Energy and nature based split multiple transform domain split vector quantization for speech coding

Keywords

Signal processing -- Digital techniques; Speech processing systems

Abstract

Recently vector quantization techniques in multiple transform domains for waveform signal characterization that improved signal-coding performance have been reported. Windowed portions of the signal are transformed into vectors that are encoded in multiple domains. The decoder selects the transform that yields the best result. In this contribution enhancements to this algorithm are developed and presented. Vectors are categorized either according to their energy contents (High/Low Energy) or to their speech nature (Voiced/Unvoiced). This is done by first splitting the signal into its category and then applying the multiple transform domains techniques on each part ' independently. Simulations were run on both algorithms and results showed improvement over the classical multiple transform algorithm applied on speech waveforms.

Notes

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Graduation Date

2003

Advisor

Mikhael, Wasfy

Degree

Master of Science (M.S.)

College

College of Engineering

Department

Electrical Engineering and Computer Science

Format

PDF

Pages

112 p.

Language

English

Length of Campus-only Access

None

Access Status

Masters Thesis (Open Access)

Identifier

DP0029114

Subjects

Dissertations, Academic -- Engineering; Engineering -- Dissertations, Academic

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