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Music 264

Course Title: 
Musical Engagement
Instructor: 
Jeffrey Christopher Smith
Course Description: 
Using correlation analysis and big data to identify and predict musical behaviors.  According to a recent Nielsen study, Music 360 2014, 93% of the country's population listens to music, spending more than 25 hours each week tuning into their favorite songs.  In fact more people actively choose to listen to music than watch television.  Why?   This course will use data and analytics to explore why people engage in music.  The course will be one part lab, one part seminar, meeting once a week for two hours.  Students will learn to apply correlation analysis to a vast corpus of actual performance data using the latest analytics and query tools, developing insights into what motivates the musical preferences and behaviors of both performers and listeners. 
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Winter Quarter 2023

101 Introduction to Creating Electronic Sound
158/258D Musical Acoustics
220B Compositional Algorithms, Psychoacoustics, and Computational Music
222 Sound in Space
250C Interaction - Intermedia - Immersion
251 Psychophysics and Music Cognition
253 Symbolic Musical Information
264 Musical Engagement
285 Intermedia Lab
319 Research Seminar on Computational Models of Sound
320B Introduction to Audio Signal Processing Part II: Digital Filters
356 Music and AI
422 Perceptual Audio Coding
451B Neuroscience of Auditory Perception and Music Cognition II: Neural Oscillations

 

 

 

   

CCRMA
Department of Music
Stanford University
Stanford, CA 94305-8180 USA
tel: (650) 723-4971
fax: (650) 723-8468
info@ccrma.stanford.edu

 
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