Undergraduate
Faculty of Engineering and Architecture
Computer Engineering
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Digital Speech Processing

Course CodeSemester Course Name LE/RC/LA Course Type Language of Instruction ECTS
EE0836 - Digital Speech Processing 3/0/0 DE English 6
Course Goals
 The objective of this course is to give students a deep understanding of human speech generation system, feature extraction from speech signals, digital coding of speech, and recognition of speech or speaker by a computer. Another objective is to give students an understanding of applications of Speech Processing in emerging technologies.
Prerequisite(s) -
Corequisite(s) -
Special Requisite(s) -
Instructor(s) Assist. Prof. Dr. Güray GÜRKAN
Course Assistant(s) -
Schedule Wednesday, 15:00 - 17:45, 2B-11/13
Office Hour(s) 2D-13
Teaching Methods and Techniques Lecture and applications
Principle Sources L.R. Rabiner and R.W. Schafer (1978), Digital Processing of Speech Signals, Prentice Hall, Englewood Cliffs, NJ, USA, 0132136031

Aydın Akan (2000), Digital Speech Processing, Lecture Notes, Istanbul 
Other Sources -
Course Schedules
Week Contents Learning Methods
1. Week Introduction to the course: Explanation on course content, reference books, homework, quizzes, exams. Introduction to speech generation system
2. Week Review of digital signal processing. Microphone, data acquisition and MATLAB usage.
3. Week Introduction to acoustical speech modeling
4. Week Time domain processing of speech signals
5. Week Autocorrelation and Pitch Frequency estimation
6. Week The Short-time Fourier transform for speech.
7. Week PCM, Adaptive and Differential PCM, Delta Modulation
8. Week Midterm I
9. Week Linear Predictive Coding (LPC)
10. Week Speech Recognition by LPC
11. Week Speech Synthesis, Speech Recognition
12. Week Announcement of Final Projects
13. Week
14. Week Problem session and review of the course
15. Week
16. Week
17. Week
Assessments
Evaluation tools Quantity Weight(%)


Program Outcomes
PO-1Adequate knowledge in mathematics, science and engineering subjects pertaining to the relevant discipline; ability to use theoretical and applied information in these areas to model and solve engineering problems.
PO-2Ability to identify, formulate, and solve complex engineering problems; ability to select and apply proper analysis and modelling methods for this purpose.
PO-3Ability to design a complex system, process, device or product under realistic constraints and conditions, in such a way so 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.)
PO-4Ability to devise, select, and use modern techniques and tools needed for engineering practice; ability to employ information technologies effectively.
PO-5Ability to design and conduct experiments, gather data, analyse and interpret results for investigating engineering problems.
PO-6Ability to work efficiently in intra-disciplinary and multi-disciplinary teams; ability to work individually.
PO-7Ability to communicate effectively, both orally and in writing; knowledge of a minimum of one foreign language.
PO-8Recognition of the need for lifelong learning; ability to access information, to follow developments in science and technology, and to continue to educate him/herself.
PO-9Awareness of professional and ethical responsibility.
PO-10Information about business life practices such as project management, risk management, and change management; awareness of entrepreneurship, innovation, and sustainable development.
PO-11Knowledge 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.
Learning Outcomes
LO-1describe human speech generation system
LO-2Apply standard digital signal processing tools to analyse speech signals
LO-3Employ signal processing techniques to analyse speech in time and frequency domains
LO-4Experiment on different type of speech samples to extract some features and illustrate the results in MATLAB
LO-5Design speech and speaker recognition systems for computer applications
LO-6Develop software to implement text to speech and speech to text applications
Course Assessment Matrix:
Program Outcomes - Learning Outcomes Matrix
 PO 1PO 2PO 3PO 4PO 5PO 6PO 7PO 8PO 9PO 10PO 11