Digital audio processing

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Introduction[edit | edit source]

This course introduces students to digital signal processing in the context of audio signals.

Prerequisites[edit | edit source]

Assignments should be completed using one of the programming languages listed below in the Tools section, and therefore requires a basic understanding of the syntax of at least one of the listed languages. If you are not sure which one to use, use MATLAB if you have it, and Python if you don't own MATLAB.

Tools[edit | edit source]

Lessons[edit | edit source]

Lesson Name Description
Lab 00: Setting up your environment A quick guide on setting up all of your tools so that you can best follow this course
Lab 01: Analyzing digital audio Before getting into the modification of signals, we must first understand more about the signals themselves, and some of the pros and cons of the digital realm
Lab 02: Denoising and source separation An overview of noise and a few different ways to remove/reduce it
Lab 03: Speech processing An exploration of converting audio into text and vice versa
Lab 04: Music Information Retrieval An exploration of analyzing the musical characteristics of an audio signal
Lab 05: Audio compression An exploration of different ways to compress digital audio, prefaced by a cursory explanation of compression as a whole
Lab 06: Array processing Things like beamforming and acoustic cameras; may be moved to a second class
Lab 07: Machine learning in audio The name says it all; may be moved to a second class

See also[edit | edit source]

Type classification: this resource is a course.
Educational level: this is a tertiary (university) resource.
Subject classification: this is an engineering resource.
Completion status: this resource is just getting off the ground. Please feel welcome to help!