|Grade, Semester||Year 3 1st semest [Department of Information and Electronic Engineering, Faculty of Science and Engineering]|
|Elective, Credits||Elective 2credit|
This course provides you the knowledge about multimedia computing technology which integrates various media such as image, sound, speech, and text. You will learn basic method, theory, and element technology to handle sound, speech, and text with computer. Moreover, you will learn basic method and theory of pattern recognition for handling these element media technologies.
You will deepen your understanding of the general principles of the multimedia processing, by actually applying some media processing algorithms to a media to compare and confirm those effects.
The course includes lectures, assignments, and final written examination.
This course follows DP4M in the diplomat policies of the faculty.
By the end of this course, you will be able to:
(1) understand and explain the fundamental principle and the algorithm of some simple pattern recognition algorithms
(2) understand and explain the Image media processing technology
(3) understand and explain the sound and speech media processing technology
(4) understand and explain the sound and text media processing technology
Grade will be computed as follows:
- Weekly assignments 50%
- Final examination 50%
You can receive a credit if you obtain 60% and above.
|Textbook||マルチメディアコンピューティング||尾内理紀夫||コロナ社 (ISBN: 978-4-339-02434-0)|
|References||マルチモーダルインタラクション||榎本美香, 飯田仁, 相川清明||コロナ社 (ISBN: 978-4-339-02784-6)|
|References||音声言語処理と自然言語処理||中川聖一（編）||コロナ社 (ISBN: 978-4-339-02888-1)|
|References||音声工学||板橋秀一||森北出版 (ISBN: 978-4-627-82811-7)|
You should summarize a note named "worksheet" by reading the textbook or additional texts on LMS, and submit it at the beginning of each class.
At the end of each class, problem sets will be provided over LMS. Solve problem sets for each class and submit them by the deadline.
|1||guidance for this course.|
What is multimedia?
|2||Pattern recognition (1): Bayes decision rule|
|3||Pattern recognition (2): Simple perceptron|
|4||Pattern recognition (3): Support Vector Machine|
|5||Pattern recognition (4): Unsupervised learning|
|6||Speech processing (1): Foundation of sound, Fourier transform|
|7||Speech processing (2): Spectral analysis for speech|
|8||Speech processing (3): Acoustic features|
|9||Speech processing (4): Acoustic analysis for speech recognition|
|10||Speech processing (5): Acoustic analysis for speech synthesis|
|11||Text processing (1): Morphological analysis|
|12||Text processing (2): N-gram|
|13||Text processing (3): Term weighting|
|14||Text processing (4): Information retrieval|
|15||Review and summary|