AUTOMATIC SPECTRAL ANALYSIS FOR SPEECH TO TEXT CONVERSION WITH EMBEDDED EXECUTION |
Author(s): |
| P.Yasotha , Kongunadu college of Engineering; N.Rajasekaran, Kongunadu college of Engineering; M.Nathiya, Kongunadu college of Engineering |
Keywords: |
| Speech Recognition, Mel Frequency Ceptral Coefficients, Hidden Markow Model, PIC Microcontroller, URAT Interface |
Abstract |
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Speech signal important role in the Digital signal processing. In this paper speech sample observed with MFCC for the improvement of speech feature representation of the HMM based training approach. MFCC is used to extract the voice features from the voice sample and also HMM is used to the recognize the speaker based on the extracted features. I order to recognize the speaker first train the extracted feature by using HMM parameters and then compared to the original voice signal. If it is matched the voice signals to produce the text by using MATLAB Software. The Simulation results show an improvement of speech recognition with respect to computational time, learning precision for a speech recognition system. Here MATLAB output is interface to the Microcontroller by using UART and display through the LCD module. |
Other Details |
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Paper ID: IJSRDV2I9371 Published in: Volume : 2, Issue : 9 Publication Date: 01/12/2014 Page(s): 644-646 |
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