This course deals with various music analysis and processing problems that use sampled audio as the primary data representation. We discuss, but do not emphasize, digital signal processing including filtering and its relationship to Fourier techniques. We will focus on applications including score following (online and offline), automatic music transcription and annotation from audio, musical accompaniment systems, as well as some useful audio effects. The class is open to all graduate students, but students should be prepared for some mathematics, computer science and statistics.
Instructor Christopher Raphael (email@example.com) Class Hours Lindley Hall 008, Time MW 9:30-10:45 Office Hours Info West 315, Time TR 4:00 - 5:00 or by appointment. Syllabus Syllabus Course Notes Course_Notes R Code Samples R Code Samples
|Homework 2||Due: 9/19 in class||Solutions|
|Homework 3||Due: 10/05 in class||Solutions|
|Homework 4||Due: 10/17 in class||Solutions|
|Homework 5||Due: 10/31 in class|
 Syllabus  R Tutorial  How to get started with sound in R  How to use tuneR package in R to deal with sound waves
 Audio quality - a demonstration about the role of sampling rate and bit depth in sound quality (excerpts from Mozart oboe concerto).
 Sound effects
 Sound samples - may be used as raw materials for homework assignments.
 More sound effects
 Musical pitch from Wikipedia  A comprehensive introduction to music theory  "To begin your journey to music..."  A digital audio primer  A music pitches table (from I545)  A notation of the song Amazing Grace (4 parallel voices)  Wikipedia page about DFT - Discrete Fourier Transform  A more comprehensive book on Discrete Fourier Transform