Digital signal ProcessingDigital signal Processing

ECI-3-832

Semester 1 2003/2004

Telecommunication and Internet Engineering, School of Engineering,

South Bank University

CoordinatorCoordinator Dr. Z. Zhao Room:Room: T409 Tel:Tel: 0207 815 6340 Email: Email: zhaoza@lsbu.ac.ukzhaoza@lsbu.ac.uk

TextbookTextbook

Alan V. Oppenheim, Ronald W. Schafer, Discrete-time Signal Processing, 2ed, Prentice Hall, ISBN: 0-13-083443-2

Unit Structure 1.    Introduction to DSP 2.    Discrete-time signals 3.    Discrete-time systems 4.    The z-transform and the Fourier

transforms of discrete-time signals 5.    The discrete Fourier transform (DFT)

and its efficient computation (FFT) 6.    Digital filters

Unit Calendar (Changes possible)

Introduction to DSP 1 Discrete-time signals 1-2 Discrete-time systems 3-4 The z-transform and the Fourier transforms 5-7

of discrete-time signals The discrete Fourier transform (DFT) and 8-10

its efficient computation (FFT) Digital filters 12 Revision 13 Examination 14-15

Teaching and Learning Methods

Lecture: 2 hour each week Tutorial: 2 hour on Even weeks Laboratory work (Matlab

exercises):2 hour of on odd weeks Self learning: 102 hours

Assessment 3-hour written examination: 75% Workshop assignment: 25%

1. log book 2. formal written reports3. Submit: J200 between 10:00 and 16:00, following the standard school procedure.

Introduction to DSP1.1 What is DSP?

DSP, or Digital Signal Processing, is concerned with the use of programmable digital hardware and software (digital systems) to perform mathematical operations on a sequence of discrete numbers (a digital signal).

Introduction to DSP

1.2 A General DSP SystemAnti-

aliasing filter

A/D DSP

D/AReconstructi

on filter

Analog

signal

Analog

signal

Analog

signal

Analog

signal

Digital

signal

Digital

signal

An Example

Introduction to DSP1.3 Advantages: Programmable Well-defined, stable, and repeatable Manipulating data in the digital domian

provides high immunity from noise Use of computer algorithms allows

implementation of functions and features that are impossible with analog methods

Introduction to DSP

1.4 Disadvantages: Relatively low bandwidths Signal resolution is limited by the

D/A and A/D converters.

Introduction to DSP1.5 Applications: digital sound recording such as CD and

DAT speech and compression for

telecommucation and storage implementation of wireline and radio

modems image enhancement and compression speech synthesis and speech recognition

What is DSP Used For?

……And much more!And much more!

Speech Recognition System

Featureextractionspeech

Phoneme recognition

Phonememodels

Sentencerecognition

Wordrecognition

Word pronunciation

Semantic knowledge

decision

Syntactic knowledge

Dialogue knowledge

Text-to-Speech SynthesisTo be ornot to bethat is thequestion

Textnormalization

expandsabbreviationsdates, times,money..etc

Parsing Pronunciation

Prosodyrules

Tu bee awrnawt tu beedhat iz dhekwestchun

semantic &syntactic ‘partsof speech’ analysis of text

phonetic descriptionof each word, dictionarywith letter-to-sound rules as a back up

Waveformgeneration

Synthesized speech

Apply wordstress, durationand pitch

Phonetic-to-acoustictransformation

phonetic formInputtext

Speech Coding – Vocoder

Pulse Train

Random Noise

Vocal TractModel

V/U

Synthesized Speech

Decoder

Original Speech

Analysis:• Voiced/Unvoiced decision• Pitch Period (voiced only)• Signal power (Gain)

Signal PowerPitch

Period

Encoder

LPC-10:

JPEG ExampleOriginal

JPEG (100:1)JPEG (4:1)