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.
MARL is pleased to welcome Dr. Michael Hawley from the MIT Media Laboratory. An accomplished musician as well as a leading thinker on the uses and development of technology, Dr. Hawley will address both fields in a lecture entitled "Bits 'n Pieces."
Yahoo! Research's Dr. Malcolm Slanley will be visiting MARL this Tuesday to give a talk about current issues and practices pertaining to digital media on the web.
Research Projects @ MARL
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.
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.
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.
