Updates on the campus response to coronavirus (COVID-19)

ECE Course Syllabus

ECE6255 Course Syllabus

ECE6255

Digital Processing of Speech Signals (3-0-0-3)


Lab Hours
0 supervised lab hours and 0 unsupervised lab hours

Technical Interest
Group
Digital Signal Processing

Course Coordinator
Lee,Chin-Hui

Prerequisites
ECE4270

Corequisites
None

Catalog Description
The application of digital signal processing to problems in speech communication. Part of this goal requires a laboratory project.

Textbook(s)
Rabiner & Schafer, Theory and Applications of Digital Speech Processing, Pearson Higher Education, 2011. ISBN 9780136034285 (required)


Strategic
Performance
Indicators (SPIs)
SPIs are a subset of the abilities a student will be able to demonstrate upon successfully completing the course.

Outcome 1 (Students will demonstrate expertise in a subfield of study chosen from the fields of electrical engineering or computer engineering):
1.	Using tools learned in class to display the speech waveform and its corresponding spectrogram, pitch contour, energy progression and format profile. 
2.	Deriving cues from above-mentioned time-frequency features can be used to further infer key information about the speaker, speaking environment and even the linguistic content.

Outcome 2 (Students will demonstrate the ability to identify and formulate advanced problems and apply knowledge of mathematics and science to solve those problems):

Outcome 3 (Students will demonstrate the ability to utilize current knowledge, technology, or techniques within their chosen subfield):
1.	Given a project at work, the students should be able to carry out literature survey, problem formulation, speech data collection, speech experiments, and project reports by relating real-world signal processing problems to what they learn in class and analyze their experimental results by varying key parameters

Topical Outline
 1. Introduction to Speech Communication
    a. Concept of Speech Knowledge Hierarchy 
    b. Distinctive Features and Derived Phonetic Structure
    c. Supersegmental Description of Speech
 2. The Vocal Mechanism and Sound Acoustics
    a. Electrical Analog of the Vocal Tract
    b. Two Tube Model for Vowels
    c. Fricatives, Glides, Liquids and Stops
 3. Review of Digital Signal Processing
    a. Fourier Transforms
    b. z-Transforms
    c. System Functions
 4. Digital Models for Speech Production
    a. Acoustics of Speech Production, Properties of Speech Waveform
    b. Digital Models and Basic Problems of Speech Processing
 5. Speech Waveform Fundamentals
    a. Sampling Theorem and Quantization
    b. Mu-law, A-law and Optimum Quantization
 6. Time-Domain Analysis Methods
    a. Peak, Energy and Zero-crossing Measurements
    b. Auto-correlation Analysis
 7. Short-Time Spectrum Analysis Methods
    a. Definitions, Filterbanks, Computation, Sound Spectrograms
    b. Decimation and Interpolation
 8. Cepstrum and Homomorphic Speech Processing
    a. Basic Theory, Cepstrum of Speech Signals
    b. Pitch Detection, Formant Analysis and Applications
    c. Mel-cepstra
 9. Linear Prediction Analysis
    a. Basic Theory and Implementations
    b. Formant Analysis, Spectrum Analysis
    c. Lattice Structures,Recursive Autocorrelation Functions
10. Introduction to Speech Coding
11. Introduction to Speech Synthesis and Vocoders
12. Introduction to Automatic Speech and Speaker Recognition