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M. P. Paulraj
University College of Engineering
37Publications
5H-index
108Citations
Publications 37
Newest
#2M. P. PaulrajH-Index: 5
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#1Kamalraj Subramaniam (Karpagam University)H-Index: 3
#2M. P. PaulrajH-Index: 5
Last.B. S. Divya (Karpagam University)H-Index: 2
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In this paper, a simple method to determine the hearing threshold state of a subject using the parametric model of EEG time series signal has been investigated. The proposed autoregressive (AR) pole-tracking algorithm tracks the position of the poles and extracts the upper and lower hearing threshold factors of a subject. From the results, for abnormal hearing subjects, the hearing-threshold values are about 40–50 % higher than the normal hearing subjects. The results also show that the hearing ...
2 CitationsSource
#1M. A. Yusnita (UiTM: Universiti Teknologi MARA)H-Index: 5
#2M. P. PaulrajH-Index: 5
Last.M. Nor Fadzilah (UiTM: Universiti Teknologi MARA)H-Index: 2
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The standard speech feature extractors such as Mel-Frequency Cepstral Coefficients (MFCC) and Linear Prediction Coefficients (LPC) fail to perform well under noisy conditions. In this paper two noise less-susceptible features are proposed to mitigate the deficiency of MFCC and LPC. Statistical descriptors of Mel-Bands Spectral Energy (MBSE) is applied to the traditional filter-bank analysis, however, this technique increases the feature size. This issue is tackled by proposing a transformation u...
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#1M. A. Yusnita (UiTM: Universiti Teknologi MARA)H-Index: 5
#2M. P. PaulrajH-Index: 5
Last.M. Nor Fadzilah (UiTM: Universiti Teknologi MARA)H-Index: 2
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To date, Malaysian English (MalE) accents arises from different ethnics of its populace are scarcely investigated using empirical methods that give a decisive conclusion to treat MalE as either uniform or non-uniform variety. The popularly used Mel-Frequency Cepstral Coefficients (MFCC) and Linear Prediction Coefficients (LPC) as feature extractors fail to perform well under noisy conditions. This paper proposes two new methods and noise less-susceptible feature extractors to mitigate the defici...
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#2M. P. PaulrajH-Index: 5
Last.Sazali YaacobH-Index: 27
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In this paper, a simple Brain Machine Interface (BMI) system that translates a change of rhythm from brain signal while performing a simulation of hand movement mentally into a real activity movement command is proposed. Four different imaginary tasks are used in the analysis process. A non-stimulus-based BCI approach is used to acquire the brain signal from ten different subjects using 19 channel EEG electrodes. Five spectral band features from each channel are extracted and associated to the r...
3 CitationsSource
Sep 1, 2013 in SOCO (Soft Computing)
#1M. P. PaulrajH-Index: 5
#2C. R. Hema (Karpagam University)
Last.Rajkumar PalaniappanH-Index: 8
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This paper presents a simple sign language recognition system that has been developed using skin colour segmentation and Elman neural network. A simple segmentation process is carried out to separate the right and left hand. The 2D-invariant moments of the right and left hand segmented image are obtained as features. Using the 2D-invariant moment features, an Elman neural network model was developed. The system has been implemented and tested for its validity. Experimental results show that the ...
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Sep 1, 2013 in SOCO (Soft Computing)
#1M. P. PaulrajH-Index: 5
In this research, a Proton model cars noise comfort level classification system has been developed to detect the noise comfort level in cars using artificial neural network. This research focuses on developing a database consisting of car sound samples measured from different Proton make models in stationary and moving state. In the stationary condition, the sound pressure level is measured at 1,300 RPM, 2,000 RPM and 3,000 RPM while in moving condition, the sound is recorded using dB Orchestra ...
2 CitationsSource
#1M. A. Yusnita (UiTM: Universiti Teknologi MARA)H-Index: 5
#2M. P. PaulrajH-Index: 5
Last.A. B. ShahrimanH-Index: 5
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This paper investigates the most accent-sensitive words for Malaysian English (MalE) speakers in multi-resolution 13 Mel-frequency cepstral coefficients. A text-independent accent system was implemented using different numbers of Mel-filters to determine the optimal settings for this database. Then, text-dependent accent systems were developed to rank the most accent-sensitive words for MalE speakers according to the classification rates. Prior work has also been conducted to test the significan...
5 CitationsSource
Jun 1, 2013 in ICIEA (Conference on Industrial Electronics and Applications)
#1M. A. YusnitaH-Index: 5
#2M. P. PaulrajH-Index: 5
Last.Nor Fadzilah MokhtarH-Index: 1
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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 recognition systems (ASRs) if not delicately handled. Normally accent recognizer in the preceding stage offers subsystem training or adaptation strategy to improve the ASRs. Formant analysis is one of the effective techniques used to extract accent information in speech. In this pape...
3 CitationsSource
#1M. P. PaulrajH-Index: 5
#2Sazali Bin YaccobH-Index: 3
Last.C. R. Hema (Karpagam University)H-Index: 3
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In this paper, a simple analysis has been made to distinguish the normal and abnormal hearing subjects using acoustically stimulated EEG signals. Independent power spectral features of the brain rhythms (delta, theta, alpha, beta, and gamma) were extracted from the recorded EEG signals. The extracted power spectral features were then associated to the auditory perception and neural network models for the left and right ears were developed. The result indicates that the gamma-power derived from t...
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