📋 Tender Overview
Exploring Musical Possibilities Via Machine Simulation
Computer Simulation For Exploring Musical Possibilities
In His Famous Lectures At Harvard University In 1973, Leonard Bernstein Analysed The Process That Led To What He Called The 20Th Century Crisis Of Music. The Eu-Funded Whither Music? Project, Named After The Motto Of These Lectures, Will Create Computer Models Of Music Composition, Performance, And Listening That Can Be Used To Explore Musical Developments And Alternatives, And Support Active Exploration Of The Space Of Musical Possibilities. At The Heart Of This Will Be A New Approach To Structured Music Modelling, Using Ai, Machine Learning And Probabilistic Modelling Methods To Obtain Stylistically Faithful, Tightly Controllable And Transparent Generative Models That Permit Musically Meaningful Simulations And Contribute To Music Information Research.
Funded Under: Excellent Science - European Research Council (Erc)
Total Cost: € 2 500 000,00
Eu Contribution: € 2 500 000,00
Coordinated By: Universitat Linz
Austria
Objective
"""Whither Music?"" was the motto of Leonard Bernstein's 1973 lectures at Harvard, where he analysed the (inevitable?) process that led to what he called the 20th Century Crisis of Music: the gradual decline of tonality, driven by a takeover of tonal ambiguity in the late 19th and early 20th centuries, eventually leading to complete abandonment of tonality in Schönberg's dodecaphony.
WHITHER MUSIC? is a project that aims to establish model-based computer simulation (via methods of Artificial Intelligence, Machine Learning and probabilistic modelling) as a viable methodology for asking questions about musical developments, possibilities and alternatives - for musicology, for didactic purposes, for creative music exploration scenarios. Computer simulation here means the design of predictive or generative computational models of music (of certain styles), learned from large corpora, and their purposeful and skilful application to answer, e.g. ""what if"" questions, make testable predictions, or generate musical material for further analysis, musicological or aesthetic.
