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IntroductionDespite its importance in voice training, comprehensive research into sustained vowel phonation with constant pitch and increasing and decreasing loudness, the so-called Messa di Voce, is lacking. The study examines the laryngeal behavior during Messa di Voce, regarding the impact of the speed of execution on voice stability parameters.Materials and methodsNine untrained, healthy subjects (5 female, 4 male) were asked to perform Messa di Voce exercises on the vowel [i:], involving a gradual increase and decrease of volume. During the first task, each phase should take 3 s, whereas in the second task, each phase should take 1 s. Female subjects sang pitch B3 (fundamental frequency fo ≈ 247 Hz), and male subjects pitch B2 (fo ≈ 124 Hz). Throughout phonation, synchronous recordings were captured through high-speed videolaryngoscopy (HSV), electroglottography, and audio signals. Subsequently, the Glottal Area Waveform was extracted from the HSV data. The tasks' duration and calculated parameters (including, e.g., Open Quotient (OQ), Closing Quotient (ClQ), Relative Average Perturbation (RAP)), excluding parts of the signal with stationary sound pressure level (SPL), were analyzed with correlation analysis and statistical analysis (Analysis of Variance and subsequent multiple comparisons).ResultsSubjects shortened the requested task length by factor ≈ 0.5. The fo remained almost stable for most subjects and tasks. There were strong negative correlations between SPL and both OQ and ClQ. The median RAP appears to decrease towards the SPL apex and then increase again. Statistical effects were shown especially for females during the fast task, which may be due to raised SPL.ConclusionThere was no specific effect on stability found corresponding to the task's speed. Also, no major vocal instabilities at a specific sound pressure level were apparent, indicating no transitions as they exist for fo regions with registration events.

Musical activities, especially singing and playing wind instruments, have been singled out as potentially high-risk activities for the transmission of SARS CoV-2, due to a higher rate of aerosol production and emission. Playing wind instruments can produce condensation, droplets of saliva, and aerosol particles, which hover and spread in the environmental air’s convectional flows and which can be potentially infectious. The aim of this study is to investigate the primary impulse dispersion of aerosols that takes place during the playing of different wind instruments as compared to breathing and to speaking. Nine professional musicians (3 trumpeters, 3 flautists and 3 clarinetists) from the Bavarian Symphony Orchestra performed the main theme from the 4th movement of Ludwig van Beethoven‘s 9th symphony in different pitches and loudness. The inhaled air volume was marked with small aerosol particles produced using a commercial e-cigarette. The expelled aerosol cloud was recorded by cameras from different perspectives. Afterwards, the dimensions and dynamics of the aerosol cloud were measured by segmenting the video footage at every time point. Overall, the flutes produced the largest dispersion at the end of the task, reaching maximum forward distances of 1.88 m. An expulsion of aerosol was observed in different directions: upwards and downwards at the mouthpiece, at the end of the instrument, and along the flute at the key plane. In comparison, the maximum impulse dispersions generated by the trumpets and clarinets were lower in frontal and lateral direction (1.2 m and 1.0 m towards the front, respectively). Also, the expulsion to the sides was lower.

The U-Net architecture is a state-of-the-art neural network for semantic image segmentation that is widely used in biomedical research. It is based on an encoder-decoder framework and its vanilla version shows already high performance in terms of segmentation quality. Due to its large parameter space, however, it has high computational costs on both, CPUs and GPUs. In a research setting, inference time is relevant, but not crucial for the results. However, especially in mobile, clinical applications a light and fast variant would allow deep-learning assisted, objective diagnosis at the point of care. In this work, we suggest an optimized, tiny-weight U-Net for an inexpensive hardware accelerator. We first mined the U-Net architecture to reduce computational complexity to increase runtime performance by simultaneously keeping the accuracy on a high level. Using an open, biomedical dataset for high-speed videoendoscopy (BAGLS), we show that we can dramatically reduce the parameter space and computations by over 99.8% while keeping the segmentation performance at 95% of our baseline. Using a custom upscaling routine, we further successfully deployed our optimized U-Net to an EdgeTPU hardware accelerator to gain cost-effective speed improvements on conventional computers and to showcase the applicability of EdgeTPUs for biomedical imaging processing of large images on portable devices. Combining the optimized architecture and the EdgeTPU, we gain a speedup of >79-times compared to our initial baseline while keeping high accuracy. This combination allows to provide immediate results to the clinician, especially in constrained computational environments, and an objective diagnosis at the point of care.

Background: Various voice assessment tools, such as questionnaires and aerodynamic voice characteristics, can be used to assess vocal function of individuals. However, not much is known about the best combinations of these parameters in identification of functional dysphonia in clinical settings. Methods: This study investigated six scores from clinically commonly used questionnaires and seven acoustic parameters. 514 females and 277 males were analyzed. The subjects were divided into three groups: one healthy group (N01) (49 females, 50 males) and two disordered groups with perceptually hoarse (FD23) (220 females, 96 males) and perceptually not hoarse (FD01) (245 females, 131 males) sounding voices. A tree stumps Adaboost approach was applied to find the subset of parameters that best separates the groups. Subsequently, it was determined if this parameter subset reflects treatment outcome for 120 female and 51 male patients by pairwise pre- and post-treatment comparisons of parameters. Results: The questionnaire “Voice-related-quality-of-Life” and three objective parameters (“maximum fundamental frequency”, “maximum Intensity” and “Jitter Percent”) were sufficient to separate the groups (accuracy ranging from 0.690 (FD01 vs. FD23, females) to 0.961 (N01 vs. FD23, females)). Our study suggests that a reduced parameter subset (4 out of 13) is sufficient to separate these three groups. All parameters reflected treatment outcome for patients with hoarse voices, Voice-related-quality-of-Life showed improvement for the not hoarse group (FD01). Conclusion: Results show that single parameters are insufficient to separate voice disorders but a set of several well-chosen parameters is. These findings will help to optimize and reduce clinical assessment time.

For the clinical analysis of underlying mechanisms of voice disorders, we developed a numerical aeroacoustic larynx model, called simVoice, that mimics commonly observed functional laryngeal disorders as glottal insufficiency and vibrational left-right asymmetries. The model is a combination of the Finite Volume (FV) CFD solver Star-CCM+ and the Finite Element (FE) aeroacoustic solver CFS++. simVoice models turbulence using Large Eddy Simulations (LES) and the acoustic wave propagation with the perturbed convective wave equation (PCWE). Its geometry corresponds to a simplified larynx and a vocal tract model representing the vowel /a/. The oscillations of the vocal folds are externally driven. In total, 10 configurations with different degrees of functional-based disorders were simulated and analyzed. The energy transfer between the glottal airflow and the vocal folds decreases with an increasing glottal insufficiency and potentially reflects the higher effort during speech for patients being concerned. This loss of energy transfer may also have an essential influence on the quality of the sound signal as expressed by decreasing sound pressure level (SPL), Cepstral Peak Prominence (CPP), and Vocal Efficiency (VE). Asymmetry in the vocal fold oscillations also reduces the quality of the sound signal. However, simVoice confirmed previous clinical and experimental observations that a high level of glottal insufficiency worsens the acoustic signal quality more than oscillatory left-right asymmetry. Both symptoms in combination will further reduce the quality of the sound signal. In summary, simVoice allows for detailed analysis of the origins of disordered voice production and hence fosters the further understanding of laryngeal physiology, including occurring dependencies. A current walltime of 10 h/cycle is, with a prospective increase in computing power, auspicious for a future clinical use of simVoice.

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.

Quantifying the physical parameters of voice production is essential for understanding the process of phonation and can aid in voice research and diagnosis. As an alternative to invasive measurements, they can be estimated by formulating an inverse problem using a numerical forward model. However, high-fidelity numerical models are often computationally too expensive for this. This paper presents a novel approach to train a long short-term memory network to estimate the subglottal pressure in the larynx at massively reduced computational cost using solely synthetic training data. We train the network on synthetic data from a numerical two-mass model and validate it on experimental data from 288 high-speed ex vivo video recordings of porcine vocal folds from a previous study. The training requires significantly fewer model evaluations compared with the previous optimization approach. On the test set, we maintain a comparable performance of 21.2% versus previous 17.7% mean absolute percentage error in estimating the subglottal pressure. The evaluation of one sample requires a vanishingly small amount of computation time. The presented approach is able to maintain estimation accuracy of the subglottal pressure at significantly reduced computational cost. The methodology is likely transferable to estimate other parameters and training with other numerical models. This improvement should allow the adoption of more sophisticated, high-fidelity numerical models of the larynx. The vast speedup is a critical step to enable a future clinical application and knowledge of parameters such as the subglottal pressure will aid in diagnosis and treatment selection.

In laryngeal high-speed videoendoscopy (HSV) the area between the vibrating vocal folds during phonation is of interest, being referred to as glottal area waveform (GAW). Varying camera resolution may influence parameters computed on the GAW and hence hinder the comparability between examinations. This study investigates the influence of spatial camera resolution on quantitative vocal fold vibratory function parameters obtained from the GAW. In total 40 HSV recordings during sustained phonation (20 healthy males and 20 healthy females) were investigated. A clinically used Photron Fastcam MC2 camera with a frame rate of 4000 fps and a spatial resolution of 512×256 pixels was applied. This initial resolution was reduced by pixel averaging to (1) a resolution of 256×128 and (2) to a resolution of 128×64 pixels, yielding three sets of recordings. The GAW was extracted and in total 50 vocal fold vibratory parameters representing different features of the GAW were computed. Statistical analyses using SPSS Statistics, version 21, was performed. 15 Parameters showing strong mathematical dependencies with other parameters were excluded from the main analysis but are given in the Supporting Information. Data analysis revealed clear influence of spatial resolution on GAW parameters. Fundamental period measures and period perturbation measures were the least affected. Amplitude perturbation measures and mechanical measures were most strongly influenced. Most glottal dynamic characteristics and symmetry measures deviated significantly. Most energy perturbation measures changed significantly in males but were mostly unaffected in females. In females 18 of 35 remaining parameters (51%) and in males 22 parameters (63%) changed significantly between spatial resolutions. This work represents the first step in studying the impact of video resolution on quantitative HSV parameters. Clear influences of spatial camera resolution on computed parameters were found. The study results suggest avoiding the use of the most strongly affected parameters. Further, the use of cameras with high resolution is recommended to analyze GAW measures in HSV data.

The enormous computational power and time required for simulating the complex phonation process preclude the effective clinical use of computational larynx models. The aim of this study was to evaluate the potential of a numerical larynx model, considering the computational time and resources required. Using Large Eddy Simulations (LES) in a 3D numerical larynx model with prescribed motion of vocal folds, the complicated fluid-structure interaction problem in phonation was reduced to a pure flow simulation with moving boundaries. The simulated laryngeal flow field is in good agreement with the experimental results obtained from authors’ synthetic larynx model. By systematically decreasing the spatial and temporal resolutions of the numerical model and optimizing the computational resources of the simulations, the elapsed simulation time was reduced by 90% to less than 70 h for 10 oscillation cycles of the vocal folds. The proposed computational larynx model with reduced mesh resolution is still able to capture the essential laryngeal flow characteristics and produce results with sufficiently good accuracy in a significant shorter time-to-solution. The reduction in computational time achieved is a promising step towards the clinical application of these computational larynx models in the near future.

Normal voice is characterized by periodic oscillations of the vocal folds. On the other hand, disordered voice dynamics (e.g., subharmonic and aperiodic oscillations) are often associated with voice pathologies and dysphonia. Unfortunately, not all investigations may be conducted on human subjects; hence animal laryngeal studies have been performed for many years to better understand human phonation. The rabbit larynx has been shown to be a potential model of the human larynx. Despite this fact, only a few studies regarding the phonatory parameters of rabbit larynges have been performed. Further, to the best of our knowledge, no ex vivo study has systematically investigated phonatory parameters from high-speed, audio and subglottal pressure data with irregular oscillations. To remedy this, the present study analyzes experiments with sustained phonation in 11 ex vivo rabbit larynges for 51 conditions of disordered vocal fold dynamics. (1) The results of this study support previous findings on non-disordered data, that the stronger the glottal closure insufficiency is during phonation, the worse the phonatory characteristics are; (2) aperiodic oscillations showed worse phonatory results than subharmonic oscillations; (3) in the presence of both types of irregular vibrations, the voice quality (i.e., cepstral peak prominence) of the audio and subglottal signal greatly deteriorated compared to normal/periodic vibrations. In summary, our results suggest that the presence of both types of irregular vibration have a major impact on voice quality and should be considered along with glottal closure measures in medical diagnosis and treatment.

Laryngeal high-speed videoendoscopy (HSV) allows objective quantification of vocal fold vibratory characteristics. However, it is unknown how the analyzed sequence length affects some of the computed parameters. To examine if varying sequence lengths influence parameter calculation, 20 HSV recordings of healthy females during sustained phonation were investigated. The clinical prevalent Photron Fastcam MC2 camera with a frame rate of 4000 fps and a spatial resolution of 512 × 256 pixels was used to collect HSV data. The glottal area waveform (GAW), describing the increase and decrease of the area between the vocal folds during phonation, was extracted. Based on the GAW, 16 perturbation parameters were computed for sequences of 5, 10, 20, 50 and 100 consecutive cycles. Statistical analysis was performed using SPSS Statistics, version 21. Only three parameters (18.8%) were statistically significantly influenced by changing sequence lengths. Of these parameters, one changed until 10 cycles were reached, one until 20 cycles were reached and one, namely Amplitude Variability Index (AVI), changed between almost all groups of different sequence lengths. Moreover, visually observable, but not statistically significant, changes within parameters were observed. These changes were often most prominent between shorter sequence lengths. Hence, we suggest using a minimum sequence length of at least 20 cycles and discarding the parameter AVI.

Recently, we reported on the in vivo application of a miniaturized measuring device for 3D visualization of the superior vocal fold vibrations from high-speed recordings in combination with a laser projection unit (LPU). As a long-term vision for this proof of principle, we strive to integrate the further developed laserendoscopy as a diagnostic method in daily clinical routine. The new LPU mainly comprises a Nd:YAG laser source (532 nm/CW/2 ω ) and a diffractive optical element (DOE) generating a regular laser grid (31 × 31 laser points) that is projected on the vocal folds. By means of stereo triangulation, the 3D coordinates of the laser points are reconstructed from the endoscopic high-speed footage. The new design of the laserendoscope constitutes a compromise between robust image processing and laser safety regulations. The algorithms for calibration and analysis are now optimized with respect to their overall duration and the number of required interactions, which is objectively assessed using binary classifiers. The sensitivity and specificity of the calibration procedure are increased by 40.1% and 22.3%, which is statistically significant. The overall duration for the laser point detection is reduced by 41.9%. The suggested semi-automatic reconstruction software represents an important stepping-stone towards potential real time processing and a comprehensive, objective diagnostic tool of evidence-based medicine.

Abstract Voice production of humans and most mammals is governed by the MyoElastic-AeroDynamic (MEAD) principle, where an air stream is modulated by self-sustained vocal fold oscillation to generate audible air pressure fluctuations. An alternative mechanism is found in ultrasonic vocalizations of rodents, which are established by an aeroacoustic (AA) phenomenon without vibration of laryngeal tissue. Previously, some authors argued that high-pitched human vocalization is also produced by the AA principle. Here, we investigate the so-called “whistle register” voice production in nine professional female operatic sopranos singing a scale from C6 (≈ 1047 Hz) to G6 (≈ 1568 Hz). Super-high-speed videolaryngoscopy revealed vocal fold collision in all participants, with closed quotients from 30 to 73%. Computational modeling showed that the biomechanical requirements to produce such high-pitched voice would be an increased contraction of the cricothyroid muscle, vocal fold strain of about 50%, and high subglottal pressure. Our data suggest that high-pitched operatic soprano singing uses the MEAD mechanism. Consequently, the commonly used term “whistle register” does not reflect the physical principle of a whistle with regard to voice generation in high pitched classical singing.

Abstract Objective The objective of this study is to evaluate three‐dimensional vertical motion of the superior surface of the vocal folds in vivo in (a) typically developing children as a function of vocal frequency variations and (b) a child with vocal nodules. Methods A custom developed laser endoscope coupled with high‐speed videoendoscopy was used to obtain 3D parameters from 2 healthy children, one child with vocal nodules, and 23 vocally healthy adults (females = 11, males = 12). Parameters of amplitude (mm), maximum opening/closing velocity (mm/s), and mean opening/closing velocity (mm/s) were computed for the lateral and vertical vibratory motion along the anterior, middle, and posterior sections of the vocal folds were computed. Results We provide for the first time, absolute measurements of vertical amplitude and maximum/ mean velocity during the opening and closing phases, in vivo in children. Overall, the vertical motion was larger in vocally normal children compared with the lateral motion, especially along the visible posterior section of the vocal folds and during low pitch phonation. The opening phase dynamics were consistently large along the posterior section in the child with vocal nodules. Conclusions The study findings establish the feasibility of capturing 3D motion in a clinical setting and provide proof of concept for the application of the proposed 3D laser in the pediatric population. Future large sample size studies are needed to establish the diagnostic potential of examining the closing phase vertical motion to evaluate vibratory development in children with normal voice and investigating the opening phase vertical motion in children with nodules. Level of Evidence N/A.

The onset of phonation can be used as a biomarker for quantitative voice assessment and identification of phonation type, e.g., breathy, modal, and creaky. The onset of phonation can be calculated considering different modalities: acoustic, electroglottography (EGG), airflow, and glottal area waveforms. Considering the potential of voice onset in clinical applications, we have been developing the Voice Onset Analysis Tool (VOAT), a computer-aided program written in Python for the semi-automatic detection of vowel phonation onset. VOAT can detect the vowel onset on recordings with multiple phonations. Furthermore, the user can manually select the segments from the recording where the onset is present or apply a voice activity detection for automatic segmentation. VOAT provides filtering options to facilitate the detection and allows the saving of results in an Excel file for further processing. Our software also allows batch processing to detect vowel onset on several files automatically.

The primary acoustic signal of the voice is generated by the complex oscillation of the vocal folds (VFs), whereby physicians can barely examine the medial VF surface due to its anatomical inaccessibility. In this study, we investigated possibilities to infer medial surface dynamics by analyzing correlations in the oscillatory behavior of the superior and medial VF surfaces of four human hemilarynges, each in 24 different combinations of flow rate, VF adduction, and elongation. The two surfaces were recorded synchronously during sustained phonation using two high-speed camera setups and were subsequently 3D-reconstructed. The 3D surface parameters of mean and maximum velocities and displacements and general phonation parameters were calculated. The VF oscillations were also analyzed using empirical eigenfunctions (EEFs) and mucosal wave propagation, calculated from medial surface trajectories. Strong linear correlations were found between the 3D parameters of the superior and medial VF surfaces, ranging from 0.8 to 0.95. The linear regressions showed similar values for the maximum velocities at all hemilarynges (0.69–0.9), indicating the most promising parameter for predicting the medial surface. Since excessive VF velocities are suspected to cause phono-trauma and VF polyps, this parameter could provide added value to laryngeal diagnostics in the future.

Abstract Objective Use of computational fluid dynamic (CFD) simulations to measure the changes in upper airway geometry and aerodynamics during (a) an episode of Exercise‐Induced Laryngeal Obstruction (EILO) and (b) speech therapy exercises commonly employed for patients with EILO. Methods Magnetic resonance imaging stills of the upper airway including the nasal and oral cavities from an adult female were used to re‐construct three‐dimensional geometries of the upper airway. The CFD simulations were used to compute the maximum volume flow rate (l/s), pressure (Pa), airflow velocity (m/s) and area of cross‐section opening in eight planes along the vocal tract, separately for inhalation and exhalation. Results Numerical predictions from three‐dimensional geometrical modeling of the upper airway suggest that the technique of nose breathing for inhalation and pursed lip breathing for exhalation show most promising pressure conditions and cross‐sectional diameters for rescue breathing exercises. Also, if EILO is due to the constriction at the vocal fold level, then a quick sniff may also be a proper rescue inhalation exercise. EILO affects both the inspiratory and the expiratory phases of breathing. Conclusions A prior knowledge of the supraglottal aerodynamics and the corresponding upper airway geometry from CFD analysis has the potential to assist the clinician in choosing the most effective rescue breathing technique for optimal functional outcome of speech therapy intervention in patients with EILO and in understanding the pathophysiology of EILO on a case‐by‐case basis with future studies. Level of Evidence 4

Purpose: Individual prediction of treatment response is crucial for personalized treatment in multimodal approaches against head-and-neck squamous cell carcinoma (HNSCC). So far, no reliable predictive parameters for treatment schemes containing immunotherapy have been identified. This study aims to predict treatment response to induction chemo-immunotherapy based on the peripheral blood immune status in patients with locally advanced HNSCC. Methods: The peripheral blood immune phenotype was assessed in whole blood samples in patients treated in the phase II CheckRad-CD8 trial as part of the pre-planned translational research program. Blood samples were analyzed by multicolor flow cytometry before (T1) and after (T2) induction chemo-immunotherapy with cisplatin/docetaxel/durvalumab/tremelimumab. Machine Learning techniques were used to predict pathological complete response (pCR) after induction therapy. Results: The tested classifier methods (LDA, SVM, LR, RF, DT, and XGBoost) allowed a distinct prediction of pCR. Highest accuracy was achieved with a low number of features represented as principal components. Immune parameters obtained from the absolute difference (lT2-T1l) allowed the best prediction of pCR. In general, less than 30 parameters and at most 10 principal components were needed for highly accurate predictions. Across several datasets, cells of the innate immune system such as polymorphonuclear cells, monocytes, and plasmacytoid dendritic cells are most prominent. Conclusions: Our analyses imply that alterations of the innate immune cell distribution in the peripheral blood following induction chemo-immuno-therapy is highly predictive for pCR in HNSCC.

Abstract In laryngeal research, studying the vertical vocal fold oscillation component is often disregarded. However, vocal fold oscillation by its nature is a three-dimensional process. In the past, we have developed an in-vivo experimental protocol to reconstruct the full, three-dimensional vocal fold vibration. The goal of this study is to validate this 3D reconstruction method. We present an in-vivo canine hemilarynx setup using high-speed video recording and a right-angle prism for 3D reconstruction of vocal fold medial surface vibrations. The 3D surface is reconstructed from the split image provided by the prism. For validation, reconstruction error was calculated for objects located at a distance of up to 15 mm away from the prism. The influence of camera angle, changing calibrated volume, and calibration errors were determined. Overall average 3D reconstruction error is low and does not exceed 0.12 mm at 5 mm distance from the prism. Influence of a moderate (5°) and large (10°) deviation in camera angle led to a slight increase in error to 0.16 mm and 0.17 mm, respectively. This procedure is robust towards changes in calibration volume and small calibration errors. This makes this 3D reconstruction approach a useful tool for the reconstruction of accessible and moving tissue surfaces.

Vocal fold (VF) vibrations are the primary source of human phonation. High-speed video (HSV) endoscopy enables the computation of descriptive VF parameters for assessment of physiological properties of laryngeal dynamics, i.e., the vibration of the VFs. However, underlying biomechanical factors responsible for physiological and disordered VF vibrations cannot be accessed. In contrast, physically based numerical VF models reveal insights into the organ’s oscillations, which remain inaccessible through endoscopy. To estimate biomechanical properties, previous research has fitted subglottal pressure-driven mass–spring–damper systems, as inverse problem to the HSV-recorded VF trajectories, by global optimization of the numerical model. A neural network trained on the numerical model may be used as a substitute for computationally expensive optimization, yielding a fast evaluating surrogate of the biomechanical inverse problem. This paper proposes a convolutional recurrent neural network (CRNN)-based architecture trained on regression of a physiological-based biomechanical six-mass model (6 MM). To compare with previous research, the underlying biomechanical factor “subglottal pressure” prediction was tested against 288 HSV ex vivo porcine recordings. The contributions of this work are two-fold: first, the presented CRNN with the 6 MM handles multiple trajectories along the VFs, which allows for investigations on local changes in VF characteristics. Second, the network was trained to reproduce further important biomechanical model parameters like VF mass and stiffness on synthetic data. Unlike in a previous work, the network in this study is therefore an entire surrogate of the inverse problem, which allowed for explicit computation of the fitted model using our approach. The presented approach achieves a best-case mean absolute error (MAE) of 133 Pa (13.9%) in subglottal pressure prediction with 76.6% correlation on experimental data and a re-estimated fundamental frequency MAE of 15.9 Hz (9.9%). In-detail training analysis revealed subglottal pressure as the most learnable parameter. With the physiological-based model design and advances in fast parameter prediction, this work is a next step in biomechanical VF model fitting and the estimation of laryngeal kinematics.

ObjectiveTo systematically evaluate the evidence for the reliability, sensitivity and specificity of existing measures of vowel-initial voice onset.MethodsA literature search was conducted across electronic databases for published studies (MEDLINE, EMBASE, Scopus, Web of Science, CINAHL, PubMed Central, IEEE Xplore) and grey literature (ProQuest for unpublished dissertations) measuring vowel onset. Eligibility criteria included research of any study design type or context focused on measuring human voice onset on an initial vowel. Two independent reviewers were involved at each stage of title and abstract screening, data extraction and analysis. Data extracted included measures used, their reliability, sensitivity and specificity. Risk of bias and certainty of evidence was assessed using GRADE as the data of interest was extracted.ResultsThe search retrieved 6,983 records. Titles and abstracts were screened against the inclusion criteria by two independent reviewers, with a third reviewer responsible for conflict resolution. Thirty-five papers were included in the review, which identified five categories of voice onset measurement: auditory perceptual, acoustic, aerodynamic, physiological and visual imaging. Reliability was explored in 14 papers with varied reliability ratings, while sensitivity was rarely assessed, and no assessment of specificity was conducted across any of the included records. Certainty of evidence ranged from very low to moderate with high variability in methodology and voice onset measures used.ConclusionsA range of vowel-initial voice onset measurements have been applied throughout the literature, however, there is a lack of evidence regarding their sensitivity, specificity and reliability in the detection and discrimination of voice onset types. Heterogeneity in study populations and methods used preclude conclusions on the most valid measures. There is a clear need for standardisation of research methodology, and for future studies to examine the practicality of these measures in research and clinical settings.

High-speed videoendoscopy is a major tool for quantitative laryngology. Glottis segmentation and glottal midline detection are crucial for computing vocal fold-specific, quantitative parameters. However, fully automated solutions show limited clinical applicability. Especially unbiased glottal midline detection remains a challenging problem. We developed a multitask deep neural network for glottis segmentation and glottal midline detection. We used techniques from pose estimation to estimate the anterior and posterior points in endoscopy images. Neural networks were set up in TensorFlow/Keras and trained and evaluated with the BAGLS dataset. We found that a dual decoder deep neural network termed GlottisNetV2 outperforms the previously proposed GlottisNet in terms of MAPE on the test dataset (1.85% to 6.3%) while converging faster. Using various hyperparameter tunings, we allow fast and directed training. Using temporal variant data on an additional data set designed for this task, we can improve the median prediction accuracy from 2.1% to 1.76% when using 12 consecutive frames and additional temporal filtering. We found that temporal glottal midline detection using a dual decoder architecture together with keypoint estimation allows accurate midline prediction. We show that our proposed architecture allows stable and reliable glottal midline predictions ready for clinical use and analysis of symmetry measures.

Abstract High-speed videoendoscopy is an important tool to study laryngeal dynamics, to quantify vocal fold oscillations, to diagnose voice impairments at laryngeal level and to monitor treatment progress. However, there is a significant lack of an open source, expandable research tool that features latest hardware and data analysis. In this work, we propose an open research platform termed OpenHSV that is based on state-of-the-art, commercially available equipment and features a fully automatic data analysis pipeline. A publicly available, user-friendly graphical user interface implemented in Python is used to interface the hardware. Video and audio data are recorded in synchrony and are subsequently fully automatically analyzed. Video segmentation of the glottal area is performed using efficient deep neural networks to derive glottal area waveform and glottal midline. Established quantitative, clinically relevant video and audio parameters were implemented and computed. In a preliminary clinical study, we recorded video and audio data from 28 healthy subjects. Analyzing these data in terms of image quality and derived quantitative parameters, we show the applicability, performance and usefulness of OpenHSV. Therefore, OpenHSV provides a valid, standardized access to high-speed videoendoscopy data acquisition and analysis for voice scientists, highlighting its use as a valuable research tool in understanding voice physiology. We envision that OpenHSV serves as basis for the next generation of clinical HSV systems.

IntroductionGroup musical activities using wind instruments have been restricted during the CoVID19 pandemic due to suspected higher risk of virus transmission. It was presumed that the aerosols exhaled through the tubes while playing would be ejected over larger distances and spread into the room due to jet stream effects. In particular, the soprano recorder is widely used as an instrument in school classes, for beginners of all age groups in their musical education, in the context of leisure activities and in professional concert performances. Understanding the aerosol impulse dispersion characteristics of playing the soprano recorder could assist with the establishment of concepts for safe music-making.MethodsFive adult professionally trained soprano recorder players (4 female, 1 male) played four bars of the main theme of L. van Beethoven's "Ode to Joy" in low and in high octaves, as well as with 3 different potential protection devices in the high octave. For comparison they spoke the corresponding text by F. Schiller. Before each task, they inhaled .5 L of vapor from an e-cigarette filled with base liquid. The vapor cloud escaping during speaking or playing was recorded by cameras and its spread was measured as a function of time in the three spatial dimensions. The potential safety devices were rated for practicability with a questionnaire, and their influence on the sound was compared, generating a long-term average spectrum from the audio data.ResultsWhen playing in the high octave, at the end of the task the clouds showed a median distance of 1.06 m to the front and .57 m diameter laterally (maxima: x: 1.35 m and y: .97 m). It was found that the clouds' expansion values in playing the recorder with and without safety measures are mostly lower when compared to the ordinary, raised speaking voice of the same subjects. The safety devices which covered the instrument did not show clear advantages and were rated as unpractical by the subjects. The most effective reduction of the cloud was reached when playing into a suction funnel.ConclusionThe aerosol dispersion characteristics of soprano recorders seem comparable to clarinets. The tested safety devices which covered holes of the instrument did not show clear benefits.

Endoscopic high-speed video (HSV) systems for visualization and assessment of vocal fold dynamics in the larynx are diverse and technically advancing. To consider resulting “concepts shifts” for neural network (NN)-based image processing, re-training of already trained and used NNs is necessary to allow for sufficiently accurate image processing for new recording modalities. We propose and discuss several re-training approaches for convolutional neural networks (CNN) being used for HSV image segmentation. Our baseline CNN was trained on the BAGLS data set (58,750 images). The new BAGLS-RT data set consists of additional 21,050 images from previously unused HSV systems, light sources, and different spatial resolutions. Results showed that increasing data diversity by means of preprocessing already improves the segmentation accuracy (mIoU + 6.35%). Subsequent re-training further increases segmentation performance (mIoU + 2.81%). For re-training, finetuning with dynamic knowledge distillation showed the most promising results. Data variety for training and additional re-training is a helpful tool to boost HSV image segmentation quality. However, when performing re-training, the phenomenon of catastrophic forgetting should be kept in mind, i.e., adaption to new data while forgetting already learned knowledge.

Understanding the risk of infection by routine medical examination is important for the protection of the medical personnel. In this study we investigated respiratory particles emitted by patients during routine otolaryngologic procedures and assessed the risks for the performing physician. We developed two experimental setups to measure aerosol and droplet emission during rigid/flexible laryngoscopy, rhinoscopy, pharyngoscopy, otoscopy, sonography and patient interview for subjects with and without masks. A high-speed-camera setup was used to detect ballistic droplets (approx. > 100 µm) and an aerosol-particle-sizer was used to detect aerosol particles in the range of 0.3 µm to 10 µm. Aerosol particle counts were highly increased for coughing and slightly increased for heavy breathing in subjects without masks. The highest aerosol particle counts occurred during rigid laryngoscopy. During laryngoscopy and rhinoscopy, the examiner was exposed to increased particle emission due to close proximity to the patient’s face and provoked events such as coughing. However, even during sonography or otoscopy without a mask, aerosol particles were expelled close to the examiner. The physician’s exposure to respiratory particles can be reduced by deliberate choice of examination technique depending on medical indication and the use of appropriate equipment for the examiners and the patients (e.g., FFP2 masks for both).

Today, research into voice and speech is not only limited to acoustic, medical, and clinical studies and investigations [...]

Abstract Purpose The voice is the most important instrument of communication. Tissue defects in the vocal fold (VF) area lead to serious reduction in quality of life, but thus far, no satisfactory VF implant exists. Therefore, we aim to establish a functional VF implant in a rabbit model by magnetic tissue engineering (MTE) using superparamagnetic iron oxide nanoparticles (SPION). Hence, iron quantification over time as well as cell behavior studies upon SPION treatment are of great importance. Methods Rabbit VF fibroblasts (VFF) were treated with different concentrations of SPIONs (20, 40, and 80 μg/cm2), and iron content was examined for up to 40 days using microwave plasma-atom emission spectroscopy. The effects of SPION treatment on VFF (adhesion, spreading, and migration), which are important for the formation of 3D structures, were tested. Results Cellular SPION quantification revealed that there was no residual iron remaining in VFFs after 40 days. SPIONs had a dose-dependent effect on cell adhesion, with good tolerability observed up to 20 μg/cm2. Migration and spreading were not significantly influenced by SPION treatment up to 80 μg/cm2. Discussion and Conclusion To develop 3D structures, cell behavior should not be affected by SPION uptake. After 40 days, cells were free of iron as a result of metabolism or rarefication during cell division. Cell functions including adhesion, spreading, and migration were proven to be intact in a dose-dependent manner after SPION treatment, suggesting a safe usage of MTE for voice rehabilitation. Our results thus constitute a solid basis for a successful transfer of this technique into 3D constructs, in order to provide an individual and personalized human VF implant in the future.

Objectives The study was designed to evaluate the tissue expression of NRP-1 and serum level of sNRP-1 in the same patients with intraepithelial laryngeal lesions or early staged laryngeal cancer to identify the clinical significance of these biomarkers in the diagnosis of laryngeal lesions. Material and methods A prospective analysis of tissue was performed on specimens and blood samples from 49 patients, who were admitted for surgical resection due to suspicious vocal fold lesions and were diagnosed as non-dysplasia, low-grade dysplasia, high-grade dysplasia and invasive cancers. Results ELISA was conducted on 48 blood samples. The minimum level of sNRP-1 was 0.15 ng/ml and maximum– 37.71 ng/ml. The Kruskal–Wallis one-way analysis of variance revealed no differences in sNRP-1 levels between different histopathological stages of vocal fold lesions (p = 0.234). IHC was conducted in 49 tissue samples. The evaluated mean scores of NRP-1 tissue expression were compared to histopathological stage of the lesion. The Kruskal–Wallis one-way analysis of variance revealed no differences in NRP-1 tissue expression between different histopathological stages of vocal fold lesions (p = 0.536). The correlation of tissue NRP-1 expression and serum levels of NRP-1 within analyzed group was insignificant. The Spearman’s rank correlation coefficient was 0.076 (p = 0.606). Conclusions The NRP-1 tissue expression and serum levels are unlikely to be a prognostic factor for identification of laryngeal dysplasia or early stage laryngeal cancer. Further studies investigating biomolecules involved in laryngeal carcinogenesis are necessary.

The flow-induced sound sources of human voice production are investigated based on a validated voice model. This analysis is performed using a hybrid aeroacoustic workflow based on the perturbed convective wave equation. In the first step, the validated 3D incompressible turbulent flow simulation is computed by the finite volume method using STARCCM+. In a second step, the aeroacoustic sources are evaluated and studied in detail. The formulation of the sound sources is compared to the simplification (neglecting the convective sources) systematically using time-domain and Fourier-space analysis. Additionally, the wave equation is solved with the finite element solver openCFS to obtain the 3D sound field in the acoustic far-field. During the detailed effect analysis, the far-field sound spectra are compared quantitatively, and the flow-induced sound sources are visualized within the larynx. In this contribution, it is shown that the convective part of the sources dominates locally near the vocal folds (VFs) while the local time derivative of the incompressible pressure is distributed in the whole supra-glottal area. Although the maximum amplitude of the time derivative is lower, the integral contribution dominates the sound spectrum. As a by-product of the detailed perturbed convective wave equation source study, we show that the convective source term can be neglected since it only reduces the validation error by 0.6%. Neglecting the convective part reduces the algorithmic complexity of the aeroacoustic source computation of the perturbed convective wave equation and the stored flow data. From the source visualization, we learned how the VF motion transforms into specific characteristics of the aeroacoustic sources. We found that if the VFs are fully closing, the aeroacoustic source terms yield the highest dynamical range. If the VFs are not fully closing, VFs motion does not provide as much source energy to the flow-induced sound sources as in the case of a healthy voice. As a consequence of not fully closing VFs, the cyclic pulsating velocity jet is not cut off entirely and therefore turbulent structures are permanently present inside the supraglottal region. These turbulent structures increase the broadband component of the voice signal, which supports research results of previous studies regarding glottis closure and insufficient voice production.

Mucus consistency affects voice physiology and is connected to voice disorders. Nevertheless, the rheological characteristics of human laryngeal mucus from the vocal folds remain unknown. Knowledge about mucus viscoelasticity enables fabrication of artificial mucus with natural properties, more realistic ex-vivo experiments and promotes a better understanding and improved treatment of dysphonia with regard to mucus consistency. We studied human laryngeal mucus samples from the vocal folds with two complementary approaches: 19 samples were successfully applied to particle tracking microrheology (PTM) and five additional samples to oscillatory shear rheology (OSR). Mucus was collected by experienced laryngologists from patients together with demographic data. The analysis of the viscoelasticity revealed diversity among the investigated mucus samples according to their rigidity (absolute G′ and G″). Moreover some samples revealed throughout solid-like character (G′ > G″), whereas some underwent a change from solid-like to liquid-like (G′ < G″). This led to a subdivision into three groups. We assume that the reason for the differences is a variation in the hydration level of the mucus, which affects the mucin concentration and network formation factors of the mucin mesh. The demographic data could not be correlated to the differences, except for the smoking behavior. Mucus of predominant liquid-like character was associated with current smokers.

Most sports like surfing are highly developed. It is necessary to tease the last percentages out of the competitors and equipment—in the case of surfing the surfboard-fin-system—to win competitions or championships. In this computational investigation, a parameter study of the positioning of the two rear fins within a 4-fin configuration with fixed front fins on a surfboard is executed to find appropriate fin positions for specific surf situations. Four different inflow velocities are investigated. The RANS and URANS models combined with the SST k − ω turbulence model, which is available within the computational fluid dynamics (CFD) package STAR-CCM+, are used to simulate the flow field around the fins for angles of attack (AoA) between 0° and 45°. The simulation results show that shifting the rear fins toward the longitudinal axis of the surfboard lowers the maximum lift. Surfboards with 4-fin configurations are slower in nearly the whole range of AoA due to a higher drag force but produce a higher lift force compared to the 3-fin configuration. The lift and drag forces increase significantly with increasing inflow velocity. This study shows a significant influence of the rear fin positioning and the inflow velocity on lift and drag performance characteristics.

Voiced speech is the result of a fluid-structure-acoustic interaction in larynx and vocal tract (VT). Previous studies show a strong influence of the VT on this interaction process, but are limited to individually obtained VT geometries. In order to overcome this restriction and to provide a more general VT replica, we computed a simplified, averaged VT geometry for the vowel /a/. The basis for that were MRI-derived cross-sections along the straightened VT centerline of six professional tenors. The resulting mean VT replica, as well as realistic and simplified VT replicas of each tenor were 3D-printed for experiments with silicone vocal folds that show flow-induced oscillations. Our results reveal that all replicas, including the mean VT, reproduce the characteristic formants with mean deviations of 12% when compared with the subjects’ audio recordings. The overall formant structure neither is impaired by the averaging process, nor by the simplified geometry. Nonetheless, alterations in the broadband, non-harmonic portions of the sound spectrum indicate changed aerodynamic characteristics within the simplified VT. In conclusion, our mean VT replica shows similar formant properties as found in vivo. This indicates that the mean VT geometry is suitable for further investigations of the fluid-structure-acoustic interaction during phonation.

Human voice is generated in the larynx by the two oscillating vocal folds. Owing to the limited space and accessibility of the larynx, endoscopic investigation of the actual phonatory process in detail is challenging. Hence the biomechanics of the human phonatory process are still not yet fully understood. Therefore, we adapt a mathematical model of the vocal folds towards vocal fold oscillations to quantify gender and age related differences expressed by computed biomechanical model parameters.The vocal fold dynamics are visualized by laryngeal high-speed videoendoscopy (4000 fps). A total of 33 healthy young subjects (16 females, 17 males) and 11 elderly subjects (5 females, 6 males) were recorded. A numerical two-mass model is adapted to the recorded vocal fold oscillations by varying model masses, stiffness and subglottal pressure. For adapting the model towards the recorded vocal fold dynamics, three different optimization algorithms (Nelder-Mead, Particle Swarm Optimization and Simulated Bee Colony) in combination with three cost functions were considered for applicability. Gender differences and age-related kinematic differences reflected by the model parameters were analyzed.The biomechanical model in combination with numerical optimization techniques allowed phonatory behavior to be simulated and laryngeal parameters involved to be quantified. All three optimization algorithms showed promising results. However, only one cost function seems to be suitable for this optimization task. The gained model parameters reflect the phonatory biomechanics for men and women well and show quantitative age- and gender-specific differences. The model parameters for younger females and males showed lower subglottal pressures, lower stiffness and higher masses than the corresponding elderly groups. Females exhibited higher subglottal pressures, smaller oscillation masses and larger stiffness than the corresponding similar aged male groups. Optimizing numerical models towards vocal fold oscillations is useful to identify underlying laryngeal components controlling the phonatory process.

Due to a lack of empirical data, the current understanding of the laryngeal mechanics in the passaggio regions (i.e., the fundamental frequency ranges where vocal registration events usually occur) of the female singing voice is still limited.In this study the first and second passaggio regions of 10 professionally trained female classical soprano singers were analyzed. The sopranos performed pitch glides from A3 (ƒo = 220 Hz) to A4 (ƒo = 440 Hz) and from A4 (ƒo = 440 Hz) to A5 (ƒo = 880 Hz) on the vowel [iː]. Vocal fold vibration was assessed with trans-nasal high speed videoendoscopy at 20,000 fps, complemented by simultaneous electroglottographic (EGG) and acoustic recordings. Register breaks were perceptually rated by 12 voice experts. Voice stability was documented with the EGG-based sample entropy. Glottal opening and closing patterns during the passaggi were analyzed, supplemented with open quotient data extracted from the glottal area waveform.In both the first and the second passaggio, variations of vocal fold vibration patterns were found. Four distinct patterns emerged: smooth transitions with either increasing or decreasing durations of glottal closure, abrupt register transitions, and intermediate loss of vocal fold contact. Audible register transitions (in both the first and second passaggi) generally coincided with higher sample entropy values and higher open quotient variance through the respective passaggi.Noteworthy vocal fold oscillatory registration events occur in both the first and the second passaggio even in professional sopranos. The respective transitions are hypothesized to be caused by either (a) a change of laryngeal biomechanical properties; or by (b) vocal tract resonance effects, constituting level 2 source-filter interactions.

Though deliberative theory has a bias toward rigorous argument and democratic social relations, it presumes that an ideal discursive process otherwise has a neutral stance with respect to particular ideologies and cultural values. This essay provides a preliminary test of that assumption by examining attitude change across a wide range of Deliberation Polls held across the globe. We analyzed 65 questionnaire statements on which Poll participants significantly changed their views on a wide variety of issues. By coding each of these survey items on various value dimensions, we were able to look for any obvious patterns of attitude change. Despite its small size and the exclusion of items showing no attitude change, this sample showed that Poll respondents tend to move toward more cosmopolitan, egalitarian, and collectivist value orientations. Further analysis showed the strongest value-laden shifts were on empirical statements, with public opinion on such questions shifting moderately toward cosmopolitan and collectivist beliefs. The conclusion considers the implications of these findings for deliberative theory, research, and practice.