Skip to content
Microsystems, Electronics and Acoustics
ISSN 2523-4447 · e‑ISSN 2523-4455 Open Access · CC BY-SA 4.0
Vol. 27 · Issue 1 · 2022 Apr 29, 2022 Acoustical devices and systems

Computer Modeling of Human Voice System Diagnostic Algorithms

ОД
Олександр Ігорович Денисенко Corresponding Національний технічний університет України "Київський політехнічний інститут імені Ігоря Сікорського",Igor Sikorsky Kyiv Polytechnic Institute Ukraine
Pages254174-1-254174-6 PublishedApr 29, 2022
VOL 27 · ISS 1 · 2022 View issue

Abstract

Every year, people are faced with an increasing number of diseases that require timely detection and diagnosis without causing discomfort to the patient. Thus arose the systems of objective and subjective assessment of the quality of hearing, as well as the first systems of analysis of the state of the vocal tract. The problem of voice pathology is inherent in a fairly large risk group, which includes teachers, artists, call center operators. The specifics of the development of such systems is that the hardware and software complex developed by the engineer should be convenient for use by a doctor and relevant in terms of existing solutions to identify certain acoustic parameters of the voice. The study of the voice spectrum can be the main diagnostic test in the diagnosis of persistent voice disorders and, along with the study of the voice field and vibrometry, allows you to determine the form of voice disorders in professionals. Acoustic tests for the presence of high and low singing forms in the singing voice can be highly important in determining the singer's performance and professional prognosis, can serve as a criterion in the diagnosis of persistent voice disorders, and their use in early stages of occupational laryngeal diseases will help prevent preventive measures. MATLAB software comes with a large number of tools, which facilitates the implementation of many engineering, mathematical, computational issues of development and research of various processes related to any field of research. Based on these tools, there are a large number of basic functions of digital signal analysis, including audio signals. FFT - fast Fourier transform algorithms are chosen as a basis, which with a certain modification are divided into parametric and nonparametric. In this case, the nonparametric Welch method and the parametric Berg method are chosen. The user is given access to choose between the parameters required for their operation. For the first it is the dimension of the weight function, for the second it is the order of the autoregressive model. All this gives opportunity to analyze the spectrum of vowel phonemes. The AppDesigner package provides great opportunities for creating interfaces in software development. By manipulating the functions of Callback, you can bring the program to the finest settings, which at first may seem invisible, but generally create comfort when working. It is important to build a certain algorithm of action of each component. It often happens that it is necessary to take into account such details for which a certain component in itself is not responsible. For example, this could be changing the signatures of other components. To simplify code writing, it is important to create m-functions. However, this must be taken into account when editing them after entering them in the main script. Using the above toolbox, a software interface was developed, which is divided into two working areas: time and spectral parts. In addition, the interface is filled with controls for input data and spectrum analyzer parameters, as well as spectrum analysis tools.

Keywords

References

  1. Shydlovsʹka T. A. Funktsionalʹni porushennya holosu [Functional disorders of the voice], 2011
  2. Pokrovs'kiy N. B. Raschet i izmereniye razborchivosti rechi [Calculation and measurement of speech intelligibility]. Moskva, Svyaz'izdat, 1962
  3. Sapozhkov M. A. Rechevoy signal v kibernetike i svyazi [Speech signal in cybernetics and communication]. Moskva, Svyaz'izdat, 1963.
  4. O. G. Pavlikhin, A. P. Meshcherkin "Diagnosticheskoye znacheniye komp'yuternogo spektral'nogo analiza golosa u vokalistov [Diagnostic value of computer spectral analysis of the voice of vocalists]" Sbornik nauchnykh trudov. Pervyy mezhdunarodnyy mezhdistsiplinarnyy kongress "Golos", 2007, pp. 86–90.
  5. MathWorks - Makers of MATLAB and Simulink - MATLAB & Simulink URL: https://www.mathworks.com/
  6. Sergiyenko A. B. Tsifrovaya obrabotka signalov [Digital signal processing]. 2011. 768 p
  7. Didkovsʹkyy V. S., Didkovsʹka M. V., Prodeus A. M. "Komp'yuterna obrobka akustychnykh syhnaliv [Computer processing of acoustic signals]". Navchalʹnyy posibnyk. Kyiv, «Imeks-LTD», 2010. 420 p.
  8. Denysenko, O. I. Spektralʹnyy analiz vokalʹnykh zvukiv [Spectral analysis of vocal sounds] : dyplomna robota bakalavra : 171 Elektronika. Kyyiv, 2020. 75 s. URI: : https://ela.kpi.ua/handle/123456789/34773
  9. Pediatric otolaryngology. Edited by Charles D. Bluestone. 4th ed., 2003. 2214 p.
  10. Poorjam A., Jensen J., Christensen M. Dominant Distortion Classification for Pre-Processing of Vowels in Remote Biomedical Voice Analysis. URL: https://www.researchgate.net/publication/317064232
§ 06 — Related

Similar articles in this journal

Related peer-reviewed studies published in this journal.
View all issues

Experimental Study of the Frequency Characteristics of MEMS Microphones for Railway Noise Monitoring

Vitalii R. Prus, PhD, Assoc. Prof. Oleksii Viktorovych Bogdanov

Abstract–The paper presents the results of an experimental study of the acoustic characteristics of modular MEMS microphones INMP441 and SPH0645, aimed at their…

#acoustic monitoring #MEMS microphone #amplitude-frequency response #directivity pattern
p. 359669.1-359669.6
10.20535/2523-4455.mea.359669

Acoustic Localization of Aerial Objects and Practical Evaluation of its Accuracy

Dr.Sc.(Eng.), Prof. Serhii Anatoliiovych Naida, Dr.Sc.(Eng.), Assoc. Prof. Oleksandr Ivanovych Drozdenko, PhD, Assoc. Prof. Pavlo Vasyliovych Popovych, канд. техн. наук, доц. Катерина Сергіївна Дрозденко, PhD Oleksandr Ihorovych Nyzhnyk, PhD Yaroslav Ivanovych Starovoit

The active use of aerial objects creates a need for passive detection methods. This paper presents an experimental study of an automated acoustic hardware and software…

#acoustic signal processing #sound source localization #microphone arrays #beamforming
p. 359830.1-359830.7
10.20535/2523-4455.mea.359830

Similar Articles

1-10 of 75

You may also start an advanced similarity search for this article.