EE 8373
Digital Speech Processing
Spring 2004
Meeting Time:
M-W-F, 09:00-09:50
Room 129, Caruth
Instructor:
Professor Panos Papamichalis
Office: Room 349, Junkins
Telephone: 214-768-4905
E-mail: panos@engr.smu.edu
Office Hours:
M-W-F 10:00-11:00, or by appointment
(but you can send an e-mail any time)
Course Description:
A detailed treatment of theory and application of digital
speech processing. The course provides a fundamental knowledge of speech
signals and speech processing techniques. Topics include digital speech coding,
speech synthesis, speech recognition, and speaker verification.
Course Outline:
Introduction
Jan 12
Review of Digital Signal Processing Methods
Jan 14, 16
Fourier Transforms
z-Transforms
Sampling Theorem
Segmental Descriptions of Speech
Jan 21, 23
Concept of a Phoneme, Phonemic Analysis
The Vocal Mechanism
Electrical Analog of the Vocal Tract
Two Tube Model for Vowels
Digital Models for Speech Production
Jan 26, 28, 30
Acoustics of Speech Production, Properties of Speech Waveform
Digital Models and Basic Problems of Speech Processing
Digital Waveform Coding
Feb 2, 4, 6
Sampling Theorem and Quantization
Mu-law, A-law and Optimum Quantization
Time-Domain Analysis Methods
Feb 9, 11, 13
Peak, Energy and Zero-crossing Measurements
Auto-correlation Analysis
Differential Quantization
Adaptive Quantization
Feb 16, 18, 20
Adaptive Predictions and Applications
Noise Shaping
Short-Time Spectrum Analysis Methods
Feb 23, 25, 27
Definitions, Filterbanks, Computation, Sound Spectrograms
Decimation and Interpolation
Subband Coding
Adaptive Transform Coding
Homomorphic Speech Processing
Mar 1, 3, 5
Basic Theory, Cepstrum of Speech Signals, Pitch Detection
Formant Analysis and Applications
Linear Prediction Analysis Methods
Mar 15, 17, 19, 22
Basic Theory, Computation, Formant Analysis, Spectrum Analysis
Lattice Structures, LSPs, and Perceptual Weighting
Recursive Autocorrelation Functions
Pitch Detection and Vocoders
Analysis-Synthesis Systems
Mar 24, 26, 29, 31
Multi-Pulse Excited Vocoder
Code Excited Linear Predictive (CELP) Vocoder
Self-Excited Vocoder and Regular Pulse Excited Vocoders
Sinusoidal Analysis-Synthesis
Modern Coding Standards
Apr 2, 5, 7
Speech Processing Issues
Introduction to Automatic Speech Recognition
Apr 12, 14, 16, 19, 21
Dynamic-time warping
Hidden-Markov Models
Review
Apr 23, 26
Prerequisites:
EE 7372, Digital Signal Processing
Text:
“Discrete-Time Signal Processing”, Thomas Quatieri
Prentice-Hall, 2002
(Required)
“Digital Processing of Speech Signals”, L. Rabiner & R. Schafer
Prentice-Hall, 1978
(Optional)
Grading:
Homework
Computer projects
Final Exam
20%
50%
30% (Sat, May 1, 11:30-14:30)
Homework & Computer Projects:
The homework will be more of the analytical type.
Computer projects will require you to process signals and then view and
listen to them. The processing should be done using MATLAB, and the
MATLAB files should accompany the project, to be able to duplicate your
results.
Late homework: Solutions will be given on the lecture period after the
homework is collected. No homework will be accepted after solutions are
posted.
Late projects: The projects’ due date for distance education students will
be one lecture period after the in-class students. The grade will be reduced
by 10% for every lecture period you miss in turning it in. No projects will
be accepted after the last day of classes.
Feedback:
After every lecture:
1. What stood out as most important in today’s lecture?
2. What are you confused about?
3. Other comments / complaints / suggestions?