Stanford University
Coursera
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assignment Level : Intermediate
chat_bubble_outline Language : English
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Key information

credit_card Free access
verified_user Fee-based Certificate
timer 80 hours in total

About the content

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.

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Syllabus

Week 1: Introduction; basic mathematics 
Week 2: Discrete Fourier transform
Week 3: Fourier transform properties
Week 4: Short-time Fourier transform
Week 5: Sinusoidal model
Week 6: Harmonic model
Week 7: Sinusoidal plus residual modeling
Week 8: Sound transformations
Week 9: Sound/music description
Week 10: Concluding topics; beyond audio signal processing
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Intructors

Xavier Serra
Full Professor
Dept. of Information and Communication Technologies, UPF

Prof Julius O Smith, III
Professor of Music and (by courtesy) Electrical Engineering
CCRMA

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Content designer

The Leland Stanford Junior University, commonly referred to as Stanford University or Stanford, is an American private research university located in Stanford, California on an 8,180-acre (3,310 ha) campus near Palo Alto, California, United States.
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Platform

Coursera is a digital company offering massive open online course founded by computer teachers Andrew Ng and Daphne Koller Stanford University, located in Mountain View, California. 

Coursera works with top universities and organizations to make some of their courses available online, and offers courses in many subjects, including: physics, engineering, humanities, medicine, biology, social sciences, mathematics, business, computer science, digital marketing, data science, and other subjects.

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