PROSPECTIVE ARABIC LANGUAGE DATA BASE FOR IDENTIFICATION AND RECOGNITION OF VOICE DISORDER

Authors

  • S. A. Syed Department of Biomedical Engineering and Electrical Engineering Ziauddin University Faculty of Engineering

DOI:

https://doi.org/10.57041/pjs.v73i1.655

Keywords:

Acoustic analysis, Clinical voice pathology, Voice disorder, AVPD, machine learning technique

Abstract

Speech is the underlying strong characteristic and voice is the vibration that the air creates as it's pushed out of the lungs and going into the vocal cords. Vocal cords are two folds of tissue within the larynx, sometimes called a speech box, the sound of these strings is what gives rise to speech.Anything that interferes with vocal cord movement or contact can cause a voice disorder. Speech production may often be compromised as social stressors contribute to chronic aphonia or dysphonia.Machine learning algorithm and non-invasive systems may play a major role in the early detection and in tracking and even development of efficient pathological speech diagnosis, based on a computerized acoustic analysis. A strong voice impairment dataset will help in recognition and classification ofincreasing number of voice disorders in and outside the Arab area. The database protocols for AVPD (Arabic voice pathology database) has been developed in a way to prevent previous data base deficiencies in widely used databases like MEEI (Massachusetts eye and ear infirmary) and SVD (Saarbrücken voice database).

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Published

2022-12-18

How to Cite

S. A. Syed. (2022). PROSPECTIVE ARABIC LANGUAGE DATA BASE FOR IDENTIFICATION AND RECOGNITION OF VOICE DISORDER. Pakistan Journal of Science, 73(1). https://doi.org/10.57041/pjs.v73i1.655