Digital signal Processing ECI-3-832
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Transcript of Digital signal Processing ECI-3-832
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: [email protected]@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)