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. Berrak Öztürk Şimşek
Course Assistant(s)
-
Schedule
Wednesday, 10:00 - 12:45
Office Hour(s)
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
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Course Schedules
Week
Contents
Learning Methods
1. Week
Introduction to the course: Explanation on course content, reference books, homework, quizzes, exams.
Oral presentation, practise
2. Week
Review of digital signal processing.
Oral presentation, practise
3. Week
Introduction to acoustical speech production
Oral presentation, practise
4. Week
Time domain processing of speech signals
Oral presentation, practise
5. Week
Speech Coding
Oral presentation, practise
6. Week
Review for midterm
Oral presentation, practise
7. Week
Midterm I
8. Week
The Short-time Fourier transform for speech.
Oral presentation, practise
9. Week
Estimation Theory, Linear Predictive Coding (LPC)
Oral presentation, practise
10. Week
Spectrum Analysis of Speech, Cepstrum
Oral presentation, practise
11. Week
Applications of Speech
Oral presentation, practise
12. Week
Applications of Speech
Oral presentation, practise
13. Week
Neural networks in Speech Signal
Oral presentation, practise
14. Week
Problem session and review of the course
Oral presentation, practise
15. Week
16. Week
17. Week
Assessments
Evaluation tools
Quantity
Weight(%)
Midterm(s)
1
30
Homework / Term Projects / Presentations
5
15
Attendance
1
5
Final Exam
1
50
Program Outcomes
PO-1
Adequate 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-2
Ability to identify, formulate, and solve complex engineering problems; ability to select and apply proper analysis and modeling methods for this purpose.
PO-3
Ability 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-4
Ability to devise, select, and use modern techniques and tools needed for engineering practice; ability to employ information technologies effectively.
PO-5
Ability to design and conduct experiments, gather data, analyze and interpret results for investigating engineering problems.
PO-6
Ability to work efficiently in intra-disciplinary and multi-disciplinary teams; ability to work individually.
PO-7
Ability to communicate effectively, both orally and in writing; knowledge of a minimum of one foreign language.
PO-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.
PO-9
Awareness of professional and ethical responsibility.
PO-10
Information about business life practices such as project management, risk management, and change management; awareness of entrepreneurship, innovation, and sustainable development.
PO-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.
Learning Outcomes
LO-1
describe human speech generation system
LO-2
Apply standard digital signal processing tools to analyse speech signals
LO-3
Employ signal processing techniques to analyse speech in time and frequency domains
LO-4
Experiment on different type of speech samples to extract some features and illustrate the results in MATLAB
LO-5
Design speech and speaker recognition systems for computer applications
LO-6
Develop software to implement text to speech and speech to text applications
