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Speech emotion recognition using kNN classifier
(Universiti Malaysia Perlis (UniMAP), 2012-06-18)
There are many methods that are commonly used by researches in order to recognize speech of human emotion. In this paper, Surrey audio-visual expressed emotion (SAVEE) database are used for the analysis. The Mel-Frequency ...
Investigation of vision impairments using pattern reversal VEPs and extreme learning machine
(Universiti Malaysia Perlis (UniMAP), 2012-06-18)
Analysis of vision impairment using pattern reversal visually evoked potentials (VEP) is gaining interest from researchers. The VEPs are collected using non-invasive EEG electrodes from the scalp overlaying the occipital ...
Performance comparison of daubechies wavelet family in Infant cry classification
(IEEE Conference Publications, 2012)
Infant cry is a non-stationary, loud, high-pitched signal made by infants in response to certain situations. This acoustic signal can be used to identify physical or psychology status of infant. The aim of this work is to ...
Mathematical model attitude estimation using Kalman filter technique for low earth orbit satellite
(Universiti Malaysia Perlis (UniMAP), 2012-02-27)
In space, the attitude analysis of a satellite is constantly being computed within the system of the satellite. In this paper, the linear mathematical model of the satellite attitude control with gravity gradient moment, ...
Improved back propagation neural network for the diagnosis of pathological voices
(Association for Advancedment of Modelling and Simulation Techniques in Entreprises (A.M.S.E), 2008)
Most of vocal and voice diseases cause changes in the voice. ENT clinicians use acoustic voice analysis to characterize the pathological voices. Nowadays, voice diseases are increasing dramatically due to unhealthy social ...
Analysis of infant cry through weighted linear prediction cepstral coefficients and probabilistic neural network
(Springer Science+Business Media, LLC., 2012)
Acoustic analysis of infant cry signals has been proven to be an excellent tool in the
area of automatic detection of pathological status of an infant. This paper investigates
the application of parameter weighting for ...
Time-domain features and probabilistic neural network for the detection of vocal fold pathology
(Universiti Malaya, 2010)
Due to the nature of job, unhealthy social habits and voice abuse, people are subjected to the risk of voice problems. It is well known that most of vocal fold pathologies cause changes in the acoustic voice signal. ...
Identification of vocal fold pathology based on Mel Frequency Band Energy Coefficients and singular value decomposition
(Institute of Electrical and Elctronics Engineering (IEEE), 2009-11-18)
Many approaches have been developed to detect the vocal fold pathology. Among the approaches, analysis of speech has proved to be an excellent tool for vocal fold pathology detection. This paper presents the Mel Frequency ...
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 ...