Result: MUSICNTWRK: data tools for music theory, analysis and composition
Title:
MUSICNTWRK: data tools for music theory, analysis and composition
Authors:
Contributors:
Perception, Représentations, Image, Son, Musique (PRISM), Aix Marseille Université (AMU)-Ecole supérieure d'Art d'Aix en Provence (ESA AIX)-Centre National de la Recherche Scientifique (CNRS), Institut d'Etudes Avancées (IMéRA), Aix Marseille Université (AMU), University of North Texas (UNT)
Source:
Computer Music Multidisciplinary Research 2019, Oct 2019, Marseille, France
Publisher Information:
CCSD, 2019.
Publication Year:
2019
Collection:
collection:SHS
collection:CNRS
collection:UNIV-AMU
collection:AO-MUSICOLOGIE
collection:PRISM-AMU
collection:CNRS
collection:UNIV-AMU
collection:AO-MUSICOLOGIE
collection:PRISM-AMU
Subject Terms:
[SPI.ACOU]Engineering Sciences [physics], Acoustics [physics.class-ph], [STAT.CO]Statistics [stat], Computation [stat.CO], [SHS.MUSIQ]Humanities and Social Sciences, Musicology and performing arts, [INFO.INFO-DS]Computer Science [cs], Data Structures and Algorithms [cs.DS], [INFO.INFO-SD]Computer Science [cs], Sound [cs.SD]
Subject Geographic:
Original Identifier:
HAL: hal-02271492
Document Type:
Conference
conferenceObject<br />Conference papers
Language:
English
Access URL:
Rights:
info:eu-repo/semantics/OpenAccess
Accession Number:
edshal.hal.02271492v1
Database:
HAL
Further Information
We present the API for MUSICNTWRK, a python library for pitch class set and rhythmic sequences classification and manipulation, the generation of networks in generalized music and sound spaces, deep learning algorithms for timbre recognition, and the sonification of arbitrary data. The software is freely available under GPL 3.0 and can be downloaded at www.musicntwrk.com.