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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 ...
Normal and hypoacoustic infant cry signal classification using time-frequency analysis and general regression neural network
(Elsevier Ireland Ltd., 2012-11)
Crying is the most noticeable behavior of infancy. Infant cry signals can be used to identify physical or psychological status of an infant. Recently, acoustic analysis of infant cry signal has shown promising results and ...
Human Affective (Emotion) behaviour analysis using speech signals: A review
(Institute of Electrical and Electronics Engineers (IEEE), 2012-02-27)
Affective (Emotional) state of a person is very important in medical application due to the fact that it can indicate the stress level of an individual. This can be done through manipulating the speech signal of
individual ...
Classification of speech dysfluencies with MFCC and LPCC features
(Elsevier Ltd., 2012-02)
The goal of this paper is to discuss comparison of speech parameterization methods: Mel-Frequency Cepstrum Coefficients (MFCC) and Linear Prediction Cepstrum Coefficients (LPCC) for recognizing the stuttered events. Speech ...
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 ...
Diagnosis of vocal fold pathology using time-domain features and systole activated neural network
(Institute of Electrical and Elctronics Engineering (IEEE), 2009-03-06)
Due to the nature of job, unhealthy social habits and voice abuse, the 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. ...
Development of attitude control system on RCM3400 microcontroller
(Institute of Electrical and Electronic Engineers (IEEE), 2009-02-17)
This paper describes the development of a nanosatellite altitude control system (ACS) which employ a filter base controller with comparison with a simple adaptive predictive fuzzy logic controller (APFLC) for a 1, 2 and 3 ...
Nano-satellite Attitude Control System
(Universiti Malaysia Perlis (UniMAP), 2009-12)
A satellite maneuvers through orbit with the use of an attitude control system (ACS) to stay on course and always pointing towards earth reference. This maximizes the solar cell-sun and camera-earth coverage, a process ...
Identification of vocal and voice disorders
(Universiti Malaysia Perlis (UniMAP), 2007-10-25)
The discrimination of normal and pathological voices using noninvasive acoustic analysis helps to perform accurate identification of voice disorders and diagnoses of vocal and voice disease. Acoustic analysis is a non- ...