## MUSIC 390: Practicum Internship

On-the-job training under the guidance of experienced, on-site supervisors. Meets the requirements for curricular practical training for students on F-1 visas. Students submit a concise report detailing work activities, problems worked on, and key results. May be repeated for credit. Prerequisite: qualified offer of employment and consent of adviser.

Terms: Aut, Win, Spr, Sum
| Units: 1
| Repeatable for credit

Instructors:
Abel, J. (PI)
;
Applebaum, M. (PI)
;
Barth, G. (PI)
...
more instructors for MUSIC 390 »

Instructors:
Abel, J. (PI)
;
Applebaum, M. (PI)
;
Barth, G. (PI)
;
Berger, J. (PI)
;
Berger, K. (PI)
;
Cai, J. (PI)
;
Chafe, C. (PI)
;
Ferneyhough, B. (PI)
;
Fujioka, T. (PI)
;
Grey, T. (PI)
;
Hadlock, H. (PI)
;
Hinton, S. (PI)
;
Kapuscinski, J. (PI)
;
Mahrt, W. (PI)
;
Rodin, J. (PI)
;
Sano, S. (PI)
;
Smith, J. (PI)
;
Ulman, E. (PI)
;
Wang, G. (PI)

## MUSIC 399: D.M.A. Final Project

May be repeated for credit a total of 5 times.

Terms: Aut, Win, Spr, Sum
| Units: 1-10
| Repeatable for credit

Instructors:
Alessandrini, P. (PI)
;
Applebaum, M. (PI)
;
Barth, G. (PI)
...
more instructors for MUSIC 399 »

Instructors:
Alessandrini, P. (PI)
;
Applebaum, M. (PI)
;
Barth, G. (PI)
;
Berger, J. (PI)
;
Berger, K. (PI)
;
Chafe, C. (PI)
;
DeMarinis, P. (PI)
;
Ferneyhough, B. (PI)
;
Fujioka, T. (PI)
;
Grey, T. (PI)
;
Hadlock, H. (PI)
;
Hinton, S. (PI)
;
Kapuscinski, J. (PI)
;
Mahrt, W. (PI)
;
Myers, H. (PI)
;
Rodin, J. (PI)
;
Rose, F. (PI)
;
Sano, S. (PI)
;
Smith, J. (PI)
;
Ulman, E. (PI)
;
Wang, G. (PI)

## MUSIC 420A: Signal Processing Models in Musical Acoustics

Computational methods in musical sound synthesis and digital audio effects based on acoustic physical models. Topics: mass-spring-dashpot systems; electric circuit analogies; finite difference schemes; state-space models and the modal representation; impedance; ports; acoustic simulation using delay lines, digital filters, and nonlinear elements; interpolation and sampling-rate conversion; delay effects; wave digital filters; real-time computational models for musical instruments and effects, both acoustic and electronic. See
http://ccrma.stanford.edu/courses/420/. Prerequisites:
MUSIC 320A and
MUSIC 320B or equivalent;
PHYSICS 21 or equivalent course applying Newton's laws of motion; and
CS 106B or equivalent programming in C and C++.

Terms: Win
| Units: 3-4

Instructors:
Smith, J. (PI)
;
Rau, M. (TA)

## MUSIC 421A: Time-Frequency Audio Signal Processing

Spectrum analysis and signal processing using Fast Fourier Transforms (FFTs) with emphasis on audio applications. Topics: Fourier theorems; FFT windows; spectrum analysis; spectrograms; sinusoidal modeling; spectral modeling synthesis; FFT convolution; FIR filter design and system identification; overlap-add and filter-bank-summation methods for short-time Fourier analysis, modification, and resynthesis. See
http://ccrma.stanford.edu/courses/421/. Prerequisites:
Music 320A and
Music 320B or equivalent background in spectrum analysis and linear systems.

Terms: Spr
| Units: 3-4

Instructors:
Smith, J. (PI)
;
Das, O. (TA)

## MUSIC 422: Perceptual Audio Coding

History and basic principles: development of psychoacoustics-based data-compression techniques; perceptual-audio-coder applications (radio, television, film, multimedia/internet audio, DVD, EMD). In-class demonstrations: state-of-the-art audio coder implementations (such as AC-3, MPEG) at varying data rates; programming simple coders. Topics: audio signals representation; quantization; time to frequency mapping; introduction to psychoacoustics; bit allocation and basic building blocks of an audio codec; perceptual audio codecs evaluation; overview of MPEG-1, 2, 4 audio coding and other coding standards (such asAC-3). Prerequisites: knowledge of digital audio principles, familiarity with C programming. Recommended: 320,
EE 261. See
http://ccrma.stanford.edu/.

Terms: Win
| Units: 3

Instructors:
Bosi, M. (PI)
;
Oshiro, S. (TA)

## MUSIC 423: Graduate Research in Music Technology

Research discussion, development, and presentation by graduate students, visiting scholars, and CCRMA faculty in the areas of music and/or audio technology. Permission of instructor required. See
http://ccrma.stanford.edu/courses/423/ for latest information. May be repeated for credit.

Terms: Aut, Win, Spr
| Units: 1-10
| Repeatable for credit

Instructors:
Abel, J. (PI)
;
Berners, D. (PI)
;
Lopez-Lezcano, F. (PI)
...
more instructors for MUSIC 423 »

Instructors:
Abel, J. (PI)
;
Berners, D. (PI)
;
Lopez-Lezcano, F. (PI)
;
Mysore, G. (PI)
;
Smith, J. (PI)

## MUSIC 424: Signal Processing Techniques for Digital Audio Effects

Techniques for dynamic range compression, reverberation, equalization and filtering, panning and spatialization, digital emulation of analog processors, and implementation of time-varying effects. Single-band and multiband compressors, limiters, noise gates, de-essers, convolutional reverberators, parametric and linear-phase equalizers, wah-wah and envelope-following filters, and the Leslie. Students develop effects algorithms of their own design in labs. Prerequisites: digital signal processing, sampling theorem, digital filtering, and the Fourier transform at the level of 320 or
EE 261; Matlab and modest C programming experience. Recommended: 420 or
EE 264; audio effects in mixing and mastering at the level of 192.

Terms: Spr
| Units: 3-4

## MUSIC 451A: Basics in Auditory and Music Neuroscience

Understanding basic concepts and techniques in cognitive neuroscience using electroencephalography (EEG) specific to auditory perception and music cognition via seminar and laboratory exercise work. Acquiring and practicing skills in experimental design, data analysis, and interpretation, writing for scientific reports and research proposals, and giving a critical review of others' scientific work. Seminar discusses related literature in neuroanatomy, neurophysiology, psychology, and neuroimaging. Laboratory focuses on electroencephalography (EEG) techniques, classic paradigms for recording evoked response, and associated data analysis methods.

Terms: Aut
| Units: 2-5

Instructors:
Fujioka, T. (PI)

## MUSIC 451B: Neuroscience of Auditory Perception and Music Cognition II: Neural Oscillations

Building on 451A, this course will review basic knowledge and EEG techniques of neural oscillations related to auditory perception and music cognition via seminar and laboratory work. Through reviewing and replicating findings using classic and recent paradigms, the laboratory exercises offer multiple ways to understand how to design experiments and analyze data to observe neural oscillatory activities in different frequency bands, then interpret their functional significance in sensorimotor processing, attention, and social interaction ¿ important aspects of music listening and performance. Seminar discusses literature in neurophysiology, neuropsychology, and brain-computer interface. Prerequisite:
Music 451A or permission of instructor.

Terms: Win
| Units: 2-5

Instructors:
Fujioka, T. (PI)

## MUSIC 801: TGR Project

Terms: Aut, Win, Spr, Sum
| Units: 0
| Repeatable for credit

Instructors:
Alessandrini, P. (PI)
;
Applebaum, M. (PI)
;
Barth, G. (PI)
...
more instructors for MUSIC 801 »

Instructors:
Alessandrini, P. (PI)
;
Applebaum, M. (PI)
;
Barth, G. (PI)
;
Berger, J. (PI)
;
Berger, K. (PI)
;
Cai, J. (PI)
;
Chafe, C. (PI)
;
DeMarinis, P. (PI)
;
Ferneyhough, B. (PI)
;
Fujioka, T. (PI)
;
Gill, D. (PI)
;
Grey, T. (PI)
;
Hadlock, H. (PI)
;
Hinton, S. (PI)
;
Kapuscinski, J. (PI)
;
Kronengold, C. (PI)
;
Mahrt, W. (PI)
;
Myers, H. (PI)
;
Phillips, P. (PI)
;
Rodin, J. (PI)
;
Sano, S. (PI)
;
Smith, J. (PI)
;
Ulman, E. (PI)
;
Wang, G. (PI)