Please use this identifier to cite or link to this item:
http://dspace.unimap.edu.my:80/xmlui/handle/123456789/3288
Title: | Speech compression based on LPC method |
Authors: | Muhammad Zaidi Muhammad Nor Hasliza A. Rahim (Advisor) |
Keywords: | Compressed speech Speech processing systems Digital electronics Signal theory (Telecommunication) Speech synthesis Speech compression |
Issue Date: | Apr-2008 |
Publisher: | Universiti Malaysia Perlis |
Abstract: | Speech processing is currently a key focus for many researchers in the area of Digital Signal Processing. This project is focus on the topic of voice conversion, which involves producing the speech compression. The aim of speech compression is to produce a compact representation of speech sounds such that when reconstructed it is perceived to be close to the original. In addition to the implementation of a set of methods, as LPC (Linear Prediction Coding) techniques, encoding good quality speech at a low bit rate and provides extremely accurate estimates of speech parameters. Linear predictive coding (LPC) is defined as a digital method for encoding an analog signal in which a particular value is predicted by a linear function of the past values of the signal. It was first proposed and approved as a method for encoding human speech. The main steps of the complete project include: a method for compressing voice transformation, create a programming in Matlab software and finally translating it into Digital Signal Processing board. |
URI: | http://dspace.unimap.edu.my/123456789/3288 |
Appears in Collections: | School of Materials Engineering (FYP) |
Files in This Item:
File | Description | Size | Format | |
---|---|---|---|---|
References and appendix.pdf | 42 kB | Adobe PDF | View/Open | |
Conclusion.pdf | 15.37 kB | Adobe PDF | View/Open | |
Results and discussion.pdf | 286.15 kB | Adobe PDF | View/Open | |
Methodology.pdf | 556.38 kB | Adobe PDF | View/Open | |
Literature review.pdf | 1.33 MB | Adobe PDF | View/Open | |
Introduction.pdf | 200.28 kB | Adobe PDF | View/Open | |
Abstract, Acknowledgement.pdf | 23.4 kB | Adobe PDF | View/Open |
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