< Back to Search

ENGR 100.430:  Music Signal Processing (ECE)


Philip Derbesy (TechComm),

Jeff Fessler (EECS, BME)

Winter Term

Student looking up from project with solar panel in front
Course Description:

In this section you will learn data processing methods by analyzing music signals the way an engineer would analyze other data from sensors. Motivated by music signals, you will learn the basics of Fourier signal analysis and synthesis – a tool used in many engineering fields, including Biomedical, Environmental, Electrical and Computer Engineering as well as Computer Science. You will work individually on computer-based labs related to musical signals, and you will work in teams on projects including music synthesizers and transcribers and a touch-tone phone signals decoder. Your teams will also finish the course by applying the signal processing techniques you have learned to an open-ended design project such as an advanced music synthesizer or a pitch tracker or real-time music transposition, just to name a few of the creative past projects that student teams have devised. Like all sections of 100, technical communications methods are taught and used throughout.

Absolutely no previous knowledge of music is necessary, though we will try to form teams where at least one team member has some basic music knowledge.

Because this is a Winter section of the course, we will assume that all students in this section have had a prior programming course, such as ENGR 101, and are familiar with concepts like variable types (vectors, matrices, strings), control flow (conditionals, loops), functions, I/O, etc. The labs and homework and projects will most likely use the Julia language (a newer open-source language that combines the best of Matlab and Python). No prior experience with Julia is needed.

Please note: this is NOT a composition or performance arts technology course.

Many of the concepts in the course are relevant to the field of machine learning because the challenge of training a computer to recognize musical pitches is analogous to the challenge of learning how to perform other classification problems like speech recognition.

Term Project

Design, build and test your own music signal processing software application, incorporating digital music synthesis and/or musical pitch recognition.

Drawing of a robot holding sign that says “I love ENGR 100” on whiteboard
Two music signal graphs
Black toolbox filled with colorful parts on table in front of classroom