Browsing Sazali Yaacob, Prof. Dr. by Author "paul@unimap.edu.my"

Now showing items 1-20 of 29

    • Automatic detection of voice disorders using self loop architecture in back propagation network 

      Murugesa Pandiyan, Paulraj, Prof. Madya Dr,; Sazali, Yaacob, Prof. Dr.; Sivanandam, S. N.; Muthusamy, Hariharan, Dr. (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 ...

    • Damage detection in steel plates using discrete cosine transformation techniques and artificial neural network 

      Paulraj, M.P.; Mohd Shukry, Abdul Majid; Sazali, Yaacob; Mohd Hafiz, Fazalul Rahiman; R Pranesh, Krishnan (Universiti Malaysia Perlis, 2009-10-11)
      In this paper, a simple method for crack identification in steel plates based on the Frame Energy based Discrete Cosine Transformation [DCT] moments is presented. A simple experimental procedure is also proposed to measure ...

    • Detection of vocal fold paralysis and edema using time-domain features and probabilistic neural network 

      Hariharan, Muthusamy; Paulraj, Murugesa Pandiyan, Assoc. Prof.; Sazali, Yaacob, Prof. Dr. (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 ...

    • Diagnosis of voice disorders using band energy spectrum in wavelet domain 

      Murugesa Pandiyan, Paulraj, Prof. Madya Dr,; Sazali, Yaacob, Prof. Dr.; Muthusamy, Hariharan, Dr. (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 

      Paulraj, Muregesa Pandiyan, Prof. Madya Dr.; Sazali, Yaacob, Prof. Dr.; Hariharan, Muthusamy (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 ...

    • Discrimination of pathological voices using systole activated neural network 

      Murugesa Pandiyan, Paulraj, Prof. Madya Dr,; Sazali, Yaacob, Prof. Dr.; Hariharan, Muthusamy, Dr. (Noise, Vibration and Comfort Research Group, 2007-11-27)
      The discrimination of normal and pathological voices using noninvasive acoustical analysis features helps speech specialits to perform accurate diagnoses of vocal and voices disease. Acoustic analysis is a non-invasive ...

    • EEG based detection of conductive and sensorineural hearing loss using artificial neural networks 

      Pandiyan, Paulraj Murugesa , Prof. Dr.; Subramaniam, Kamalraj; Sazali, Yaacob, Prof. Dr.; Abdul Hamid, Adom, Prof. Dr.; Hema, C. R. (Advanced Institute of Convergence IT, 2013-05)
      In this paper, a simple method has been proposed to distinguish the normal and abnormal hearing subjects (conductive or sensorineural hearing loss) using acoustically stimulated EEG signals. Auditory Evoked Potential (AEP) ...

    • EEG signal classification using Particle Swarm Optimization (PSO) neural network for brain machine interfaces 

      Paulraj, Murugesapandian; Hema, Chengalvarayan Radhakrishnamurthy; Ramachandran, Nagarajan; Sazali, Yaacob; Abdul Hamid, Adom (Association for the Advancement of Modelling & Simulation Techniques in Enterprises (A.M.S.E.), 2008)
      The brain uses the neuromuscular channels to communicate and control its external environment, however many disorders can disrupt these channels. Amyotrophic lateral sclerosis is one such disorder which impairs the neural ...

    • Feature extraction based on mel-scaled wavelet packet transform for the diagnosis of voice disorders 

      Murugesa Pandian, Paulraj, Prof. Madya Dr,; Sazali, Yaacob, Prof. Dr.; Muthusamy, Hariharan, Dr. (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 ...

    • Feature space reduction in ethnically diverse Malaysian English accents classification 

      Yusnita, Mohd Ali; Pandiyan, Paulraj Murugesa , Prof. Dr.; Sazali, Yaacob, Prof. Dr.; Shahriman, Abu Bakar, Dr. (IEEE Conference Publications, 2013)
      In this paper we propose a reduced dimensional space of statistical descriptors of mel-bands spectral energy (MBSE) vectors for accent classification of Malaysian English (MalE) speakers caused by diverse ethnics. Principle ...

    • Identification of vocal and voice disorders 

      Murugesa Pandiyan, Paulraj, Prof. Madya Dr.; Sazali, Yaacob, Prof. Dr.; Mohd Rizon, Mohammed Juhari, Prof. Dr.; Sivanandam, S. N.; Muthusamy, Hariharan, Dr. (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- ...

    • Implementing eigen features methods/neural network for EEG signal analysis 

      Saidatul Ardeenawatie, Awang; Pandiyan, Paulraj Murugesa, Prof. Dr.; Sazali, Yaacob, Prof. Dr. (Institute of Electrical and Electronics Engineers (IEEE), 2013-01)
      This paper presented the possibility of implementing eigenvector methods to represent the features of electroencephalogram signal. In this study, three eigenvector methods were investigated namely Pisarenko, Multiple Signal ...

    • An Intelligent Gesture to Voice Communication System for Hearing Impaired 

      Paulraj, M. P. , Prof. Dr.; Sazali, Yaacob, Prof. Dr.; Hazry, Desa, Prof. Madya Dr.; Wan Mohd Ridzuan; Sathees, Kumar; Raj, Kumar; Norasmadi, Abd Rahim (Universiti Malaysia Perlis, 2010-01-07)
      The designed system is accessible and user friendly. This system is primarily designed for deaf, deafened and hard of hearing people to solve their communication problems and gives them the same whole life experience to ...

    • An Intelligent System for Engine Fault Detection 

      Paulraj, M.P., Assoc. Prof Dr.; Sazali, Yaacob, Prof. Dr.; Nor Shaifudin, Abd Hamid (Malaysian Invention & Design Society (MINDS), 2007-05-18)
      Condition monitoring and machinery fault diagnosis are central to the implementation of efficient maintenance management strategies. In real time vehicle servicing environment engine fault diagnosis is being done manually ...

    • Motorbike engine faults diagnosing system using neural network 

      Paulraj, Murugesa Pandiyan, Prof. Dr.; Mohd Shukry, Abdul Majid, Dr.; Sazali, Yaacob, Prof. Dr.; Zin, M.Z.M. (IEEE Conference Publications, 2008-12)
      Monitoring systems for motorbike industry requires high and efficient degree of performance. In recent years, automatic identification and diagnosis of motorbike engine faults has become a very complex and critical task. ...

    • Neural network based detection of voice disorders using energy spectrum and equal-loudness contours 

      Murugesa Pandian, Paulraj, Prof. Madya Dr.; Sazali, Yaacob, Prof. Dr.; Sivanandam, S. N.; Muthusamy, Hariharan, Dr. (Universiti Teknologi MARA (UiTM)Faculti of Electrical Engineering, 2008-03-07)
      Impairment of vocal function can have a major impact on the quality of life, severely limiting communication at work and affecting all social aspect of daily life. In the recent years, voice disease are increasing dramatically ...

    • A phoneme based sign language recognition system using interleaving feature and neural network 

      Paulraj, Murugesa Pandiyan, Assoc. Prof. Dr.; Sazali, Yaacob, Prof. Dr.; Mohd Shuhanaz, Zanar Azalan; Palaniappan, Rajkumar (Universiti Malaysia Perlis (UniMAP)School of Mechatronic Engineering, 2012-02-27)
      A sign language is a language which, instead of acoustically conveyed sound patterns, uses visually transmitted sign patterns. Sign languages are commonly developed in hearing impaired communities, which can include ...

    • Phoneme-based or isolated-word modeling speech recognition system? An overview 

      Yusnita, M. A.; Murugesa Pandiyan, Paulraj, Assoc. Prof. Dr.; Sazali, Yaacob, Prof. Dr.; Shahriman, Abu Bakar; Saidatul Ardeenaawatie, Awang; Ahmad Nazri, Abdullah (Institute of Electrical and Electronics Engineers (IEEE), 2011-03-04)
      In this paper speech theories and some methodological concerns about feature extraction and classification techniques widely used in speech recognition system are surveyed and discussed. The shortage of isolated word speech ...

    • Speaker accent recognition through statistical descriptors of Mel-bands spectral energy and neural network model 

      Yusnita, Mohd Ali; Pandiyan, Paulraj Murugesa, Prof. Dr.; Sazali, Yaacob, Prof. Dr.; Shahriman, Abu Bakar, Dr.; Nataraj, Sathees Kumar (IEEE Conference Publications, 2012-10)
      Accent recognition is one of the most important topics in automatic speaker and speaker-independent speech recognition (SI-ASR) systems in recent years. The growth of voice-controlled technologies has becoming part of our ...

    • Statistical formant descriptors with linear predictive coefficients for accent classification 

      Yusnita, Mohd Ali; Pandiyan, Paulraj Murugesa , Prof. Dr.; Sazali, Yaacob, Prof. Dr.; Shahriman, Abu Bakar, Dr.; Nor Fadzilah, Mokhtar (Institute of Electrical and Electronics Engineers (IEEE), 2013-06)
      Accent is a special trait of human speech that can deliver some information about a speaker's background. At the same time it is one of the profound factors that affects the intelligibility and performance of speech ...