CENG560 Speech Processing II

6 ECTS - 3-0 Duration (T+A)- . Semester- 3 National Credit

Information

Code CENG560
Name Speech Processing II
Term 2024-2025 Academic Year
Semester . Semester
Duration (T+A) 3-0 (T-A) (17 Week)
ECTS 6 ECTS
National Credit 3 National Credit
Teaching Language İngilizce
Level Yüksek Lisans Dersi
Type Normal
Mode of study Yüz Yüze Öğretim
Catalog Information Coordinator Prof. Dr. ZEKERİYA TÜFEKCİ


Course Goal / Objective

The objective of this course is to provide the fundamentals concepts of speech recognition systems based on Dynamic Time Warping, Hidden Markov Model, and Artificial Neural Network

Course Content

This course covers speech recognition systems based on Dynamic Time Warping, Hidden Markov Model, and Artificial Neural Network

Course Precondition

no prerequisites

Resources

Discrete Time Processing of Speech Signals John R. Deller

Notes

Spoken Language Processing A guide to Theory, Algorithm, and System Development. X. Huang, A. Acero, H. W. Hon


Course Learning Outcomes

Order Course Learning Outcomes
LO01 Designs Dynamic Time Warping Based Speech Recognition Systems
LO02 Designs Hidden Markov Model Based Speech Recognition Systems
LO03 Designs Artificial Neural Network Based Speech Recognition Systems
LO04 Understands Language Modeling


Relation with Program Learning Outcome

Order Type Program Learning Outcomes Level
PLO01 Bilgi - Kuramsal, Olgusal On the basis of the competencies gained at the undergraduate level, it has an advanced level of knowledge and understanding that provides the basis for original studies in the field of Computer Engineering.
PLO02 Bilgi - Kuramsal, Olgusal By reaching scientific knowledge in the field of engineering, he/she reaches the knowledge in depth and depth, evaluates, interprets and applies the information. 1
PLO03 Yetkinlikler - Öğrenme Yetkinliği Being aware of the new and developing practices of his / her profession and examining and learning when necessary. 3
PLO04 Yetkinlikler - Öğrenme Yetkinliği Constructs engineering problems, develops methods to solve them and applies innovative methods in solutions. 4
PLO05 Yetkinlikler - Öğrenme Yetkinliği Designs and applies analytical, modeling and experimental based researches, analyzes and interprets complex situations encountered in this process. 3
PLO06 Yetkinlikler - Öğrenme Yetkinliği Develops new and / or original ideas and methods, develops innovative solutions in system, part or process design. 4
PLO07 Beceriler - Bilişsel, Uygulamalı Has the skills of learning.
PLO08 Beceriler - Bilişsel, Uygulamalı Being aware of new and emerging applications of Computer Engineering examines and learns them if necessary.
PLO09 Beceriler - Bilişsel, Uygulamalı Transmits the processes and results of their studies in written or oral form in the national and international environments outside or outside the field of Computer Engineering. 3
PLO10 Beceriler - Bilişsel, Uygulamalı Has comprehensive knowledge about current techniques and methods and their limitations in Computer Engineering. 4
PLO11 Beceriler - Bilişsel, Uygulamalı Uses information and communication technologies at an advanced level interactively with computer software required by Computer Engineering. 3
PLO12 Bilgi - Kuramsal, Olgusal Observes social, scientific and ethical values in all professional activities. 4


Week Plan

Week Topic Preparation Methods
1 The Speech Recognition Problem Reading related chapter in the textbook Öğretim Yöntemleri:
Anlatım, Soru-Cevap, Tartışma
2 Dynamic Programming Reading related chapter in the textbook Öğretim Yöntemleri:
Anlatım, Soru-Cevap, Tartışma
3 Dynamic Time Warping Applied to Isolated Word Recognition Reading related chapter in the textbook Öğretim Yöntemleri:
Anlatım, Soru-Cevap, Tartışma
4 Dynamic Time Warping Applied to Continuous Speech Recognition Reading related chapter in the textbook Öğretim Yöntemleri:
Anlatım, Soru-Cevap, Tartışma
5 Training Issues in Dynamic Time Warping Algorithms Reading related chapter in the textbook Öğretim Yöntemleri:
Anlatım, Soru-Cevap, Tartışma
6 Introduction to Hidden Markov Model Reading related chapter in the textbook Öğretim Yöntemleri:
Anlatım, Soru-Cevap, Tartışma
7 Discrete Observation Hidden Markov Model Reading related chapter in the textbook Öğretim Yöntemleri:
Anlatım, Soru-Cevap, Tartışma
8 Mid-Term Exam Reading lecture notes and related chapters in the textbook Ölçme Yöntemleri:
Yazılı Sınav
9 Continuous Observation Hidden Markov Model Reading related chapter in the textbook Öğretim Yöntemleri:
Anlatım, Soru-Cevap, Tartışma
10 Acoustic Modeling Using Hidden Markov Model Reading related chapter in the textbook Öğretim Yöntemleri:
Anlatım, Soru-Cevap, Tartışma
11 Training and Recognition Reading related chapter in the textbook Öğretim Yöntemleri:
Anlatım, Soru-Cevap, Tartışma
12 Isolated Word and Continuous Speech Recignition Using HMM Reading related chapter in the textbook Öğretim Yöntemleri:
Anlatım, Soru-Cevap, Tartışma
13 Language Modeling Reading related chapter in the textbook Öğretim Yöntemleri:
Anlatım, Soru-Cevap, Tartışma
14 N-Gram Statistical Models Reading related chapter in the textbook Öğretim Yöntemleri:
Anlatım, Soru-Cevap, Tartışma
15 Artificial Neural Network Based Speech Recognition Systems Reading related chapter in the textbook Öğretim Yöntemleri:
Anlatım, Soru-Cevap, Tartışma
16 Term Exams Reading lecture notes and related chapters in the textbook Ölçme Yöntemleri:
Yazılı Sınav
17 Term Exams Reading lecture notes and related chapters in the textbook Ölçme Yöntemleri:
Yazılı Sınav


Student Workload - ECTS

Works Number Time (Hour) 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 0 0 0
Mid-term Exams (Written, Oral, etc.) 1 15 15
Final Exam 1 30 30
Total Workload (Hour) 157
Total Workload / 25 (h) 6,28
ECTS 6 ECTS

Update Time: 13.05.2024 03:07