Implementation of vector quantization technique in image compression and speech recognition system

Type :

Term papers

Pages :

6 pages

Format :

.pdf

Published date :

09/21/2009

Category :

Science & technology

Sub category :

Physics & chemistry

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Summary :

Abstract
Introduction
Vector quantization
1. LBG algorithm
2. Mathematical analysis of LBG algorithm
3. Steps of LBG
Splitting codebook design
Experiment and output
Vector quantization in speech recognition
Algorithm
1. Pre-processing
2. Mel Frequency Wrapping (MFCC)
3. Principle of MFCC
4. Steps used in MFCC
Vector quantization
1. Initialization
2. Vector coding
3. Codebook updating
Conclusion
Bibliography

Abstract

In this paper, we have described the application of vector quantization in image and speech processing. Compressing image data by using vector quantization (VQ)[1]-[3] will compare Training Vectors with Code book. The result is an index of position with minimum distortion. Basically there are three ways of generating the code book: 1) The random method, 2) Pair wise nearest neighbor clustering and 3) Splitting. The implementing Random Code book will reduce the image quality. This paper presents the Splitting solution to implement the Code book, which improves the image quality by the average Training Vectors, then splits the average result to Code book that has minimum distortion. The result from this presentation will give the better quality of the image than using Random Code book. The area of speech processing is just developing, and shows the tremendous potentialities for widespread use in the future. In this paper we have processed the speech signal with the help of the digital signal processing techniques. The speech signal which is given as the input will be verified using speech recognition technique. We have used Mel Frequency Cepstrum Coefficient (MFCC) along with vector quantization (VQLBG) and Euclidean Distance.