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Sifting Sound


Term:

Spring

Department:

MAS: Media Arts and Sciences

Faculty Supervisor:

Tod Machover

Faculty email:

tod@media.mit.edu

Apply by:

As soon as possible

Contact:

Sizi Chen: sizichen@media.mit.edu

Project Description

This project is about computationally assembling, analyzing, organizing, and combining large unstructured audio datasets to create new expressive musical forms. Role specifics will depend on student experience and interest, but involves opportunities to learn about frontend and backend development, and audio and data analysis.

Pre-requisites

Software development experience. Some Python and/or Javascript programming experience, and a willingness to quickly learn new tools and techniques. Any background in music or audio is great to have. Also helpful to have experience or interest in any of the following: C/C++, SQL, React, Backend development, UI/UX, data and ML stack (NumPy, Scikit-learn, Keras, etc.), signal processing, creating or consuming APIs, web audio, data visualization.