ECTS - Speech Processing and Its Applications

Speech Processing and Its Applications (EE519) Course Detail

Course Name Course Code Season Lecture Hours Application Hours Lab Hours Credit ECTS
Speech Processing and Its Applications EE519 3 0 0 3 5
Pre-requisite Course(s)
EE 306 Digital Signal Processing
Course Language English
Course Type N/A
Course Level Natural & Applied Sciences Master's Degree
Mode of Delivery Face To Face
Learning and Teaching Strategies Lecture, Demonstration, Drill and Practice, Project Design/Management.
Course Coordinator
Course Lecturer(s)
  • N/A
Course Assistants
Course Objectives To become familiar with the speech signal and its applications.
Course Learning Outcomes The students who succeeded in this course;
  • Describe properties of speech signal
  • Describe short-term and long-term analysis concepts
  • Discuss methods for voiced/ unvoiced classification and pitch period estimation
  • Discuss various signal processing techniques for speech coding including LPC, MELP, CELP
  • Use various tools (or simulators) for speech processing applications such as speech synthesis and recognition, speech enhancement, speaker verification
Course Content Features of the speech signal; time-domain and frequency-domain analysis techniques; speech coding fundamentals; speech processing applications, speech recognition, speech synthesis, speaker verification.

Weekly Subjects and Releated Preparation Studies

Week Subjects Preparation
1 Speech signal properties Read your lectrue notes
2 Speech signal properties Read from the supplementary sources
3 Speech signal analysis methods Study the lecture notes and complete the simulations
4 Voiced/ unvoiced classification and pitch period estimation Review your lecture notes
5 Voiced/ unvoiced classification and pitch period estimation Review your lecture notes
6 Speech signal production model Study the lecture notes
7 Midterm examination
8 Speech coding methods Review your notes
9 Speech coding methods
10 Introducing research topics (Applications of speech processing) Consult the resources
11 Examining the given paper and submitting its summary Do your homework
12 Presentation of research study-1 Prepare your presentation
13 Presentation of research study-2 Prepare your presentation
14 Review of the topics
15 Final examination period Review the topics
16 Final examination period Review the topics


Other Sources 1. Theory and Applications of Digital Speech Processing, L. R. Rabiner and R. W. Schafer, Prentice-Hall Inc., 2011.
2. Discrete-Time Speech Signal Processing: Principles and Practice, Thomas F. Quatieri, Pearson Education, 2002
3. Speech Coding and Synthesis, W.B. Kleijn (Editor), K.K. Paliwal (Editor), Elsevier, 1995.

Evaluation System

Requirements Number Percentage of Grade
Attendance/Participation - -
Laboratory - -
Application - -
Field Work - -
Special Course Internship - -
Quizzes/Studio Critics - -
Homework Assignments 5 35
Presentation - -
Project - -
Report - -
Seminar - -
Midterms Exams/Midterms Jury 1 25
Final Exam/Final Jury 1 40
Toplam 7 100
Percentage of Semester Work 60
Percentage of Final Work 40
Total 100

Course Category

Core Courses X
Major Area Courses
Supportive Courses
Media and Managment Skills Courses
Transferable Skill Courses

The Relation Between Course Learning Competencies and Program Qualifications

# Program Qualifications / Competencies Level of Contribution
1 2 3 4 5
1 An ability to apply knowledge of mathematics, science, and engineering.
2 An ability to design and conduct experiments, as well as to analyse and interpret data.
3 An ability to design a system, component, or process to meet desired needs.
4 An ability to function on multi-disciplinary domains.
5 An ability to identify, formulate, and solve engineering problems.
6 An understanding of professional and ethical responsibility.
7 An ability to communicate effectively.
8 Recognition of the need for, and an ability to engage in life-long learning.
9 A knowledge of contemporary issues.
10 An ability to use the techniques, skills, and modern engineering tools necessary for engineering practice.
11 Skills in project management and recognition of international standards and methodologies
12 An ability to produce engineering products or prototypes that solve real-life problems.
13 Skills that contribute to professional knowledge.
14 An ability to make methodological scientific research.
15 An ability to produce, report and present an original or known scientific body of knowledge.
16 An ability to defend an originally produced idea.

ECTS/Workload Table

Activities Number Duration (Hours) Total Workload
Course Hours (Including Exam Week: 16 x Total Hours) 16 3 48
Special Course Internship
Field Work
Study Hours Out of Class 14 3 42
Presentation/Seminar Prepration 1 6 6
Homework Assignments 5 4 20
Quizzes/Studio Critics
Prepration of Midterm Exams/Midterm Jury
Prepration of Final Exams/Final Jury 1 6 6
Total Workload 122