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Pathological infant cry analysis using wavelet packet transform and probabilistic neural network
(Elsevier Ltd., 2011-11)
A new approach has been presented based on the wavelet packet transform and probabilistic neural network (PNN) for the analysis of infant cry signals. Feature extraction and development of classification algorithms play ...
Automatic detection of prolongations and repetitions using LPCC
(Institute of Electrical and Elctronics Engineering (IEEE), 2009-12-14)
Stuttering is a speech disorder in which the normal flow of speech is disrupted by occurrences of dysfluencies, such as repetitions, interjection and so on. There are high proportion of repetitions and prolongations in ...
Classification of speech dysfluencies using LPC based parameterization techniques
(Springer Science+Business Media, LLC., 2011-01-20)
The goal of this paper is to discuss and compare three feature extraction methods: Linear Predictive Coefficients (LPC), Linear Prediction Cepstral Coefficients (LPCC) and Weighted Linear Prediction Cepstral Coefficients ...
Detection of vocal fold paralysis and edema using time-domain features and probabilistic neural network
(Inderscience Publisher, 2011)
This paper proposes a feature extraction method based on time-domain energy variation for the detection of vocal fold pathology. In this work, two different vocal fold problems (vocal fold paralysis and edema) are taken ...
Feature extraction based on mel-scaled wavelet packet transform for the diagnosis of voice disorders
(SpringerLink, 2008-06-25)
Feature extraction from the vocal signal plays very important role in the area of automatic detection of voice disorders. Many feature extraction algorithms have been developed in the last three decades based on acoustic ...
Automatic detection of voice disorders using self loop architecture in back propagation network
(Anna University, 2008-01-04)
Acoustic analysis is a non-invasive technique to detect the voice disorders and diagnose the vocal and voice disease. In the recent years, voice disease are increasing dramatically due to unhealthy social habits and voice ...
Application of feedforward neural network for the classification of pathological voices
(Universiti Teknologi MARA (UiTM), 2007-03-09)
This paper present the application of feed forward neural network for the classification of pathological voices based on the on the acoustic analysis and EGG features. Acoustic analysis is a non-invasive technique based ...
Diagnosis of voice disorders using band energy spectrum in wavelet domain
(Universiti Malaysia Perlis (UniMAP), 2008-03-08)
In the evolution of quality of speech, acoustic analyses of normal and pathological voices have become increasingly interesting to researchers in laryngology and speech pathologies. Vocal signal information plays an important ...
Diagnosis of voices disorders using MEL scaled WPT and functional link neural network
(Biomedical Fuzzy Systems Association (BMFSA), 2008-03-31)
Nowadays voice disorders are increasing dramatically due to the modern way of life. Most of
the voice disorders cause changes in the voice signal. Acoustic analysis on the speech signal could be a
useful tool for ...
Patients tremble analysis under different camera placement in critical care
(Science Academy, 2011-03)
This paper presents an integrated system for detecting facial changes of patient in a hospital in Intensive Care
Unit (ICU). In this research we have considered the facial changes most widely represented by eyes and mouth ...