Specification Mining for Machine Improvisation with Formal Specifications

Author:

Valle Rafael1,Donzé Alexandre2,Fremont Daniel J.2,Akkaya Ilge2,Seshia Sanjit A.2,Freed Adrian1,Wessel David2

Affiliation:

1. UC Berkeley, CNMAT, Berkeley, CA

2. UC Berkeley, Berkeley, CA

Abstract

We address the problem of mining musical specifications from a training set of songs and using these specifications in a machine improvisation system capable of generating improvisations imitating a given style of music. Our inspiration comes from control improvisation , which combines learning and synthesis from formal specifications. We mine specifications from symbolic musical data with musical and general usage patterns. We use the mined specifications to ensure that an improvised musical sequence satisfies desirable properties given a harmonic context and phrase structure. We present a specification mining strategy based on pattern graphs and apply it to the problem of supervising the improvisation of blues songs. We present an analysis of the mined specifications and compare the results of improvisations generated with and without specifications.

Publisher

Association for Computing Machinery (ACM)

Subject

Computer Science Applications

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