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Audio Signal Processing for Music Applications

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Next session opens March 27th.

About this course

In this course you will learn about audio signal processing methodologies that are specific for music and of use in real applications. 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.

Who is this class for

This course is primary aimed at advanced undergraduate or master students, along with professionals, interested in signal processing, programming and music.

Created by: Universitat Pompeu Fabra of Barcelona, Stanford University

FAQs

Can I take this course for free?
Yes, there is no fee in this course. You can follow the course, do the assignments, and obtain a final grade completely for free.

Can I pay to get a Course Certificate?
No, we do not offer this option.

What resources will I need for this class?
All the materials and tools for the class are available online under open licences.

Do I need to buy a textbook for the course?
No, it is self-contained.

How much programming background is needed for the course?
All the assignments start from some existing Python code that the student have to understand and modify. Some programming experience is necessary.

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.

Instructors

Xavier Serra

Associate Professor, Dept. of Information and Communication Technologies, UPF

Julius Smith

Professor of Music and (by courtesy) Electrical Engineering, CCRMA


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