41 vs. 8.65 ± 3.17, p = 0.012) and nonsignificantly decreased the minimum GA (0.60 ± 0.73 vs. 0.21 ± 0.46, p = 0.098). Surgery nonsignificantly increased the maximum GA (6.34 ± 3.82 vs. 8.73 ± 5.57, p = 0.118) and significantly decreased the minimum GA (0.30 ± 0.59 vs. 0.00 ± 0.00, p = 0.036). Conclusion: This study investigated the GA of patients with VFNs who received voice therapy or surgery. The findings indicated that voice therapy significantly increased maximum GA and surgery significantly decreased minimum GA. GA analysis could be applied to evaluate the efficacy of voice therapy, and it may help physicians to develop precise treatment for VFN patients (either by optimizing voice therapy or by performing surgery directly).

Glottal Airflow and Glottal Area Waveform Characteristics of Flow Phonation in Untrained Vocally Healthy Adults

To examine flow phonation characteristics with regard to vocal fold vibration and voice source properties in vocally healthy adults using multimodality voice measurements across various phonation types (breathy, neutral, flow, and pressed) and loudness conditions (typical, loud, and soft). Vocal fold vibration, airflow, acoustic, and subglottal pressure was analyzed in 13 untrained voices (six female and seven male). Participants repeated the syllable / pæ:/ using breathy, neutral, flow, and pressed phonation during typical, loud, and soft loudness conditions. Glottal area (GA) waveforms were extracted from high-speed videoendoscopy; glottal flow was derived from inverse filtering the airflow or the audio signal; and subglottal pressure was measured as the intraoral pressure during /p/ occlusion. Changes in phonation type and loudness conditions resulted in systematic variations across the relative peak closing velocity derived from the GA waveform for both males and females. Amplitude quotient derived from the flow glottogram varied across phonation types for males. Multimodality evaluation using the GA waveform and the inverse filtered waveforms revealed a complex pattern that varied as a function of phonation types and loudness conditions across males and females. Emerging findings from this study suggests that future large-scale studies should focus on spatial and temporal features of closing speed and closing duration for differentiating flow phonation from other phonation types in untrained adults with and without voice disorders.

Machine learning based identification of relevant parameters for functional voice disorders derived from endoscopic high-speed recordings

In voice research and clinical assessment, many objective parameters are in use. However, there is no commonly used set of parameters that reflect certain voice disorders, such as functional dysphonia (FD); i.e. disorders with no visible anatomical changes. Hence, 358 high-speed videoendoscopy (HSV) recordings (159 normal females (NF), 101 FD females (FDF), 66 normal males (NM), 32 FD males (FDM)) were analyzed. We investigated 91 quantitative HSV parameters towards their significance. First, 25 highly correlated parameters were discarded. Second, further 54 parameters were discarded by using a LogitBoost decision stumps approach. This yielded a subset of 12 parameters sufficient to reflect functional dysphonia. These parameters separated groups NF vs. FDF and NM vs. FDM with fair accuracy of 0.745 or 0.768, respectively. Parameters solely computed from the changing glottal area waveform (1D-function called GAW) between the vocal folds were less important than parameters describing the oscillation characteristics along the vocal folds (2D-function called Phonovibrogram). Regularity of GAW phases and peak shape, harmonic structure and Phonovibrogram-based vocal fold open and closing angles were mainly important. This study showed the high degree of redundancy of HSV-voice-parameters but also affirms the need of multidimensional based assessment of clinical data.

Duration of biodynamic changes associated with water resistance therapy

Introduction In current voice research, there is a growing interest in semi-occluded vocal tract exercises and their contribution to an increased vocal efficiency. However, there are only few studies on the lasting effects. Material and methods Eight vocally healthy subjects were asked to sustain a phonation at a comfortable loudness on the vowel /i/, with a Fundamental Frequency of 250 Hz (females) or 125 Hz (males). During phonation the subjects were simultaneously recorded with transnasal High Speed Videoendoscopy (HSV, 20,000fps), electroglottography, and audio signals. The subjects then performed a water resistance therapy (WRT) for 10 min (tube: 30 cm length, 5 cm below water surface, diameter 9 mm). Repeated measurements of sustained phonation were performed 0, 5, 10, 20, and 30 min after exercising. From the HSV material the Glottal Area Waveform (GAW) was segmented and GAW parameters were computed. Results There were strong inter-individual differences concerning the changes of different measures over time after WRT. In general, directly after WRT there was a lowering of the GAW derived Period Perturbation Quotient, a lowering of the Closing Quotient and an increase of the Sound Pressure Level (SPL) in comparison to the pre-intervention measurement. However, only 5 min post WRT there was no longer a clear difference compared to baseline results before WRT. Other values such as Open Quotients exhibited no evident changes by WRT at any timepoint. Conclusions WRT showed strong inter-individual effects concerning the changes in the evaluated measures post-intervention. General tendencies of some measures directly after the intervention showed a brief effect of only a few minutes.

Effects of Using Laryngeal High-Speed Videoendoscopy Images Visualizing Partial Views of The Glottis on Measurement Outcomes

Ideally, an analysis method for laryngeal high-speed videoendoscopy (LHSV) based on the glottal area waveforms (GAW) requires images of a complete view of the glottis to ensure findings that are representatives of the vibratory behaviors of the whole vocal folds. However, in practice, the preferred images may not be obtained at all times. Often, the only available images that a clinician has to work with consist of a partial view of the glottis. This study aims to examine the effects of using images of a partial view of the glottis (ie, posterior-middle, anterior-middle, or middle) on the LHSV-based measures (ie, fundamental frequency (F0GAW), frequency perturbation (jitterGAW), amplitude perturbation (shimmerGAW), open quotient (OQGAW), and Nyquist plot). The participants consisted of 9 young normophonic females. The procedures involved LHSV recording of the vibration of the vocal folds. The images of the complete view of the glottis were analyzed to obtain the LHSV-based measures. The same images were used to simulate the images of partial views of the glottis by changing the outline of the region of interest to include only either the posterior-middle, anterior-middle, or middle parts of the glottis. The LHSV-based measures from the images of the partial views were then compared to those with the complete view . The results showed that all LHSV-based measures from the images of the posterior-middle view were similar to those of the complete view. However, only the F0GAW, jitterGAW, and shimmerGAW from the images of the anterior-middle and middle views were similar to those of the complete view. Lower OQGAW and different Nyquist plots than those of the complete view were generated by the images of the anterior-middle and middle views. In conclusion, all LHSV-based measures from the images of the posterior-middle view of the glottis, and only the F0GAW, jitterGAW, and shimmerGAW from the images of the anterior-middle and middle views of the glottis reflect the vibratory behaviors of the whole vocal folds. The same conclusion could not be applied to the OQGAW and Nyquist plots of the images of the anterior-middle and middle views of the glottis. A possible effect of the presence or absence of a posterior glottal gap on the findings warrants further confirmation.

Immediate effects of water resistance therapy on patients with vocal fold mass lesions

IntroductionSemi-occluded vocal tract exercises, such as water resistance therapy (WRT), are widely used in voice therapy. However, the potential positive effects of such a therapy on vocal fold oscillation patterns in patients indicating a need for phonomicrosurgery have not yet been explored. The presented study aims to analyze the effect of WRT in patients suffering from vocal fold mass lesions.Materials and methodsEight participants with vocal fold mass lesions were asked to sustain a phonation on the vowel /i/ at a comfortable loudness and a fundamental frequency of 250 Hz (females) or 125 Hz (males). During phonation the subjects were simultaneously recorded with transnasal high-speed videoendoscopy (HSV, 20.000 fps), electroglottography, and audio signals. These subjects then performed a WRT (phonation in a silicone tube of 30 cm length, 5 cm below the water surface) for 10 min. Repeated measurements of sustained phonation were performed 0, 10, and 30 min after exercising. From the HSV data the glottal area waveform (GAW) was segmented and GAW parameters were computed.ResultsDuring WRT there was an increase of the GAW related open quotient and closing quotient. Immediately after WRT, there was a drop of both values followed by a rise of these parameters up to 30 min after the intervention. Furthermore, there was no correlation between GAW and electroglottographical open quotients.ConclusionsThe effects observed after a single session of WRT on participants with vocal fold mass lesions showed a similar pattern to vocal fatigue.

Relating Cepstral Peak Prominence to Cyclical Parameters of Vocal Fold Vibration from High-Speed Videoendoscopy Using Machine Learning: A Pilot Study

Smoothed cepstral peak prominence (CPPs) has been shown to be an effective indicator of breathiness (Hillenbrand and Houde, 1996). High-speed videoendoscopy (HSV) is frequently being used as a complement to stroboscopy especially when asymmetric or aperiodic vocal fold vibration is present in dysphonic voices. In an HSV image data set obtained with normal (nondisordered) voice subjects, we have observed that some degree of asymmetry is present in many of the vocal fold displacement curves extracted from the HSV exam videos; therefore, we have used this data set for a pilot study to investigate the relationship of CPPs to cyclical vocal fold vibration parameters, including left-right vocal fold (LVRF) phase asymmetry, in subjects with normal (nondisordered) voices. Twenty subjects with normal (nondisordered) voices produced sustained vowel phonations while undergoing a transoral HSV examination of the vocal folds with synchronized recording of the voice signal. Glottal area waveform (GAW) and cyclical parameters open quotient (OQ), closed quotient (CQ), speed quotient (SQ), and LVRF skew were extracted from the HSV exam videos, and CPPs measures were obtained from acoustic analysis of the audio recordings. Correlations among the cyclical parameters and CPPs values were investigated using machine learning with the Regression Learner application in the MATLAB© Statistics and Machine Learning Toolbox (version 9.5.0.944444, R2018b, August 28, 2018, (c) 1984-2018, The MathWorks, Inc., Natick, MA). Because the sample size of the data set used for this study was small, and because there possibly was multicollinearity among the predictor variables used, the only meaningful result that was obtained with the data set of 20 normal subjects in the four predictor variables was the constant model (ie, the best prediction of CPPs was just the average value of the 20 observations), when the model validation feature of the app was turned on to protect against overfitting. In order to fully investigate the usefulness of the Regression Learner App, however, the validation feature was turned off and 48 more model types were investigated. While these were not necessarily indicative of the best regression model for the current data set, the results obtained in this manner nevertheless demonstrated the utility of the automated approach for finding a regression model for a larger data set to be collected in the future. Further work is warranted to collect a data set from a larger sample size of disordered voice patients with breathy and/or rough voice. It is speculated that a correlation between CPPs and cyclical parameters of vocal fold vibration may be more evident with disordered voices, because there will be more asymmetry in LRVF displacement with an effect on the acoustic voice signal.

Vocal fold oscillation pattern changes related to loudness in patients with vocal fold mass lesions

IntroductionVocal fold mass lesions can affect vocal fold oscillation patterns and therefore voice production. It has been previously observed that perturbation values from audio signals were lower with increased loudness. However, how much the oscillation patterns change with gradual alteration of loudness is not yet fully understood.Material and methodsEight patients with vocal fold mass lesions were asked to perform a glide from minimum to maximum loudness on the vowel /i/, ƒo of 125 Hz for male or 250 Hz for female voices. During phonation the subjects were simultaneously recorded with transnasal high speed videoendoscopy (HSV, 20,000 fps), electroglottography (EGG), and an audio recording. Based on the HSV material the Glottal Area Waveform (GAW) was segmented and GAW parameters were computed.ResultsThe greatest vocal fold irregularities were observed at different values between minimum and maximum sound pressure level. There was a relevant discrepancy between the HSV and EGG derived open quotients. Furthermore, the EGG derived sample entropy and GAW values also evidenced different behavior.ConclusionsThe amount of vocal fold irregularity changes with varying loudness. Therefore, any evaluation of the voice should be performed under different loudness conditions. The discrepancy between EGG and GAW values appears to be much stronger in patients with vocal fold mass lesions than those with normal physiological conditions.Level of evidence4.

Objective Measures of Stroboscopy and High-Speed Video.

Videostroboscopy and high-speed imaging is now an accepted way to evaluate laryngeal function in patients with voice disorders. In patients with neurolaryngological diseases such as tremor, laryngeal spasm, and paralysis, having an objective way to evaluate vocal function is desirable. Using digital imaging and analysis, both the videostroboscopy and the high-speed video can be analyzed to obtain relevant measures of vocal function. From the videostroboscopy, the montage of the glottal cycle derived from steady of vocal vibration can be analyzed by using edge tracking software to obtain the glottal area waveform. The waveform is an indication of the efficiency of the vocal folds in acting as an oscillator and gives direct information as to the open and closed phase, the symmetry of vocal fold vibration and the degree of amplitude contribution from each fold. High-speed video overcomes the deficiencies of stroboscopy by allowing for all voice gestures to be studies. Using digital kymography and analysis of the vibrogram, analysis of the onset of vocal fold oscillation, evaluation of diplophonia, tremor, and voice breaks becomes possible. Furthermore, analysis of the high-speed video kymograph tracing using signal analysis allow the investigator to evaluate the frequency and power relationships of vocal fold vibratory function in the normal and disordered state.

Intersegmenter Variability in High-Speed Laryngoscopy-Based Glottal Area Waveform Measures.

High-speed videoendoscopy (HSV) has potential to objectively quantify vibratory vocal fold characteristics during phonation. Glottal Analysis Tools (GAT) version 2018, developed in Erlangen, Germany, is software for determining various glottal area waveform (GAW) quantities. Before having GAT analyze HSV videos, segmenters have to define glottis manually across videos in a semiautomatic segmentation protocol. Such interventions are hypothesized to induce variability of subsequent GAW measure computation across segmenters and may attenuate GAT measures' reliability to a certain point. This study explored intersegmenter variability in GAT's GAW measures based on semiautomatic image processing. Cohort study of rater reliability. In total, 20 HSV videos from normophonic and dysphonic subjects with various laryngeal disorders were selected for this study and segmented by three trained segmenters. They separately segmented glottis areas in the same frame sets of the videos. Upon analysis of GAW, GAT offers 46 measures related to topologic GAW dynamic characteristics, GAW periodicity and perturbation characteristics, and GAW harmonic components. To address GAT's reliability, intersegmenter-based variability in these measures was examined with intraclass correlation coefficient (ICC). In general, ICC behavior of the 46 GAW measures across three raters was highly acceptable. ICC of one parameter was moderate (0.5 < ICC < 0.75), good for seven parameters (0.75 < ICC < 0.9), and excellent for 38 parameters (0.9 < ICC). Overall, high ICC values confirm clinical applicability of GAT for objective and quantitative assessment of HSV. Small intersegmenter differences with actual small parameter differences suggest that manual or semiautomatic segmentation in GAT does not noticeably influence clinical assessment outcome. To guarantee the software's performance, we suggest segmentation training before clinical application. 2b Laryngoscope, 130:E654-E661, 2020.