- NYU Music Technology News
- Summer and Fall 2013 Course Schedules May 25, 2013
- NYU Music Technology Open House 2013 May 25, 2013
- NYU Steinhardt's Interactive Art Series at Fredrick Loewe Theatre Feb 24, 2013
- NYU Music Technology at the Grammys Feb 18, 2013
- Whammy Jammy: 48-Hour Music & Audio-Centric Game Jam Nov 29, 2012
Welcome to MARL - NYU's Music and Audio Research Lab
About MARL @ NYU
Music and Audio Research Laboratory
MARL groups scholars from music theory, technology and composition, computer and information science, interactive media and media studies, to explore the intersection between music, computation and science. The objective is to combine techniques and methodologies from the arts, the humanities and the sciences to (a) understand and model human cognitive abilities in music, and (b) innovate the analysis, organization and creation of music.
The initiative aims to provide a forum that increases the visibility and contextualizes the work of NYU faculty, post-doctoral researchers, and doctoral, master and undergraduate students, interested in the intersection of music and science. By providing a space for discovery and discussion, MARL seeks to spark collaborations across departments and schools that have the potential to evolve into inter-disciplinary research, co-supervised student work, joint publications, grant writing, curricular development, event organization and artistic output.
Recent Events
Mark Ballora: The Sounds of Science
Mark Ballora will be discussing his work in sonification of scientific datasets that he has created for the educational science production Rhythms of the Universe
Psyche Loui: Neural and cognitive mechanisms for music: Insights from special populations
Music is ubiquitous around the world, but the source of musical ability is unknown. How do human beings come to know what they know about music? In this talk, I will review our recent research on...
Rebecca Friebrink: Real-time, Interactive Machine Learning for Music Composition and Performanc
Rebecca Friebrink shows how supervised learning offers a useful set of computational tools for many problems in computer music composition and performance.
Paul Lamere: Data Mining Music
Paul Lamere explores "how we can use music data mining for tasks such as automatic genre detection, song similarity for music recommendation, and data visualization for music exploration and discovery."
Projects
Research Projects @ MARL
Analyzing the Sequential Structure of Music Audio
This project aims at extending the understanding and usefulness of music data, through the research, development and application of computational approaches and tools. It advances an innovative and interdisciplinary program of research and education activities aimed at identifying the structures that define within- and between-song relationships in western tonal music; their applications to retrieval, visualization, music analysis and creation; and the dissemination of the knowledge base that makes these developments possible.
Improving Access to Digital Music through Content-based Analysis
This project is a collaboration between MARL and NYU Library Services, concerned with the research and development of content-based approaches to the automatic organization of, access to and interaction with digital music archives.
SIPLCA Segmentation
This package contains the implementation of the algorithm for identifying repeated harmonic patterns in music and structure segmentation. It is primarily written in Python but calls Matlab for feature extraction and performance evaluation.
