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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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Fall Courses at CCRMA

Music 101 Introduction to Creating Electronic Sounds
Music 192A Foundations in Sound Recording Technology
Music 201 CCRMA Colloquium
Music 220A Foundations of Computer-Generated Sound
Music 223A Composing Electronic Sound Poetry
Music 256A Music, Computing, and Design I: Software Paradigms for Computer Music
Music 319 Research Seminar on Computational Models of Sound Perception
Music 320 Introduction to Audio Signal Processing
Music 351A Research Seminar in Music Perception and Cognition I
Music 423 Graduate Research in Music Technology
Music 451A Auditory EEG Research I

 

 

 

   

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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