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Advanced Hands Free Computing?

Journal: International Journal of Computer Science and Mobile Computing - IJCSMC (Vol.3, No. 4)

Publication Date:

Authors : ; ; ; ;

Page : 580-589

Keywords : Hidden Marcov Model; feature extraction; MFCC; speech recognition; speech synthesis; Fourier transform;

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Speech recognition technology is already available to Higher Education and Further Education as are many of the alternatives to a mouse. In this project we have proposed a new application for hands free computing which uses voice as a major communication mean to assist user in monitoring and computing purpose on his machine. In our project as we have mainly used voice as communication mean. Speech technology encompasses two technologies: Speech Recognition and Speech Synthesis. In this project we have directly used speech engine which uses Hidden Marcov Model and Feature extraction technique as Mel scaled frequency cepstral. The mel scaled frequency cepstral coefficients (MFCCs) derived from Fourier transform and filter bank analysis are perhaps the most widely used front ends in state-of-the-art speech recognition systems. Our aim is to create more and more functionalities which can help human to assist in their daily life and also reduce their efforts. The HMM (Hidden Marcov Model) is used internally in which the state is not directly visible, but output, dependent on the state, is visible. Each state has a probability distribution over the possible output tokens. Therefore the sequence of tokens generated by an HMM gives some information about the sequence of states.

Last modified: 2014-04-20 16:37:10