Electroglottograph Research Articles

Fundamental Frequency Estimation of Low-quality Electroglottographic Signals

Fundamental frequency (fo) is often estimated based on electroglottographic (EGG) signals. Because of the nature of the method, the quality of EGG signals may be impaired by certain features like amplitude or baseline drifts, mains hum, or noise. The potential adverse effects of these factors on fo estimation have to date not been investigated. Here, the performance of 13 algorithms for estimating fo was tested, based on 147 synthesized EGG signals with varying degrees of signal quality deterioration. Algorithm performance was assessed through the standard deviation σfo of the difference between known and estimated fo data, expressed in octaves. With very few exceptions, simulated mains hum, and amplitude and baseline drifts did not influence fo results, even though some algorithms consistently outperformed others. When increasing either cycle-to-cycle fo variation or the degree of subharmonics, the SIGMA algorithm had the best performance (max. σfo = 0.04). That algorithm was, however, more easily disturbed by typical EGG equipment noise, whereas the NDF and Praat's auto-correlation algorithms performed best in this category (σfo = 0.01). These results suggest that the algorithm for fo estimation of EGG signals needs to be selected specifically for each particular data set. Overall, estimated fo data should be interpreted with care.

Assessment of short-term functional voice therapy in patients with unilateral paralysis of the larynx.

Introduction Laryngeal paralysis deteriorates all laryngeal functions. Therefore the therapeutic process must include restoration of respiratory, defensive and vocal function. Selection of a proper rehabilitation path plays a key role. Appropriate research protocol that includes objective methods of voice evaluation is an important element of monitoring the return of vocal efficiency. Voice efficiency is important for the patient particularly due to psychological and social reasons. Aim The aim of the study was the assessment of short-term functional voice therapy (FVT) in patients with unilateral paralysis of the larynx with the usage of objective parameters describing the glottis and voice quality. Material and Method During the last 10 years 355 patients with laryngeal paralysis were hospitalized in the Audiology and Phoniatrics Clinic due to dysphonia. All patients undergone 5-day FVT. From 2015 we unified diagnostic protocol measuring parameters obtained from videostrobokymography (VSK), electroglottography (EGG), perceptual and acoustic voice analysis before and after 5 day hospitalization. Results After FVT patients improved voice quality and glottal compensation. The majority of patients achieved a statistically significant improvement in the VSK, EGG, MDVP and perceptual analysis. Group of patients with unsatisfactory voice improvement after therapy required a prolonged rehabilitation or has been qualified for laryngeal microsurgery. Potential factors that could have cause insufficient effects of FVT were analysed. Conclusions The complexity of voice rehabilitation is crucial for the success of therapy. Interdisciplinary therapeutic team plays a significant role during voice rehabilitation in patients with vocal fold paralysis.

Phonation type in vowels of heritage and native Gujarati speakers

Gujarati, an Indo-Aryan language, contrasts phonation type in vowels: [baɾ] ‘twelve’ and [baɾ] ‘outside’ (Pandit, 1957) and the current study looked at Gujarati vowels using acoustic and electroglottographic (EGG) analyses. The participants were native and heritage Gujarati speakers. Heritage speakers were born in Canada or arrived in Canada before seven years of age and learned Gujarati as their first language. Due to limited access to their first language, such as listening more than speaking the language and using Gujarati exclusively at home, it was expected that there might not be a significant difference between the heritage speakers’ breathy and modal vowel productions. This study determined if the acoustic and EGG parameters that differentiate breathy from modal vowels were the same or different for both speaker groups. Some of the parameters used to distinguish phonation type were H1-H2, H1-A1 ('A1' refers to amplitude of the first formant), harmonic-to-noise ratio, and contact quotient. Measure...

Objective measurement of mucosal wave parameters in diagnosing benign lesions of the vocal folds

Introduction: The diagnostic procedure of phonation is dominated by subjective assessment tools. It seems reasonable to seek methods of quantitative glottal cycle assessment.Objective: The aim of our study was the analysis of open quotients (OQ) of the glottis.Methods: One hundred and twenty-four people were included in the study. Methodology was based on tools available in everyday phoniatrics practice – laryngovideostroboscopy (LVS) and electroglottography (EGG). There were statistically significant differences between control and studied group. Vocal fold polyps, nodules and edema influence glottal function in a different manner, what can be illustrated by objective glottal function parameters. Establishing Videostroboscopic Open Quotient values from three parts of glottis and Electroglottographic Quasi Open Quotient (QOQ) value, can help in dividing patients with benign lesions of vocal folds according to the type of disease.Results and conclusions: Measurement of the open quotient from three parts of the glottis helps to differentially diagnose and localize glottal vocal fold lesions. Videostroboscopic Open Quotient and Electroglottographic QOQ values can be used to quantify the glottal cycle. Videostroboscopic Open Quotient, Electroglottographic QOQ and their ratio varies depending on the type of organic dysphonia.

Non-invasive documentation of primate voice production using electroglottography

Electroglottography (EGG) is a low-cost, non-invasive method for documenting laryngeal sound production during vocalization. The EGG signal represents relative vocal-fold contact area and thus delivers physiological evidence of vocal-fold vibration. While the method has received much attention in human voice research over the last five decades, it has seen very little application in other mammals. Here, we give a concise overview of mammalian vocal production principles. We explain how mammalian voice production physiology and the dynamics of vocal-fold vibration can be documented qualitatively and quantitatively with EGG, and we summarize and discuss key issues from research with humans. Finally, we review the limited number of studies applying EGG to non-human mammals, both in vivo and in vitro. The potential of EGG for non-invasive assessment of non-human primate vocalization is demonstrated with novel in vivo data of Cebus albifrons and Ateles chamek vocalization. These examples illustrate the great potential of EGG as a new minimally invasive tool in primate research, which can provide important insight into the ‘black box’ that is vocal production. A better understanding of vocal-fold vibration across a range of taxa can provide us with a deeper understanding of several important elements of speech evolution, such as the universality of vocal production mechanisms, the independence of source and filter, the evolution of vocal control, and the relevance of non-linear phenomena.

Japanese macaque phonatory physiology.

Although the call repertoire and its communicative function are relatively well explored in Japanese macaques (Macaca fuscata), little empirical data are available on the physics and the physiology of this species' vocal production mechanism. Here, a 6 year old female Japanese macaque was trained to phonate under an operant conditioning paradigm. The resulting 'coo' calls and spontaneously uttered 'growl' and 'chirp' calls were recorded with sound pressure level (SPL) calibrated microphones and electroglottography (EGG), a non-invasive method for assessing the dynamics of phonation. A total of 448 calls were recorded, complemented by ex vivo recordings on an excised Japanese macaque larynx. In this novel multidimensional investigative paradigm, in vivo and ex vivo data were matched via comparable EGG waveforms. Subsequent analysis suggests that the vocal range (range of fundamental frequency and SPL) of the macaque was comparable to that of a 7-10 year old human, with the exception of low intensity chirps, the production of which may be facilitated by the species' vocal membranes. In coo calls, redundant control of fundamental frequency in relation to SPL was also comparable to that in humans. EGG data revealed that growls, coos and chirps were produced by distinct laryngeal vibratory mechanisms. EGG further suggested changes in the degree of vocal fold adduction in vivo, resulting in spectral variation within the emitted coo calls, ranging from 'breathy' (including aerodynamic noise components) to 'non-breathy'. This is again analogous to humans, corroborating the notion that phonation in humans and non-human primates is based on universal physical and physiological principles.

Quantifying syringeal dynamics in vitro using electroglottography.

The complex and elaborate vocalizations uttered by many of the 10,000 extant bird species are considered a major driver in their evolutionary success, warranting study of the underlying mechanisms of vocal production. Additionally, birdsong has developed into a highly productive model system for vocal imitation learning and motor control, where, in contrast to humans, we have experimental access to the entire neuromechanical control loop. In human voice production, complex laryngeal geometry, vocal fold tissue properties, airflow and laryngeal musculature all interact to ultimately control vocal fold kinematics. Quantifying vocal fold kinematics is thus critical to understanding neuromechanical control of voiced sound production, but in vivo imaging of vocal fold kinematics in birds is experimentally challenging. Here, we adapted and tested electroglottography (EGG) as a novel tool for examining vocal fold kinematics in the avian vocal organ, the syrinx. We furthermore imaged and quantified syringeal kinematics in the pigeon (Columba livia) syrinx with unprecedented detail. Our results show that EGG signals predict (1) the relative amount of contact between the avian equivalent of vocal folds and (2) essential parameters describing vibratory kinematics, such as fundamental frequency, and timing of syringeal opening and closing events. As such, EGG provides novel opportunities for measuring syringeal vibratory kinematic parameters in vivo Furthermore, the opportunity for imaging syringeal vibratory kinematics from multiple planar views (horizontal and coronal) simultaneously promotes birds as an excellent model system for studying kinematics and control of voiced sound production in general, including in humans and other mammals.

Periodicity, spectral and electroglottographic analyses of pressed voice in expressive speech

Pressed voice is a type of voice quality produced by pressing/straining the vocal folds, which often appears in Japanese conversational speech when expressing paralinguistic information related to emotional or attitudinal behaviors of the speaker. With the aim of clarifying the acoustic and physiological features involved in pressed voice production, we conducted periodicity, spectral and electroglottographic (EGG) analyses on pressed voice segments extracted from spontaneous dialogue speech of several speakers. Periodicity analysis first indicated that pressed voice is usually accompanied by creaky or harsh voices, having irregularities in periodicity, but can also be accompanied by periodic voices with fundamental frequencies in the range of modal phonation. Spectral analysis indicated power is usually reduced in low frequency components of pressed segments. A spectral measure H1'-A1' was then proposed for characterizing pressed voice segments which commonly has few or no harmonicity. H1'-A1' was shown to be effective for identifying most pressed segments, but fails when nasalization occurs. Vocal fold vibratory pattern analysis from the EGG signals revealed that most pressed voice segments (including nasalized vowels) are characterized by glottal pulses with closed intervals longer than open intervals on average, regardless of periodicity.

Analysis of the Auditory Feedback and Phonation in Normal Voices.

The aim of this study was to investigate the auditory feedback mechanisms and voice quality during phonation in response to a spontaneous pitch change in the auditory feedback. Does the pitch shift reflex (PSR) change voice pitch and voice quality? Quantitative and qualitative voice characteristics were analyzed during the PSR. Twenty-eight healthy subjects underwent transnasal high-speed video endoscopy (HSV) at 8000 fps during sustained phonation [a]. While phonating, the subjects heard their sound pitched up for 700 cents (interval of a fifth), lasting 300 milliseconds in their auditory feedback. The electroencephalography (EEG), acoustic voice signal, electroglottography (EGG), and high-speed-videoendoscopy (HSV) were analyzed to compare feedback mechanisms for the pitched and unpitched condition of the phonation paradigm statistically. Furthermore, quantitative and qualitative voice characteristics were analyzed. The PSR was successfully detected within all signals of the experimental tools (EEG, EGG, acoustic voice signal, HSV). A significant increase of the perturbation measures and an increase of the values of the acoustic parameters during the PSR were observed, especially for the audio signal. The auditory feedback mechanism seems not only to control for voice pitch but also for voice quality aspects.

Modal and non-modal voice quality classification using acoustic and electroglottographic features.

The goal of this study was to investigate the performance of different feature types for voice quality classification using multiple classifiers. The study compared the COVAREP feature set; which included glottal source features, frequency warped cepstrum and harmonic model features; against the mel-frequency cepstral coefficients (MFCCs) computed from the acoustic voice signal, acoustic-based glottal inverse filtered (GIF) waveform, and electroglottographic (EGG) waveform. Our hypothesis was that MFCCs can capture the perceived voice quality from either of these three voice signals. Experiments were carried out on recordings from 28 participants with normal vocal status who were prompted to sustain vowels with modal and non-modal voice qualities. Recordings were rated by an expert listener using the Consensus Auditory-Perceptual Evaluation of Voice (CAPE-V), and the ratings were transformed into a dichotomous label (presence or absence) for the prompted voice qualities of modal voice, breathiness, strain, and roughness. The classification was done using support vector machines, random forests, deep neural networks and Gaussian mixture model classifiers, which were built as speaker independent using a leave-one-speaker-out strategy. The best classification accuracy of 79.97% was achieved for the full COVAREP set. The harmonic model features were the best performing subset, with 78.47% accuracy, and the static+dynamic MFCCs scored at 74.52%. A closer analysis showed that MFCC and dynamic MFCC features were able to classify modal, breathy, and strained voice quality dimensions from the acoustic and GIF waveforms. Reduced classification performance was exhibited by the EGG waveform.

Using electrolaryngography and electroglottography to assess the singing voice: A systematic review.

Electrolaryngography (Lx) and electroglottography (EGG) are non-invasive methods used to assess human vocal fold vibration and investigate speech and singing. This paper provides a systematic review of evidence-based studies using Lx/EGG in the analysis of the singing voice, identifying and critically appraising the thematic content and the research methodologies of the relevant investigations. Lx/EGG represents a powerful tool for the analysis of the singing voice in medical settings, and in support of research and teaching. Current research in this area is paving the way towards a better comprehension of singing performance.

On simultaneous electromagnetic articulography and electroglottography data acquisition

Simultaneous measurements of speech articulator movement and laryngeal activity are desirable for obtaining a picture of the coarticulatory behavior between oral articulators and laryngeal vocal fold behavior. However, since electroglottography (EGG) use the application of a weak current across the larynx, which is in close proximity to the oral vocal tract, there is a possibility that its use may interfere with the sensor voltage fluctuation measurements used in electromagnetic articulography (EMA). In order to investigate any hypothetical interference effect, data was collected using Northern Digital Instruments’ Wave articulograph with Glottal Enterprises’s EG2-PCX electroglottograph. Datasets were collected from one male and one female speaker—both with simultaneous EMA and EGG and, for comparison, with EMA alone. Means and standard deviations of inter-sensor distances for static (i.e., reference) and moving (e.g., tongue tip, lip, and jaw) EMA sensor trajectories were compared across the two collection conditions for possible interference effects. Preliminary results find no discernable differences in inter-sensor distances for either static or moving EMA sensors between the with- and without-EGG conditions. If this finding is maintained for additional speakers, NDI EMA data and GE EGG signals may be collected simultaneously without adverse effects on the measurement. [Work supported by NIH.]

Voice quality variation over the course of the English utterance

The presence of atypical voice quality (e.g. breathy and creaky voice) can be used to diagnose voice disorders, but it is also clear that healthy English speakers’ voices vary as a function of phrasing. For example, ends of declarative utterances tend to be produced with creakier voice quality. Yet for speakers who have no diagnosed voice disorder, it is still unclear what factors affect voice variation over an utterance, and how consistent these variations are across speakers. This in turn limits diagnostic utility of perceived non-modal voice. Therefore, the goal of this project is to determine how the voice varies over the course of English utterances. We recorded electroglottographic (EGG) and audio waveforms of 20 male and female speakers of Californian English reading sentences of various lengths that were designed to avoid non-modal voice associated with certain segments. The EGG waveforms were analyzed for contact quotient and f0 at the beginning, middle, and end of the utterance. Discussion will focus on how voice quality differs by position in utterance, and the extent to which it is predictable from f0. We also discuss whether voice quality varies as a function of gender, utterance length, and speakers’ average voice quality.

Significance of Differenced EGG Signal as a Spectrum in Phase Difference Computation for the Estimation of Glottal Closure Instants

Estimation of glottal closure instants (GCIs) from an electroglottograph (EGG) signal can aid in clinical applications involving the diagnosis and treatment of speech pathologies and can also serve as a ground truth to assess algorithms that estimate GCIs from speech signals. In this regard, the current work proposes a phase-difference-based approach that considers the symmetrized, differenced EGG (DEGG) signal to be the Fourier transform of an arbitrary even-signal, to estimate GCIs from EGG signals. The DEGG signal possesses sharp negative valleys at the GCIs and since the symmetrized DEGG is assumed to be a spectrum, these valleys correspond to zeros that lie outside the unit circle. The angular locations of these zeros, and in turn the locations of GCIs, can be derived from the phase-difference spectrum, since it possesses a value of around $$2\pi $$2? at these locations, the derivation of which is elaborated in the paper. The proposed algorithm is compared with the existing time of excitation generator, the high quality time of excitation algorithm, and the singularity in EGG by multiscale analysis algorithm, in terms of the identification, miss, and false alarm rates, and the identification accuracy, on normal and pathological EGG. The proposed algorithm is observed to outperform the rest with an identification rate of 98.28% in normal EGG and 96.90% in pathological EGG.

Significance of incorporating excitation source parameters for improved emotion recognition from speech and electroglottographic signals

The work presented in this paper explores the effectiveness of incorporating the excitation source parameters such as strength of excitation and instantaneous fundamental frequency ( $$F_0$$ ) for emotion recognition task from speech and electroglottographic (EGG) signals. The strength of excitation (SoE) is an important parameter indicating the pressure with which glottis closes at the glottal closure instants (GCIs). The SoE is computed by the popular zero frequency filtering (ZFF) method which accurately estimates the glottal signal characteristics by attenuating or removing the high frequency vocaltract interactions in speech. The arbitrary impulse sequence, obtained from the estimated GCIs, is used to derive the instantaneous $$F_0$$ . The SoE and the instantaneous $$F_0$$ parameters are combined with the conventional mel frequency cepstral coefficients (MFCC) to improve the recognition rates of distinct emotions (Anger, Happy and Sad) using Gaussian mixture models as classifier. The performances of the proposed combination of SoE and instantaneous $$F_0$$ and their dynamic features with MFCC coefficients are compared with the emotion utterances (4 emotions and neutral) from classical German full blown emotion speech database (EmoDb) having simultaneous speech and EGG signals and Surrey Audio Visual Expressed Emotion database (3 emotions and neutral) for both speaker dependent and speaker independent emotion recognition scenarios. To reinforce the effectiveness of the proposed features and for better statistical consistency of the emotion analysis, a fairly large emotion speech database of 220 utterances per emotion in Tamil language with simultaneous EGG recordings, is used in addition to EmoDb. The effectiveness of SoE and instantaneous $$F_0$$ in characterizing different emotions is also confirmed by the improved emotion recognition performance in Tamil speech-EGG emotion database.

Intelligent acoustic data fusion technique for information security analysis

Tone is an essential component of word formation in all tonal languages, and it plays an important role in the transmission of information in speech communication. Therefore, tones characteristics study can be applied into security analysis of acoustic signal by the means of language identification, etc. In speech processing, fundamental frequency (F0) is often viewed as representing tones by researchers of speech synthesis. However, regular F0 values may lead to low naturalness in synthesized speech. Moreover, F0 and tone are not equivalent linguistically; F0 is just a representation of a tone. Therefore, the Electroglottography (EGG) signal is collected for deeper tones characteristics study. In this paper, focusing on the Northern Kam language, which has nine tonal contours and five level tone types, we first collected EGG and speech signals from six natural male speakers of the Northern Kam language, and then achieved the clustering distributions of the tone curves. After summarizing the main characteristics of tones of Northern Kam, we analyzed the relationship between EGG and speech signal parameters, and laid the foundation for further security analysis of acoustic signal.

Smart healthcare monitoring: a voice pathology detection paradigm for smart cities

With the increasing demand for automated, remote, intelligent, and real-time healthcare services in smart cities, smart healthcare monitoring is necessary to provide improved and complete care to residents. In this monitoring, health-related media or signals collected from smart-devices/objects are transmitted and processed to cater to the need for quality care. However, it is challenging to create a framework or method to handle media-related healthcare data analytics or signals (e.g., voice/audio, video, or electroglottographic (EGG) signals) to meet the complex on-demand healthcare needs for successful smart city management. To this end, this paper proposes a cloud-oriented smart healthcare monitoring framework that interacts with surrounding smart devices, environments, and smart city stakeholders for affordable and accessible healthcare. As a smart city healthcare monitoring case study, a voice pathology detection (VPD) method is proposed. In the proposed method, two types of input, a voice signal and an EGG signal, are used. The input devices are connected to the Internet and the captured signals are transmitted to the cloud. The signals are then processed and classified as either normal or pathologic with a confidence score. These results are passed to registered doctors that make the final decision and take appropriate action. To process the signals, local features are extracted from the first-order derivative of the voice signal, and shape and cepstral features are extracted from the EGG signal. For classification, a Gaussian mixture model-based approach is used. Experimental results show that the proposed method can achieve VPD that is more than 93% accurate.

Electrically conductive synthetic vocal fold replicas for voice production research.

A method of fabricating electrically conductive synthetic vocal fold replicas and monitoring their vibration via resistance measurement is presented. Normally non-conductive silicone replicas were coated with conductive graphite and subjected to long-term vibration tests. Synchronized resistance and imaging data using hemilarynx and full larynx configurations showed an inverse correlation between replica contact area and resistance during vibration, similar to clinical electroglottography (EGG) used to estimate vocal fold contact area. This method has potential for long-term replica vibration monitoring and studying basic physical relationships between resistance and contact area in vocal folds and vocal fold replicas.

Measurement of the Maximum Frequency of Electroglottographic Fluctuations in the Expiration Phase of Volitional Cough as a Functional Test for Cough Efficiency

The hypotheses of the present study were that the maximum frequency of fluctuation of electroglottographic (EGG) signals in the expiration phase of volitional cough (VC) reflects the cough efficiency and that this EGG parameter is affected by impaired laryngeal closure, expiratory effort strength, and gender. For 20 normal healthy adults and 20 patients diagnosed with unilateral vocal fold paralysis (UVFP), each participant was fitted with EGG electrodes on the neck, had a transnasal laryngo-fiberscope inserted, and was asked to perform weak/strong VC tasks while EGG signals and a high-speed digital image of the larynx were recorded. The maximum frequency was calculated in the EGG fluctuation region coinciding with vigorous vocal fold vibration in the laryngeal HSDIs. In addition, each participant underwent spirometry for measurement of three aerodynamic parameters, including peak expiratory air flow (PEAF), during weak/strong VC tasks. Significant differences were found for both maximum EGG frequency and PEAF between the healthy and UVFP groups and between the weak and strong VC tasks. Among the three cough aerodynamic parameters, PEAF showed the highest positive correlation with the maximum EGG frequency. The correlation coefficients between the maximum EGG frequency and PEAF recorded simultaneously were 0.574 for the whole group, and 0.782/0.717/0.823/0.688 for the male/female/male-healthy/male-UVFP subgroups, respectively. Consequently, the maximum EGG frequency measured in the expiration phase of VC was shown to reflect the velocity of expiratory airflow to some extent and was suggested to be affected by vocal fold physical properties, glottal closure condition, and the expiratory function.

Acoustic Analysis of Voice and Electroglottography in Patients With Laryngopharyngeal Reflux

Laryngopharyngeal reflux (LPR) refers to the flow of gastric acid content into the laryngopharynx. It has been reported that 10% of the patients consulting an otolaryngologist present with this condition. Signs of LPR can be identified during flexible or rigid laryngoscopy. The Voice Handicap Index (VHI) is a reliable tool for detecting the impact of voice disorders, and acoustic assessment of voice including acoustic analysis of voice (AAV) and electroglottography (EGG) provide objective data of voice production and voice disorders. This study aimed to describe changes in AAV, EGG, and VHI in patients who present with LPR compared with a matched control group of healthy subjects. Seventeen patients with LPR were studied. A group of healthy subjects matched by age and gender without any history of voice disorder, LPR, or gastroesophageal reflux disease was assembled. Both groups of patients were studied by VHI, flexible laryngoscopy, AAV, and EGG. All patients with LPR demonstrated abnormal VHI values. Shimmer, jitter, open quotient, and irregularity were significantly increased in the patients with LPR. Nonsignificant correlations were found between VHI scores and abnormal acoustic parameters in patients with LPR. Although abnormal acoustic parameters of patients with LPR were not predictive of the overall VHI score, the abnormal acoustic parameters of patients with LPR suggest a decrease in adequate laryngeal control during phonation.