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FPGA Implementation of Speech Recognition System Based on HMM


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  • Product Description

This book introduced an approach to design and implement an embedded SoPC (System on Programmable Chip) technique with Altera Nios II processor on a FPGA chip for real-time speech recognition system by developing hardware/software with minimum usage of resources (hardware components) and relatively small size software. This reduces the memory utilization, achieved by using Mel Frequency Cepstral Coefficients (MFCCs) technique as feature extraction combined with its first derivative (∆MFCCs) including power computation of the speech frames (i.e. E,MFCC,∆E,and ∆MFCC), called observation vector of the speech signal. To model the obtained observation, Gaussian Mixture Model (GMM) has been used, which is passed to a Hidden Markov Model (HMM) as probabilistic model to process the GMM statistically to take a decision on the uttered words recognition, whether a single or composite, one or more syllable words (i.e. one, six, welcome). The words that are used for training and testing the system included selected English and Arabic words.

Product Specifications
SKU :COC79292
AuthorAlaa Refeis and Eyad Abbas
Number of Pages132
Publishing Year2014-03-14T00:00:00.000
Edition1 st
Book TypeElectronics & communications engineering
Country of ManufactureIndia
Product BrandLAP LAMBERT Academic Publishing
Product Packaging InfoBox
In The Box1 Piece
Product First Available On ClickOnCare.com2015-10-08 00:00:00
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