Pran Hari Talukdar

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N Network s The ability of the ANN to learn given patterns makes them suitable for such applications. Fingerprint recognition is one such area that can be used as a means of biometric verification where the ANN can play a critical rule. An ANN can be configured and trained to handle such variations observed in the texture of the fingerprint. The specialty(More)
Biometric based technologies including retina, face, fingerprint, speech, hand geometry, handwriting, iris and typing rhythm are used to deal high security problems because, they have reached a high degree of maturity such as applications on secure authentication. Artificial Neural Networks (ANN) are non-parametric prediction tools based on the analogy of(More)
This paper depicts a way of speech recognition of Assamese Isolated words in both speaker dependent and speaker independent cases by taking the parameters Zero Crossing Rate (ZCR), Short Time Energy (STE), and Mel Frequency Cepstral Coefficients (MFCC) that are extracted from the utterances of the Assamese words. The system builds with training phase,(More)
Total Electron Content (TEC) data from GPS are now used as tools for identifying an impending earthquake. The extraction of earthquake induced features from this parameter needs elaborate processing because it involves filtration of data with respect to disturbed day variations, contribution from multi path effects and also normal day-to-day fluctuations(More)
Artificial Neural Network(ANN)s are efficient means of prediction, optimization and recognition. Retina is an unique biometric pattern that can be used as part of a verification system. An ANN can be configured and trained to handle such variations observed in the texture of the fingerprint and retina. Fingerprint recognition is one such area that can be(More)
Pitch and formant frequencies are important features in speech which are used to identify the emotional state of a person. The Pitch and Formants are first extracted from the speech signal and then their analysis is carried out to recognize 3 different emotional states of the person. The emotions considered are Neutral, Happy and Sad. The TTS-GU database(More)
This work presents an application of Fundamental Frequency (Pitch), Linear Predictive Cepstral Coefficient (LPCC) and Mel Frequency Cepstral Coefficient (MFCC) in identification of sex of the speaker in speech recognition research. The aim of this article is to compare the performance of these three methods for identification of sex of the speakers. A(More)
In this paper, a new simplified approach has been made for the design and implementation of a noise robust speech recognition using Multilayer Perceptron (MLP) based Artificial Neural Network and LPC-Cepstral Coefficient. Cepstral matrices obtained via Linear Prediction Coefficient are chosen as the eligible features. Here, MLP neural network based(More)
Artificial Neural Network (ANN)s are efficient means of prediction, optimization and recognition. Retina is a unique biometric pattern that can be used as a part of a verification system. An ANN can be configured and trained to handle such variations observed in the texture of the retina. The specialty of the work is associated with the fact that if the ANN(More)
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