scholarly journals Invariant Measures Based on the U-Correlation Integral: An Application to the Study of Human Voice

Complexity ◽  
2018 ◽  
Vol 2018 ◽  
pp. 1-9
Author(s):  
Juan F. Restrepo ◽  
Gastón Schlotthauer
Keyword(s):  
Noise Level ◽  
Correlation Dimension ◽  
Stochastic Perturbation ◽  
Voice Production ◽  
Correlation Integral ◽  
Human Voice ◽  
Automated Algorithm ◽  
Correlation Entropy ◽  
The Voice

Nonlinear measures such as the correlation dimension, the correlation entropy, and the noise level were used in this article to characterize normal and pathological voices. These invariants were estimated through an automated algorithm based on the recently proposed U-correlation integral. Our results show that the voice dynamics have a low dimension. The value of correlation dimension is greater for pathological voices than for normal ones. Furthermore, its value also increases along with the type of the voice. The low correlation entropy values obtained for normal and pathological type 1 and type 2 voices suggest that their dynamics are nearly periodic. Regarding the noise level, in the context of voice signals, it can be interpreted as the power of an additive stochastic perturbation intrinsic to the voice production system. Our estimations suggest that the noise level is greater for pathological voices than for normal ones. Moreover, it increases along with the type of voice, being the highest for type 4 voices. From these results, we can conclude that the voice production dynamical system is more complex in the presence of a pathology. In addition, the presence of the inherent stochastic perturbation strengthens along with the voice type. Finally, based on our results, we propose that the noise level can be used to quantitatively differentiate between type 3 and type 4 voices.

The professional voice

2010 ◽  
Vol 125 (2) ◽  
pp. 111-116 ◽  
Author(s):  
M S Benninger
Keyword(s):  
Voice Disorders ◽  
Musical Instrument ◽  
Care Team ◽  
Human Communication ◽  
Voice Production ◽  
Anatomy And Physiology ◽  
Human Voice ◽  
The Voice ◽  
Professional Voice ◽  
And Training

AbstractThe human voice is not only the key to human communication but also serves as the primary musical instrument. Many professions rely on the voice, but the most noticeable and visible are singers. Care of the performing voice requires a thorough understanding of the interaction between the anatomy and physiology of voice production, along with an awareness of the interrelationships between vocalisation, acoustic science and non-vocal components of performance. This review gives an overview of the care and prevention of professional voice disorders by describing the unique and integrated anatomy and physiology of singing, the roles of development and training, and the importance of the voice care team.

scholarly journals Evaluating the Voice Type Component Distributions of Excised Larynx Phonations at Three Subglottal Pressures

2021 ◽  
pp. 1-10
Author(s):  
Boquan Liu ◽  
Hayley Raj ◽  
Logan Klein ◽  
Jack J. Jiang
Keyword(s):  
Chaotic Signal ◽  
Periodic Signal ◽  
Intrinsic Dimension ◽  
Human Voice ◽  
Dynamic Methods ◽  
Phonation Threshold Pressure ◽  
Noisy Signals ◽  
Signal Processing Methods ◽  
The Voice

Purpose The excised canine larynx provides an advantageous experimental framework in the study of voice physiology. In recent years, signal processing methods have been applied to analyze phonations in excised canine larynx experiments. However, phonations have a highly complex and nonstationary nature corresponding to different proportions of regular and chaotic signal elements. Current nonlinear dynamic methods that are used to assess the degree of irregularity in the voice fail to recognize the distribution of voice type components (VTCs). Method Based on measures of intrinsic dimension, this article presents a method to analyze the VTC distribution of phonations in excised canine larynx experiments. Thirty-nine phonation samples from 13 excised canine larynges at three different subglottal pressures were analyzed. Results Phonation produced with subglottal pressures above phonation instability pressure (PIP) and below phonation threshold pressure (PTP) resulted in high proportions of Voice Types 3 and 4, characterized by chaotic and noisy signals. Phonation produced with pressure between PTP and PIP contained mostly Type 1 voice, characterized by a regular and nearly periodic signal. Mean proportions of all VTCs varied significantly in comparisons of phonations produced with Sub-PTP and PTP as well as in comparisons of phonations produced with PTP and PIP. Conclusions Across all VTCs, the VTC profiles of normal and abnormal phonation differ significantly. Normal phonation is strongly associated with VTC 1 (Voice Type Component 1), whereas abnormal phonation exhibits increased VTC 4 (Voice Type Component 4). The study further demonstrates the ability of intrinsic dimension to successfully detect multiple voice types in an acoustic signal and highlights the need for expanded use of intrinsic dimension in human voice. Supplemental Material https://doi.org/10.23641/asha.14417585

In Support of the Exceptional Voice

2019 ◽  
Vol 4 (6) ◽  
pp. 1306-1310
Author(s):  
JoAnna Sloggy ◽  
Joseph Stemple ◽  
Graham Rowles ◽  
Richard Andreatta
Keyword(s):  
Voice Disorder ◽  
Adequate Description ◽  
Vocal Rehabilitation ◽  
Voice Production ◽  
Human Voice ◽  
Current Definition ◽  
Vocal Quality ◽  
Definition Of ◽  
High Level ◽  
The Voice

Purpose The human voice is an exceptionally versatile instrument that is capable of complex communicative and emotive behaviors. Typically, these behaviors are sufficient for daily communication activities; however, elite vocal athletes have higher vocal demands and arguably enhanced vocal capabilities. The current definition of a voice disorder is a change in quality, pitch, and loudness of the voice that draws attention to the speaker. In this article, we suggest that this definition does not provide an adequate description of voice problems of elite vocal athletes. Conclusion As a result, the current clinical system of evaluation and intervention may fail to meet the needs of the exceptional voice when even a subtle decline in vocal quality may affect performance. Under the current definition of a voice disorder, these vocal changes may not qualify for vocal rehabilitation supported by 3rd-party payers. To address this issue, we offer a definition of the exceptional voice, propose expansion of the current voice production continuum to include high-level vocal performers, and provide recommendations for the rehabilitation and habilitation of the exceptional voice.

Correction of the Correlation Dimension for Noisy Time Series

1997 ◽  
Vol 07 (06) ◽  
pp. 1283-1294 ◽  
Author(s):  
D. Kugiumtzis
Keyword(s):  
Time Series ◽  
Noise Level ◽  
Correlation Dimension ◽  
Epileptic Seizures ◽  
Chaotic Time Series ◽  
Simple Method ◽  
Correlation Integral ◽  
Free Data ◽  
Correction Scheme ◽  
Eeg Data

In the computation of the correlation dimension of chaotic time series corrupted with observational noise, the scaling region is often masked resulting in deteriorated estimates. Here a simple method is proposed to correct the corrupted correlation integral based on the statistical properties of the Euclidean norm used to compute the noisy point interdistances. When the noise level is known, the corrected slope from the noisy data is very close to the slope for the noise-free data. Thus if the scaling property of the noise-free attractor holds for distances around the noise amplitude then the correct dimension can be inferred. The problem of estimating the correct noise level is discussed and a simple approach is proposed. Simulations with synthetic noisy chaotic time series demonstrate the efficiency of the correction scheme. Furthermore, the correction scheme is used to enhance correlation dimension estimates for the Taylor–Couette chaotic data and for EEG data from epileptic seizures.

NOISE LEVEL ESTIMATION FOR A CHAOTIC TIME SERIES

2012 ◽  
Vol 22 (03) ◽  
pp. 1250052 ◽  
Author(s):  
PENGCHENG XU ◽  
W. K. LI ◽  
A. W. JAYAWARDENA
Keyword(s):  
Time Series ◽  
Noise Level ◽  
Correlation Dimension ◽  
Chaotic Time Series ◽  
Estimation Methods ◽  
Supremum Norm ◽  
Linear Estimation ◽  
Governing Equations ◽  
Correlation Integral ◽  
Noise Level Estimation

In this study, the correlation sum and the correlation integral for chaotic time series using the Supremum norm and the Euclidean norm are discussed. The correlation integrals are then used to develop governing equations for the correlation sum, noise level and correlation dimension in which the correlation dimension and the noise level are linearly dependent on each other. Some linear estimation methods for the noise level are then introduced by using these equations. The estimation methods are applied to four chaotic time series (two artificial and two real-world). By comparing the performances of the estimations of the noise level, the best estimating method is then suggested.

scholarly journals Impact of the Sub-Grid Scale Turbulence Model in Aeroacoustic Simulation of Human Voice

2021 ◽  
Vol 11 (4) ◽  
pp. 1970
Author(s):  
Martin Lasota ◽  
Petr Šidlof ◽  
Manfred Kaltenbacher ◽  
Stefan Schoder
Keyword(s):  
Sound Propagation ◽  
Vocal Tract ◽  
Vocal Folds ◽  
Equation Model ◽  
Voice Production ◽  
Human Voice ◽  
Large Eddy ◽  
Aeroacoustic Simulation ◽  
Scale Turbulence ◽  
The One

In an aeroacoustic simulation of human voice production, the effect of the sub-grid scale (SGS) model on the acoustic spectrum was investigated. In the first step, incompressible airflow in a 3D model of larynx with vocal folds undergoing prescribed two-degree-of-freedom oscillation was simulated by laminar and Large-Eddy Simulations (LES), using the One-Equation and Wall-Adaptive Local-Eddy (WALE) SGS models. Second, the aeroacoustic sources and the sound propagation in a domain composed of the larynx and vocal tract were computed by the Perturbed Convective Wave Equation (PCWE) for vowels [u:] and [i:]. The results show that the SGS model has a significant impact not only on the flow field, but also on the spectrum of the sound sampled 1 cm downstream of the lips. With the WALE model, which is known to handle the near-wall and high-shear regions more precisely, the simulations predict significantly higher peak volumetric flow rates of air than those of the One-Equation model, only slightly lower than the laminar simulation. The usage of the WALE SGS model also results in higher sound pressure levels of the higher harmonic frequencies.

DYNAMICAL ESTIMATION OF CALENDAR EFFECTS

2006 ◽  
Vol 06 (01) ◽  
pp. L7-L15
Author(s):  
ALEXANDROS LEONTITSIS
Keyword(s):  
Dynamical System ◽  
Time Series ◽  
Noise Level ◽  
Nonlinear Dynamical System ◽  
Main Tool ◽  
Experimental Results ◽  
Accurate Estimation ◽  
Nonlinear Dynamical ◽  
Correlation Integral ◽  
Calendar Effects

The paper introduces a method for estimation and reduction of calendar effects from time series, which their fluctuations are governed by a nonlinear dynamical system and additive normal noise. Calendar effects can be considered deviations of the distribution(s) of particular group(s) of observations that have a common characteristic related to the calendar. The concept of this method is the following: since the calendar effects are not related to the dynamics of the time series, the accurate estimation and reduction will result a time series with a smaller amount of noise level (i.e. more accurate dynamics). The main tool of this method is the correlation integral, due to its inherit capability of modeling both the dynamics and the additive normal noise. Experimental results are presented on the Nasdaq Cmp. index.

Text-to-Speech Software and Learning: Investigating the Relevancy of the Voice Effect

2018 ◽  
Vol 57 (6) ◽  
pp. 1534-1548 ◽  
Author(s):  
Scotty D. Craig ◽  
Noah L. Schroeder
Keyword(s):  
Learning Outcomes ◽  
Learning Environments ◽  
Multimedia Learning ◽  
Text To Speech ◽  
Multimedia Design ◽  
Cognitive Efficiency ◽  
Human Voice ◽  
Instructional Multimedia ◽  
Efficiency Measures ◽  
The Voice

Technology advances quickly in today’s society. This is particularly true in regard to instructional multimedia. One increasingly important aspect of instructional multimedia design is determining the type of voice that will provide the narration; however, research in the area is dated and limited in scope. Using a randomized pretest–posttest design, we examined the efficacy of learning from an instructional animation where narration was provided by an older text-to-speech engine, a modern text-to-speech engine, or a recorded human voice. In most respects, those who learned from the modern text-to-speech engine were not statistically different in regard to their perceptions, learning outcomes, or cognitive efficiency measures compared with those who learned from the recorded human voice. Our results imply that software technologies may have reached a point where they can credibly and effectively deliver the narration for multimedia learning environments.

scholarly journals Common Terminology and Acoustic Measures for Human Voice and Birdsong

2019 ◽  
Vol 62 (1) ◽  
pp. 60-69
Author(s):  
Areen Badwal ◽  
JoHanna Poertner ◽  
Robin A. Samlan ◽  
Julie E. Miller
Keyword(s):  
Acoustic Analysis ◽  
Voice Production ◽  
Acoustic Measures ◽  
Human Voice ◽  
Song Analysis ◽  
Core Set ◽  
Standard Terminology ◽  
Cepstral Peak Prominence ◽  
Two Measures ◽  
Similarities And Differences

Purpose The zebra finch is used as a model to study the neural circuitry of auditory-guided human vocal production. The terminology of birdsong production and acoustic analysis, however, differs from human voice production, making it difficult for voice researchers of either species to navigate the literature from the other. The purpose of this research note is to identify common terminology and measures to better compare information across species. Method Terminology used in the birdsong literature will be mapped onto terminology used in the human voice production literature. Measures typically used to quantify the percepts of pitch, loudness, and quality will be described. Measures common to the literature in both species will be made from the songs of 3 middle-age birds using Praat and Song Analysis Pro. Two measures, cepstral peak prominence (CPP) and Wiener entropy (WE), will be compared to determine if they provide similar information. Results Similarities and differences in terminology and acoustic analyses are presented. A core set of measures including frequency, frequency variability within a syllable, intensity, CPP, and WE are proposed for future studies. CPP and WE are related yet provide unique information about the syllable structure. Conclusions Using a core set of measures familiar to both human voice and birdsong researchers, along with both CPP and WE, will allow characterization of similarities and differences among birds. Standard terminology and measures will improve accessibility of the birdsong literature to human voice researchers and vice versa. Supplemental Material https://doi.org/10.23641/asha.7438964

scholarly journals Android Based Voice Activated Wheel Chair for Disabled

2020 ◽  
Vol 9 (3) ◽  
pp. 3508-3509
Keyword(s):  
Speech Recognition ◽  
Smart Phone ◽  
Dc Motor ◽  
Older Individuals ◽  
Recognition Model ◽  
Human Voice ◽  
Dc Motors ◽  
Wheel Chair ◽  
The Voice

The aim of the project is to develop a wheel chair which can be controlled by voice of the person. It is based on the speech recognition model. The project is focused on controlling the wheel chair by human voice. The system is intended to control a wheel seat by utilizing the voice of individual. The structure of this framework will be particularly valuable to the crippled individual and furthermore to the older individuals. It is a booming technology which interfaces human with machine. Smart phone device is the interface. This will allow the challenging people to move freely without the assistant of others. They will get a moral support to live independently .The hardware used are Arduino kit, Microcontroller, Wheelchair and DC motors. DC motor helps for the movement of wheel chair. Ultra Sonic Sensor senses the obstacles between wheelchair and its way.

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