351 - 360 of 384 results for: MUSIC

For graduate students. Provides an introduction to major frameworks for social, cultural, and historical analysis, especially in their relevance to ethnomusicology and historical musicology. Readings will consist of both foundational texts in a variety of disciplines and their application in scholarship on music and sound.

Directed reading and research. May be repeated for credit a total of 14 times.

This course will introduce students to the field of Sound Studies (methodology, vocabulary, main claims) with a focus on the various sonic articulations of human-machine interactions in literature. The world of fiction as a sonic machine that articulates noise, sound, music, voice, or silence offers an excellent archive. We will read works by Nathaniel Hawthorne, Eça de Queirós, Mark Twain, the Italian Futurists, Zora Neale Hurston, and Luigi Pirandello. Secondary readings will include seminal contributions by R. Murray Schafer (the soundscape), Leo Marx (U.S. industrialization), Jacques Attali (noise and music), Mladen Dolar (philosophy and voice), Adriana Cavarero (gender, voice, and the body), Jonathan Crary (culture, aesthetics, and perception), Friedrich Kittler (media), and Daphne Brooks (black feminist sound).

Introduction to analysis, examining diverse examples in part chosen from, otherwise supplementing and illuminating, the graduate composers' qualifying exam list; consideration of aesthetic premises and motivations, and of implications for contemporary compositional practice.

For graduate students. Topics vary each quarter. May be repeated for credit a total of 8 times.

All aspects of auditory perception, often with emphasis on computational models. Topics: music perception, signal processing, auditory models, pitch perception, speech, binaural hearing, auditory scene analysis, basic psychoacoustics, and neurophysiology. See http://ccrma.stanford.edu/courses/. May be repeated for credit a total of 14 times.

A first-course in signal processing with applications in computer music and audio for students comfortable with high-school algebra, calculus, complex variables, and beginning linear algebra. The lectures cover fundamentals of audio signal processing such as sinusoids, spectra, Fourier transforms, Laplace transform, z transform, linear time-invariant filters, digitizing systems, transfer-function analysis, and basic Fourier analysis in the continuous and discrete-time cases. Python is used for in-class demonstrations and homework/lab assignments. The labs focus on practical applications of the theory, with emphasis on working with waveforms and spectra, ''getting sound'', and developing proficiency in the Python language. See http://ccrma.stanford.edu/courses/320/.

Course focuses on developing an audio signal-processing plugin or stand-alone application in C++. Prior experience is assumed with programming in Matlab/Octave and C/C++, and signal processing theory on the level of Music 320. Class time is devoted to presenting use of the Faust programming language for generating C++, the JUCE framework for creating audio plugins or stand-alone applications, related theory and projects, project progress reports, and project final presentations.

A tutorial section aimed at students who would like a review of prerequisite material for the Center for Computer Research in Music and Acoustics (CCRMA) audio signal processing (ASP) series of classes. The tutorial can be taken prior to or concurrently with Music 320. Sessions will be structured towards the specific needs of attendees.