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| Course Description |
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| Course Name |
: |
Speech Processing I |
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| Course Code |
: |
CENG-549 |
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| Course Type |
: |
Optional |
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| Level of Course |
: |
Second Cycle |
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| Year of Study |
: |
1 |
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| Course Semester |
: |
Fall (16 Weeks) |
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| ECTS |
: |
6 |
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| Name of Lecturer(s) |
: |
Assoc.Prof.Dr. ZEKERİYA TÜFEKÇİ
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| Learning Outcomes of the Course |
: |
Knows how speech signals are produced
Models the speech signals
Learns methods to analyze and synthesize speech signals
Learns the speech signal coding methods
Learns basic information about speech recognition
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| Mode of Delivery |
: |
Face-to-Face |
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| Prerequisites and Co-Prerequisites |
: |
None |
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| Recommended Optional Programme Components |
: |
None |
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| Aim(s) of Course |
: |
To teach basic subjects of the speech signal processing |
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| Course Contents |
: |
Mathematical models of human speech production and perception mechanisms, speech analysis/synthesis techniques including linear prediction, filter bank models and homomorphic filtering. Applications to speech synthesis and automatic speech recognition.
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| Language of Instruction |
: |
English |
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| Work Place |
: |
Classroom 2 |
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Course Outline /Schedule (Weekly) Planned Learning Activities |
| Week | Subject | Student's Preliminary Work | Learning Activities and Teaching Methods |
|
1 |
Fundamentals of speech Science |
Reading |
Lecture |
|
2 |
Modeling speech Production |
Reading, homework |
Lecture |
|
3 |
Modeling speech Production |
Reading |
Lecture |
|
4 |
Modeling speech Production |
Reading, homework |
Lecture |
|
5 |
Short-term processing of speech |
Reading |
Lecture |
|
6 |
Short-term processing of speech |
Reading, homework |
Lecture |
|
7 |
Short-term processing of speech |
Reading |
Lecture |
|
8 |
Midterm exam |
Reading |
Written exam |
|
9 |
Linear Predictio Analysis |
Reading, homework |
Lecture |
|
10 |
Linear Predictio Analysis |
Reading |
Lecture |
|
11 |
Cepstral Analysis |
Reading, homework |
Lecture |
|
12 |
Cepstral Analysis |
Reading |
Lecture |
|
13 |
Speech coding and synthesis |
Reading, homework |
Lecture |
|
14 |
Speech coding and synthesis |
Reading |
Lecture |
|
15 |
Introduction to speech recognition |
Reading, homework |
Lecture |
|
16/17 |
Final exam |
Reading |
Written exam |
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Required Course Resources |
| Resource Type | Resource Name |
| Recommended Course Material(s) |
 Discrete-Time Processing of Speech Signals. John R. Deller, John G. Proakis, John H. L. Hansen
Spoken Language Processing. A Guide to Theory, Algorithm, and System Development. Xuedong Huang, Alex Acero, Hsiao-Wuen Hon
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| |
| Required Course Material(s) | |
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Assessment Methods and Assessment Criteria |
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Semester/Year Assessments |
Number |
Contribution Percentage |
|
Mid-term Exams (Written, Oral, etc.) |
1 |
50 |
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Homeworks/Projects/Others |
7 |
50 |
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Total |
100 |
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Rate of Semester/Year Assessments to Success |
40 |
| |
|
Final Assessments
|
100 |
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Rate of Final Assessments to Success
|
60 |
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Total |
100 |
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| Contribution of the Course to Key Learning Outcomes |
| # | Key Learning Outcome | Contribution* |
|
1 |
Reaches wide and deep knowledge through scientific research in the field of computer engineering, evaluates, implements, and comments. |
4 |
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2 |
Describes and uses information hidden in limited or missing data in the field of computer engineering by using scientific methods and integrates it with information from various disciplines. |
4 |
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3 |
Follows new and emerging applications of computer engineering profession, if necessary, examines and learns them |
3 |
|
4 |
Develops methods and applies innovative approaches in order to formulate and solve problems in computer engineering. |
4 |
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5 |
Proposes new and/or original ideas and methods in the field of computer engineering in developing innovative solutions for designing systems, components or processes. |
4 |
|
6 |
Designs and implements analytical modeling and experimental research and solves the complex situations encountered in this process in the field of Computer Engineering |
4 |
|
7 |
works in multi disciplinary teams and takes a leading role and responsibility. |
3 |
|
8 |
Learns at least one foreign language at the European Language Portfolio B2 level to communicate orally and written |
2 |
|
9 |
Presents his/her research findings systematically and clearly in oral and written forms in national and international meetings. |
1 |
|
10 |
Describes social and environmental implications of engineering practice. |
1 |
|
11 |
Considers social, scientific and ethical values in collection, interpretation and announcement of data. |
3 |
|
12 |
Acquires a comprehensive knowledge about methods and tools of computer engineering and their limitations. |
4 |
| * Contribution levels are between 0 (not) and 5 (maximum). |
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| Student Workload - ECTS |
| Works | Number | Time (Hour) | Total Workload (Hour) |
| Course Related Works |
|
Class Time (Exam weeks are excluded) |
14 |
3 |
42 |
|
Out of Class Study (Preliminary Work, Practice) |
14 |
5 |
70 |
| Assesment Related Works |
|
Homeworks, Projects, Others |
7 |
3 |
21 |
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Mid-term Exams (Written, Oral, etc.) |
1 |
6 |
6 |
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Final Exam |
1 |
6 |
6 |
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Total Workload: | 145 |
| Total Workload / 25 (h): | 5.8 |
| ECTS Credit: | 6 |
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