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Digital signal Processing ECI-3-832

Telecommunication and Internet Engineering, School of Engineering, South Bank University. Digital signal Processing ECI-3-832. Semester 1 2003 /2004. Coordinator. Dr. Z. Zhao Room: T409 Tel: 0207 815 6340 Email: zhaoza@lsbu.ac.uk. Textbook.

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Digital signal Processing ECI-3-832

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  1. Telecommunication and Internet Engineering, School of Engineering, South Bank University Digital signal ProcessingECI-3-832 Semester 1 2003/2004

  2. Coordinator • Dr. Z. Zhao • Room: T409 • Tel: 0207 815 6340 • Email: zhaoza@lsbu.ac.uk

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

  4. 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

  5. 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

  6. 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

  7. Assessment • 3-hour written examination: 75% • Workshop assignment: 25% 1. log book 2. formal written reports 3. Submit: J200 between 10:00 and 16:00, following the standard school procedure.

  8. Introduction to DSP 1.1 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).

  9. Anti-aliasing filter DSP A/D Reconstruction filter D/A Introduction to DSP 1.2 A General DSP System Analog signal Analog signal Digital signal Digital signal Analog signal Analog signal

  10. An Example

  11. Introduction to DSP 1.3 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

  12. Introduction to DSP 1.4 Disadvantages: • Relatively low bandwidths • Signal resolution is limited by the D/A and A/D converters.

  13. Introduction to DSP 1.5 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

  14. What is DSP Used For? …And much more!

  15. Word pronunciation Phoneme models Semantic knowledge Feature extraction Phoneme recognition Word recognition Sentence recognition speech decision Dialogue knowledge Syntactic knowledge Speech Recognition System

  16. To be or not to be that is the question Input text Tu bee awr nawt tu bee dhat iz dhe kwestchun phonetic form Text normalization Parsing Pronunciation semantic & syntactic ‘parts of speech’ analysis of text phonetic description of each word, dictionary with letter-to-sound rules as a back up expands abbreviations dates, times, money..etc Prosody rules Waveform generation Synthesized speech Apply word stress, duration and pitch Phonetic-to- acoustic transformation Text-to-Speech Synthesis

  17. Encoder Original Speech • Analysis: • Voiced/Unvoiced decision • Pitch Period (voiced only) • Signal power (Gain) Decoder PitchPeriod Signal Power Pulse Train V/U Vocal TractModel Synthesized Speech LPC-10: Random Noise Speech Coding – Vocoder

  18. Original JPEG (4:1) JPEG (100:1) JPEG Example

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