Open AccessAn evaluation of deep learning approaches for detection of voice disorders.
Author(s) -
M Chinchu,
B. Kirubagari
Publication year - 2021
Publication title -
iop conference series. materials science and engineering
Language(s) - English
Resource type - Journals
eISSN - 1757-899X
pISSN - 1757-8981
DOI - 10.1088/1757-899x/1085/1/012017
Subject(s) - loudness , computer science , process (computing) , natural (archaeology) , quality (philosophy) , noise (video) , speech recognition , psychology , artificial intelligence , biology , philosophy , epistemology , image (mathematics) , computer vision , operating system , paleontology
The human voice manufacturing system is a complicated natural device capable of modulating pitch and loudness Human sound frequency particularly. The part in which the folded is the primary source underlying internal and/or external factors often destroys vocal folds justification. Some changes consequences are reflected in functioning emotional state soul. Therefore it essential to identify variations at an early stage gives the patient an endangerment overcome any impact modernize their quality of life will-less detection disorders using depth study methods plays an important role as has been proven to facilitate the process. Many researchers have explored technologies for streamlined that can help clinics diagnose noise paper we present the conducted research activities.