Voice Production Mechanisms Research Articles

Special Issue on Current Trends and Future Directions in Voice Acoustics Measurement

The human voice production mechanism implements a superbly rich communication channel that at once tells us what, who, how, and much more [...]

Prevalence of Voice Problems and Associated Risk Factors Among Tamil-Speaking Imams

Voice of Professional Voice Users (PVUs) are of particular interest to practicing Speech-Language Pathologists. There is a dearth of studies concerning the prevalence of voice disorders and the associated risk factors among Tamil-speaking Imams. We address this research gap using non-experimental survey research. A questionnaire was framed by reviewing earlier literature. The derived questionnaire was administered to one hundred Tamil-speaking Imams actively involved in religious service in Tamil Nadu. We analyzed the obtained responses quantitatively and qualitatively. We also examined the effect of age on the prevalence of voice disorders and associated risk factors. Based on survey responses, the career prevalence of voice problems among Tamil-speaking Imams was as high as 89%, and the point prevalence was 64%. The general health status of the Imams were good. However, vocal health was not satisfactory. This study identified several factors that contribute to voice problems, such as constant use of loud voice, acid reflux, unhealthy vocal habits, and insufficient hydration. A positive aspect observed during this study was the absence of smoking and consumption of alcohol among Imams. Even though the Imams presented good awareness of the voice production mechanism, they reported not seeking medical help when facing a voice problem. Current findings report a minimal impact of age-related differences on associated risk factors for voice disorders among the Imams. Voice disorders are prevalent among Tamil-speaking Imams. Several risk factors leading to voice disorders among these individuals need to be addressed.

A Prospective Observational Study to Determine the Added Clinical Value of Videokymography to Videostroboscopy in Patients with Change in Voice.

Videolaryngostroboscopy (VLS) is considered gold standard method for assessing voice disorders. But patients with irregular waveform of vocal folds cannot benefit from the VLS. Videokymography [VKG] is a single line real time, high speed imaging technique. It detects voice disorders based on vocal fold vibration characteristics whether the vibrations are regular or irregular. There is no standard clinical protocol or evidence on the clinical relevance of VKG for functional assessment of voice disorders. Since mechanism of voice production depends on vibration characteristics, VKG imaging leads to new possibilities for diagnosis, objective documentation and monitoring of vocal fold behavior in clinical practice in case of voice disorders. This study aims to evaluate clinical value of VKG in addition to VLS as a complementary tool for the assessment of voice disorder.

Laryngeal and Voice Disorders in Patients with Pulmonary Tuberculosis.

Introduction:Laryngeal tuberculosis (LTB) is the most frequent granulomatous disease of the larynx. The aim of the present work was to study the laryngostroboscopic features and voice quality of patients with laryngeal TB secondary to pulmonary TB.Materials and Methods:Participants were 35 patients diagnosed as having pulmonary TB and dysphonia. All patients had a complete history, clinical and laboratory workup. Patients were assessed using a protocol of voice assessment which included Auditory-perceptual analysis of voice, voice analysis using the Multidimensional Voice Profile (MDVP), and laryngostroboscopy. Results:The participants were 24 males and 11 females and their mean age was 43.7 years. The voice acoustic analysis revealed a significant difference from normal in jitter percent, shimmer percent, and harmonic to noise (H/N) ratio. Laryngeal gross lesions were found in 11 patients while the other 24 patients had normal laryngoscopic findings with nonspecific stroboscopic changes as reduced mucosal waves and mild glottic gap. Diffuse lesion of the whole vocal folds was found in 5 patients and anterior predilection in 4 patients. The type of lesions were granulomatous lesions in 7 patients and non-specific inflammatory mild exophytic lesions in 4 patients. Conclusions:Voice disorders in pulmonary TB include disturbance in the mechanism of voice production with or without detectable laryngeal lesion. Videostroboscopy has the advantage of showing the extension of laryngeal involvement, vocal folds vibrations, and mucosal waves.

Acoustic to kinematic projection in Parkinson’s disease dysarthria

Speech signal analysis is a powerful tool that facilitates the monitoring and tracking of symptom deterioration caused by neurodegenerative disorders, typically achieved using either sustained vowels, diadochokinetic exercises or running speech. This study expands our previous work on the study of the movement produced by the jaw-tongue biomechanical system. The aim is to further investigate the effects of neuromotor activity during muscular exertion that translates formant acoustics into speech articulatory movements affected by hypokinetic dysarthria in Parkinson’s Disease (PD). The objective of this study is to estimate the parameters of an inverse acoustic-to-kinematic projection model that takes as an input the variations of the first and second formants and estimates as output the spatial variation of the jaw-tongue biomechanical system. The spatial variations have been extracted from 3D accelerometry (3DAcc). These serve as ground truth for comparison with the estimated activity projected from speech kinematics, as a measure of fitness of the inverse model. The estimation method is a two step process: first initial weight values are produced using multiple regression between each of the formant dynamic signals (acoustical analysis) and the estimated spatial variations (accelerometry). The second step uses a weight refinement method based on gradient-descent. Additionally, a time-realignment study has been carried out on the acoustic-to-kinematic projection model, based on the estimation of relative time displacements as to maximize the cross-correlation between signals. The study is complemented with an estimation of the model weights on a dataset from PD participants and Healthy Controls (HC). This methodology opens up new ways to investigate the underlying physiological voice production mechanism which may offer new insights into PD symptoms.

A Comparison of Cepstral Features in the Detection of Pathological Voices by Varying the Input and Filterbank of the Cepstrum Computation

Automatic voice pathology detection enables objective assessment of pathologies that affect the voice production mechanism. Detection systems have been developed using the traditional pipeline approach (consisting of the feature extraction part and the detection part) and using the modern deep learning -based end-to-end approach. Due to the lack of vast amounts of training data in the study area of pathological voice, the former approach is still a valid choice. In the existing detection systems based on the traditional pipeline approach, the mel-frequency cepstral coefficient (MFCC) features can be regarded as the defacto standard feature set. In this study, automatic voice pathology detection is investigated by comparing the performance of various MFCC variants derived by considering two factors: the input and the filterbank in the cepstrum computation. For the first factor, three inputs (the voice signal, the glottal source and the vocal tract) are compared. The glottal source and the vocal tract are estimated using the quasi-closed phase glottal inverse filtering method. For the second factor, the mel-frequency and linear-frequency filterbanks are compared. Experiments were conducted separately using six databases consisting of voices produced by speakers suffering from one of four disorders (dysphonia, Parkinson’s disease, laryngitis, or heart failure) and by healthy speakers. Support vector machine (SVM) was used as the classifier. The results show that by combining mel- and linear-frequency cepstral coefficients derived from the glottal source and vocal tract, better overall detection accuracy was obtained compared to the defacto MFCC features derived from the voice signal. Furthermore, this combination provided comparable or better performance than four existing cepstral feature extraction techniques in clean and high signal-to-noise ratio (SNR) conditions.

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.

Toward Development of a Vocal Fold Contact Pressure Probe: Bench-Top Validation of a Dual-Sensor Probe Using Excised Human Larynx Models.

A critical element in understanding voice production mechanisms is the characterization of vocal fold collision, which is widely considered a primary etiological factor in the development of common phonotraumatic lesions such as nodules and polyps. This paper describes the development of a transoral, dual-sensor intraglottal/subglottal pressure probe for the simultaneous measurement of vocal fold collision and subglottal pressures during phonation using two miniature sensors positioned 7.6 mm apart at the distal end of a rigid cannula. Proof-of-concept testing was performed using excised whole-mount and hemilarynx human tissue aerodynamically driven into self-sustained oscillation, with systematic variation of the superior–inferior positioning of the vocal fold collision sensor. In the hemilarynx experiment, signals from the pressure sensors were synchronized with an acoustic microphone, a tracheal-surface accelerometer, and two high-speed video cameras recording at 4000 frames per second for top-down and en face imaging of the superior and medial vocal fold surfaces, respectively. As expected, the intraglottal pressure signal exhibited an impulse-like peak when vocal fold contact occurred, followed by a broader peak associated with intraglottal pressure build-up during the de-contacting phase. As subglottal pressure was increased, the peak amplitude of the collision pressure increased and typically reached a value below that of the average subglottal pressure. Results provide important baseline vocal fold collision pressure data with which computational models of voice production can be developed and in vivo measurements can be referenced.

GlotNet—A Raw Waveform Model for the Glottal Excitation in Statistical Parametric Speech Synthesis

Recently, generative neural network models which operate directly on raw audio, such as WaveNet, have improved the state of the art in text-to-speech synthesis TTS. Moreover, there is increasing interest in using these models as statistical vocoders for generating speech waveforms from various acoustic features. However, there is also a need to reduce the model complexity, without compromising the synthesis quality. Previously, glottal pulseforms i.e., time-domain waveforms corresponding to the source of human voice production mechanism have been successfully synthesized in TTS by glottal vocoders using straightforward deep feedforward neural networks. Therefore, it is natural to extend the glottal waveform modeling domain to use the more powerful WaveNet-like architecture. Furthermore, due to their inherent simplicity, glottal excitation waveforms permit scaling down the waveform generator architecture. In this study, we present a raw waveform glottal excitation model, called GlotNet, and compare its performance with the corresponding direct speech waveform model, WaveNet, using equivalent architectures. The models are evaluated as part of a statistical parametric TTS system. Listening test results show that both approaches are rated highly in voice similarity to the target speaker, and obtain similar quality ratings with large models. Furthermore, when the model size is reduced, the quality degradation is less severe for GlotNet.

Feature Maps of the Acoustic Spectrum of the Voice

The change in the spectrum of sustained /a/ vowels was mapped over the voice range from low to high fundamental frequency and low to high sound pressure level (SPL), in the form of the so-called voice range profile (VRP). In each interval of one semitone and one decibel, narrowband spectra were averaged both within and across subjects. The subjects were groups of 7 male and 12 female singing students, as well as a group of 16 untrained female voices. For each individual and also for each group, pairs of VRP recordings were made, with stringent separation of the modal/chest and falsetto/head registers. Maps are presented of eight scalar metrics, each of which was chosen to quantify a particular feature of the voice spectrum, over fundamental frequency and SPL. Metrics 1 and 2 chart the role of the fundamental in relation to the rest of the spectrum. Metrics 3 and 4 are used to explore the role of resonances in relation to SPL. Metrics 5 and 6 address the distribution of high frequency energy, while metrics 7 and 8 seek to describe the distribution of energy at the low end of the voice spectrum.Several examples are observed of phenomena that are difficult to predict from linear source-filter theory, and of the voice source being less uniform over the voice range than is conventionally assumed. These include a high-frequency band-limiting at high SPL and an unexpected persistence of the second harmonic at low SPL. The two voice registers give rise to clearly different maps. Only a few effects of training were observed, in the low frequency end below 2 kHz. The results are of potential interest in voice analysis, voice synthesis and for new insights into the voice production mechanism.

The Influence of Posture and Balance on Voice: A Review

The role of posture in vocal performance is recognized for many years. Speech therapists and singing teachers use this knowledge to correct bad postures to improve vocal quality with good results, although most of that knowledge is empirical.
 This review evaluates the influence of posture and balance on voice.
 Modification in posture secondary to exogenous stimulation can affect voice, while alterations to the voice production mechanism can cause modifications in posture.
 Vocal effort results in segmental alterations of posture, accompanied by global postural changes. Dysphonic individuals demonstrate a greater displacement of the centre of gravity forward, which results in postural instability, increasing muscular work to maintain the posture and balance. After vocal rehabilitation, dysphonic patients presented an improvement in posture parameters in static and dynamic posturography.
 Posturography evaluation of patients before and after vocal treatment may represent a clinically useful variable in evaluating the efficacy of vocal therapy.

A training-based speech regeneration approach with cascading mapping models

Computational speech reconstruction algorithms have the ultimate aim of returning natural sounding speech to aphonic and dysphonic patients as well as those who can only whisper. In particular, individuals who have lost glottis function due to disease or surgery, retain the power of vocal tract modulation to some degree but they are unable to speak anything more than hoarse whispers without prosthetic aid. While whispering can be seen as a natural and secondary aspect of speech communications for most people, it becomes the primary mechanism of communications for those who have impaired voice production mechanisms, such as laryngectomees.In this paper, by considering the current limitations of speech reconstruction methods, a novel algorithm for converting whispers to normal speech is proposed and the efficiency of the algorithm is explored. The algorithm relies upon cascading mapping models and makes use of artificially generated whispers (called whisperised speech) to regenerate natural phonated speech from whispers. Using a training-based approach, the mapping models exploit whisperised speech to overcome frame to frame time alignment problems that are inherent in the speech reconstruction process. This algorithm effectively regenerates missing information in the conventional frameworks of phonated speech reconstruction, and is able to outperform the current state-of-the-art regeneration methods using both subjective and objective criteria.

Effects of age on the amplitude, frequency and perceived quality of voice.

The manner and extent to which voice amplitude and frequency control mechanisms change with age is not well understood. The related question of whether the assessment of one's own voice evolves with age, concomitant with the acoustical changes that the voice undergoes, also remains unanswered. In the present study, we characterized the aging of voice production mechanisms (amplitude, frequency), compared the aging voice in different experimental contexts (vowel utterance, connected speech) and examined the relationship between voice self-assessment and age-related voice acoustical changes. Eighty healthy adults (20 to 75 years old) participated in the study, which involved computation of several acoustical measures of voice (including measures of fundamental frequency, voice amplitude, and stability) as well as self-assessments of voice. Because depression is frequent in older adults, depression and anxiety scores were also measured. As was expected, analyses revealed age effects on most acoustical measures. However, there was no interaction between age and the ability to produce high/low voice amplitude/frequency, suggesting that voice amplitude and frequency control mechanisms are preserved in aging. Multiple mediation analyses demonstrated that the relationship between age and voice self-assessment was moderated by depression and anxiety scores. Taken together, these results reveal that while voice production undergoes important changes throughout aging, the ability to increase/decrease the amplitude and frequency of voice are preserved, at least within the age range studied, and that depression and anxiety scores have a stronger impact on perceived voice quality than acoustical changes themselves.

Reconstruction of Phonated Speech from Whispers Using Formant-Derived Plausible Pitch Modulation

Whispering is a natural, unphonated, secondary aspect of speech communications for most people. However, it is the primary mechanism of communications for some speakers who have impaired voice production mechanisms, such as partial laryngectomees, as well as for those prescribed voice rest, which often follows surgery or damage to the larynx. Unlike most people, who choose when to whisper and when not to, these speakers may have little choice but to rely on whispers for much of their daily vocal interaction. Even though most speakers will whisper at times, and some speakers can only whisper, the majority of today’s computational speech technology systems assume or require phonated speech. This article considers conversion of whispers into natural-sounding phonated speech as a noninvasive prosthetic aid for people with voice impairments who can only whisper. As a by-product, the technique is also useful for unimpaired speakers who choose to whisper. Speech reconstruction systems can be classified into those requiring training and those that do not. Among the latter, a recent parametric reconstruction framework is explored and then enhanced through a refined estimation of plausible pitch from weighted formant differences. The improved reconstruction framework, with proposed formant-derived artificial pitch modulation, is validated through subjective and objective comparison tests alongside state-of-the-art alternatives.

Using image processing technology and mathematical algorithm in the automatic selection of vocal cord opening and closing images from the larynx endoscopy video

The human larynx is an important organ for voice production and respiratory mechanisms. The vocal cord is approximated for voice production and open for breathing. The videolaryngoscope is widely used for vocal cord examination. At present, physicians usually diagnose vocal cord diseases by manually selecting the image of the vocal cord opening to the largest extent (abduction), thus maximally exposing the vocal cord lesion. On the other hand, the severity of diseases such as vocal palsy, atrophic vocal cord is largely dependent on the vocal cord closing to the smallest extent (adduction). Therefore, diseases can be assessed by the image of the vocal cord opening to the largest extent, and the seriousness of breathy voice is closely correlated to the gap between vocal cords when closing to the smallest extent. The aim of the study was to design an automatic vocal cord image selection system to improve the conventional selection process by physicians and enhance diagnosis efficiency. Also, due to the unwanted fuzzy images resulting from examination process caused by human factors as well as the non-vocal cord images, texture analysis is added in this study to measure image entropy to establish a screening and elimination system to effectively enhance the accuracy of selecting the image of the vocal cord closing to the smallest extent.

Behandlung von Glottisschlussinsuffizienzen

Glottal gaps can be either physiological or pathological. The latter are multifactorial, predominantly organic in origin and occasionally functional. Organic causes include vocal fold paralysis or scarring, as well as a deficiency or excess of tissue. In addition to loss of the mucosal wave, the degree of hoarseness is primarily determined by the circumferential area of the glottal gap. It is thus important to quantify the extent of glottal insufficiency. Although a patient's symptoms form the basis for treatment decisions, these may be subjective and inadequately reflected by the results of auditory-perceptual evaluation, voice analysis and voice performance tests. The therapeutic approach should always combine phonosurgery with conventional voice therapy methods. Voice therapy utilises all the resources made available by the sphincter model of the aerodigestive tract and knowledge on the mechanism of voice production. The aim of phonosurgery is medialization, reconstruction or reinnervation by injection laryngoplasty or larynx framework surgery. These different methods can be combined and often applied directly after vocal fold surgery (primary reconstruction). In conclusion, the techniques described here can be effectively employed to compensate for glottal gaps.

High-Speed Videoendoscopic Analysis of Relationships between Cepstral-Based Acoustic Measures and Voice Production Mechanisms in Patients Undergoing Phonomicrosurgery

There is increased interest in using cepstral-based acoustic measures for objective clinical voice assessment because of their apparent advantages over more time-honored methods, but there is a paucity of information about how these newer measures relate to underlying phonatory mechanisms. We investigated the relationships between the acoustic cepstral peak magnitude (CPM) and high-speed videoendoscopy (HSV)-based measures of vocal fold phonatory function in 20 subjects who underwent phonomicrosurgery for vocal fold lesions. Acoustic and imaging data were acquired during sustained vowel phonation before and after surgery. The changes in the measures between presurgical and postsurgical assessments showed that the CPM correlated significantly with an HSV-based measure combining fundamental frequency deviation and average speed quotient (r = 0.70; p < 0.001) in a multiple linear regression, and that the variation in the CPM could also be attributed to trading relationships between the HSV-based measures of vibratory phase asymmetry and glottal closure. These initial results demonstrate that the clinical utility of cepstral-based measures can be enhanced by a better understanding of how these acoustic measures relate to underlying phonatory mechanisms. The CPM seems to integrate information about aperiodicity in vocal fold vibration, the relative speed of glottal closure, and estimates of glottal noise generation.

Glottal inverse filtering analysis of human voice production — A review of estimation and parameterization methods of the glottal excitation and their applications

Glottal inverse filtering (GIF) refers to methods of estimating the source of voiced speech, the glottal volume velocity waveform. GIF is based on the idea of inversion, in which the effects of the vocal tract and lip radiation are cancelled from the output of the voice production mechanism, the speech signal. This article provides a review on GIF research by examining an era spanning five decades during which this topic has been under development. The topic is handled from three main perspectives: the estimation methods of the glottal source, the parameterization techniques that have been developed to express the estimated glottal excitations in numerical forms, and the application areas of GIF. Finally, the strengths and limitations of the GIF approach are discussed.

Use of laryngeal high-speed videoendoscopy systems to study voice production mechanisms in human subjects

Advances in laryngeal high-speed videoendoscopy (HSV) are making it possible to investigate critical relationships between vocal fold physiology and acoustic voice production in human subjects. Our group has developed HSV systems for clinical research with synchronous acquisition of acoustics, electroglottography, neck skin acceleration, and, in the most comprehensive setup, airflow and intraoral pressure. Key results will be presented from examinations of source-filter coupling and studies of the acoustic impact of vocal fold vibratory asymmetry in subjects with and without voice disorders. Findings hold potential clinical significance by revealing acoustic-HSV relationships not observable using standard stroboscopic imaging, as well as contributing to the direct evaluation and eventual improvement of voice production models. The work of T. F. Quatieri was supported by the Department of Defense under Air Force contract FA8721-05-C-0002. The work of other authors was supported by grants from the NIH National Institute on Deafness and Other Communication Disorders (T32 DC00038 and R01 DC007640) and by the Institute of Laryngology and Voice Restoration.

Mapping emotions into acoustic space: The role of voice production

Research on the vocal expression of emotion has long since used a “fishing expedition” approach to find acoustic markers for emotion categories and dimensions. Although partially successful, the underlying mechanisms have not yet been elucidated. To illustrate that this research can profit from considering the underlying voice production mechanism, we specifically analyzed short affect bursts (sustained/a/vowels produced by 10 professional actors for five emotions) according to physiological variations in phonation (using acoustic parameters derived from the acoustic signal and the inverse filter estimated voice source waveform). Results show significant emotion main effects for 11 of 12 parameters. Subsequent principal components analysis revealed three components that explain acoustic variations due to emotion, including “tension,” “perturbation,” and “voicing frequency.” These results suggest that future work may benefit from theory-guided development of parameters to assess differences in physiological voice production mechanisms in the vocal expression of different emotions.