ELECTRICAL AND ELECTRONICS ENGINEERING
Bachelor TR-NQF-HE: Level 6 QF-EHEA: First Cycle EQF-LLL: Level 6

Course Introduction and Application Information

Course Code Course Name Semester Theoretical Practical Credit ECTS
EEE5540 Speech Processing Spring 3 0 3 6
The course opens with the approval of the Department at the beginning of each semester

Basic information

Language of instruction: En
Type of course: Departmental Elective
Course Level: Bachelor
Mode of Delivery: Face to face
Course Coordinator : Dr. Öğr. Üyesi ZAFER İŞCAN
Course Objectives: This is an advanced level course on speech signal processing for graduate level students in Electrical and Electronics engineering. The course provides the student both the theoretical foundations of speech analysis and the detailed practical information about speech technology applications such as speech coding, speech synthesis and recognition.

Learning Outputs

The students who have succeeded in this course;
1. Describe fundamentals of speech production mechanism and auditory perception
2. Describe basic spectral processing methods for speech signals
3. Describe linear prediction modeling of speech signals and experiment in use of linear prediction modeling in speech analysis, coding and synthesis
4. Design speech coding systems
5. Design speech synthesis systems
6. Analyze expressivity in speech signals
7. Design speech recognition systems

Course Content

Speech production mechanism and auditory perception. Spectral processing methods for speech signals. Linear prediction modeling of speech signals. Speech analysis, coding and synthesis.Expressivity in speech signals. Speech recognition systems.

Weekly Detailed Course Contents

Week Subject Related Preparation
1) Basics of sound signals, auditory perception and speech production mechanism.
2) Review of signal processing concepts: short-time Fourier analysis
3) The Source-Filter model of speech. Overview of commonly used speech analysis software and application in recording, segmenting, viewing, analyzing speech data
4) Basic speech signal parameters and estimation methods: pitch, formants, glottal flow, etc.
5) Linear predictive modeling of speech signals
6) Speech coding (CELP codec used in mobile communication)
7) Midterm, introduction to text-to-speech synthesis.
8) Text-to-speech(TTS) synthesis, basic paradigms, models
9) Structure of commercial TTS systems, database design methods, systems tailored to applications. Application: create a synthesizer with your own voice
10) Prosody modeling and analysis
11) Analysis of expressivity, pathology and emotion in speech signals
12) Homomorphic processing
13) Speech recognition
14) Overview of the course

Sources

Course Notes: Discrete-time processing of speech signals, John R. Deller, John H. L. Hansen, John G. Proakis, Wiley-IEEE Press, ISBN-10: 0780353862
References: Theory and Applications of Digital Speech Processing, Lawrence Rabiner, Ronald Schafer, Prentice Hall, ISBN-10: 0136034284

Evaluation System

Semester Requirements Number of Activities Level of Contribution
Attendance % 0
Laboratory % 0
Application % 0
Field Work % 0
Special Course Internship (Work Placement) % 0
Quizzes % 0
Homework Assignments 2 % 5
Presentation 1 % 5
Project 1 % 30
Seminar % 0
Midterms 1 % 20
Preliminary Jury % 0
Final 1 % 40
Paper Submission % 0
Jury % 0
Bütünleme % 0
Total % 100
PERCENTAGE OF SEMESTER WORK % 30
PERCENTAGE OF FINAL WORK % 70
Total % 100

ECTS / Workload Table

Activities Number of Activities Duration (Hours) Workload
Course Hours 14 3 42
Laboratory 0 0 0
Application 0 0 0
Special Course Internship (Work Placement) 0 0 0
Field Work 0 0 0
Study Hours Out of Class 14 6 84
Presentations / Seminar 1 10 10
Project 1 20 20
Homework Assignments 3 10 30
Quizzes 0 0 0
Preliminary Jury 0 0 0
Midterms 1 3 3
Paper Submission 0 0 0
Jury 0 0 0
Final 1 3 3
Total Workload 192

Contribution of Learning Outcomes to Programme Outcomes

No Effect 1 Lowest 2 Low 3 Average 4 High 5 Highest
           
Program Outcomes Level of Contribution
1) Adequate knowledge in mathematics, science and electric-electronic engineering subjects; ability to use theoretical and applied information in these areas to model and solve engineering problems.
2) Ability to identify, formulate, and solve complex engineering problems; ability to select and apply proper analysis and modeling methods for this purpose.
3) Ability to design a complex system, process, device or product under realistic constraints and conditions, in such a way as to meet the desired result; ability to apply modern design methods for this purpose. (Realistic constraints and conditions may include factors such as economic and environmental issues, sustainability, manufacturability, ethics, health, safety issues, and social and political issues, according to the nature of the design.)
4) Ability to devise, select, and use modern techniques and tools needed for electrical-electronic engineering practice; ability to employ information technologies effectively.
5) Ability to design and conduct experiments, gather data, analyze and interpret results for investigating engineering problems.
6) Ability to work efficiently in intra-disciplinary and multi-disciplinary teams; ability to work individually.
7) Ability to communicate effectively in English and Turkish (if he/she is a Turkish citizen), both orally and in writing.
8) Recognition of the need for lifelong learning; ability to access information, to follow developments in science and technology, and to continue to educate him/herself.
9) Awareness of professional and ethical responsibility.
10) Information about business life practices such as project management, risk management, and change management; awareness of entrepreneurship, innovation, and sustainable development.
11) Knowledge about contemporary issues and the global and societal effects of engineering practices on health, environment, and safety; awareness of the legal consequences of engineering solutions.