Module Description:

This module is intended for advanced undergraduate and graduate students who wish to understand modern audio technologies, from low-level audio representation to high-level content analysis, from basic waveform to advanced audio compression and compressed domain processing.

Fundamentals of audio technologies will first be taught, with a focus on audio aspects relevant for students to perform research in multimedia, embedded systems, database and networks. We also pay attention to technologies with significant industrial relevance. Upon completion of this module, students should be comfortable to use audio in their own research; They should also have the fundamental knowledge to perform industrial R&D or product creation.

Course Characteristics:

• Modular Credits: 4.

• Prerequisite: CS3242 Hypermedia Technologies or equivalent is required for the course. Basic knowledge of signal processing is of great help.

• Teaching Staff: Ye Wang , wangye AT comp.nus.edu.sg. Office: AS6 #04-08 (6516 2980). You may also contact me via email.

• Workload: 2 lecture hours, about 8 hours preparation per week depending on your background.

• Reference Books: We will be reading relevant chapters from reference books as well as journal and conference papers.
      

  • Main Reference Books:

    1. Ben Gold and Nelson Morgan (2000) Speech and Audio Signal Processing.

    　

  • Supplementary Reference Books:

    1. Marina Bosi and Richard E. Goldberg (2003) Introduction to Digital Audio Coding and Standards. This book focuses on audio coding.

    2. Anssi Klapuri and Manuel Davy (2006) Signal Processing Methods for Music Transcription.

    3. Mark Kahrs and Karlheinz Brandenburg (1998) Applications of Digital Signal Processing to Audio and Acoustics. This book focuses on signal processing aspect.

    4. Ken C. Pohlmann (1995) Principles of Digital Audio (3rd edition). This is a basic book about digital audio in general.

    5. Curtis Roads (1996) The Computer Music Tutorial. This book is about computer music. It is more suitable for people with some musical background.

• Assessment:

        continuous assessment           60%

           - participation                        5%

           - assignments                      15%

           - project                             40%

        final exam                            40%

Course Content:

Part I: Basics of Signal and Music Processing

• Introduction to Matlab
• Basic music theory for CS and EE students
• Music production and transcription
• Basics of digital signal processing (DSP)
• Basics of Audio and Speech Synthesis

Part II: Audio Perception and Compression

• Fundamental psychoacoustics
• Principles of audio compression
  • Case study: MP3/AAC
  • Case study: speech coding

Part III: Analysis of Speech and Music Signal

• Feature extraction
• HMM and GMM
  • Case study: speech recognition
  • Case study: speaker recognition

Part IV: Student Project Presentations