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Audio Signal Processing for Music Applications

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About This Course

Audio signal processing is an engineering field that focuses on the computational methods for intentionally altering sounds, methods that are used in many musical applications.

We have tried to put together a course that can be of interest and accessible to people coming from diverse backgrounds while going deep into several signal processing topics. We focus on the spectral processing techniques of relevance for the description and transformation of sounds, developing the basic theoretical and practical knowledge with which to analyze, synthesize, transform and describe audio signals in the context of music applications.

The course is based on open software and content. The demonstrations and programming exercises are done using Python under Ubuntu, and the references and materials for the course come from open online repositories. We are also distributing with open licenses the software and materials developed for the course.

Prerequisites

The course assumes some basic background in mathematics and signal processing. Also, since the assignments are done with the programming language Python, some software programming background in any language is most helpful.

FAQ

  • How much programming background is needed for the course?

All the assignments start from some existing Python code that the student will have to understand and modify. Some programming experience is necessary.

  • Do I need to buy a textbook for the course?

No, it is self-contained.

  • What resources will I need for this class?

All the materials and tools for the class are available online under open licences.

  • What is the coolest thing I'll learn if I take this class?

You will play around with sounds a lot, analysing them, transforming them, and making interesting new sounds.

  • Will I earn a Statement of Accomplishment for completing this course?

Yes you will earn an Statement of Accomplishment if you do well in the course.

Course Staff

Course Staff Image #1

Xavier Serra

Universitat Pompeu Fabra - Information and Communication Technologies

Course Staff Image #2

Julius O Smith, III

Stanford University - Professor of Music and (by courtesy) Electrical Engineering (CCRMA)

  1. Course Number

    E16
  2. Classes Start

    Sep 28, 2015
  3. Classes End

    Dec 17, 2015
  4. Estimated Effort

    8-10 hours / week
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