research-article

Specification Mining for Machine Improvisation with Formal Specifications

Authors:

Alexandre Donzé,

Daniel J. Fremont,

Sanjit A. Seshia,

David WesselAuthors Info & Claims

Computers in Entertainment (CIE), Volume 14, Issue 3

Article No.: 6, Pages 1 - 20

https://doi.org/10.1145/2967504

Published: 31 December 2016 Publication History

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.

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Cited By

Aziz B(2023)Detecting Data Anomalies from Their Formal Specifications: A Case Study in IoT SystemsElectronics10.3390/electronics1203063012:3(630)Online publication date: 27-Jan-2023
https://doi.org/10.3390/electronics12030630
Carsault TNika JEsling PAssayag G(2021)Combining Real-Time Extraction and Prediction of Musical Chord Progressions for Creative ApplicationsElectronics10.3390/electronics1021263410:21(2634)Online publication date: 28-Oct-2021
https://doi.org/10.3390/electronics10212634
Tatar KPasquier P(2018)Musical agents: A typology and state of the art towards Musical MetacreationJournal of New Music Research10.1080/09298215.2018.1511736(1-50)Online publication date: 10-Sep-2018
https://doi.org/10.1080/09298215.2018.1511736

Index Terms

Specification Mining for Machine Improvisation with Formal Specifications
1. Computing methodologies
  1. Machine learning
  2. Modeling and simulation
2. Theory of computation
  1. Formal languages and automata theory

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Published In

cover image Computers in Entertainment

Computers in Entertainment Volume 14, Issue 3

Special Issue on Musical Metacreation, Part II

Fall 2016

109 pages

EISSN:1544-3574

DOI:10.1145/3023312

Issue’s Table of Contents

Copyright © 2016 ACM.

Permission to make digital or hard copies of all or part of this work for personal or classroom use is granted without fee provided that copies are not made or distributed for profit or commercial advantage and that copies bear this notice and the full citation on the first page. Copyrights for components of this work owned by others than the author(s) must be honored. Abstracting with credit is permitted. To copy otherwise, or republish, to post on servers or to redistribute to lists, requires prior specific permission and/or a fee. Request permissions from [email protected].

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Association for Computing Machinery

New York, NY, United States

Publication History

Accepted: 01 January 2017

Revised: 01 January 2017

Published: 31 December 2016

Received: 01 December 2016

Published in CIE Volume 14, Issue 3

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Citations

Cited By

Aziz B(2023)Detecting Data Anomalies from Their Formal Specifications: A Case Study in IoT SystemsElectronics10.3390/electronics1203063012:3(630)Online publication date: 27-Jan-2023
https://doi.org/10.3390/electronics12030630
Carsault TNika JEsling PAssayag G(2021)Combining Real-Time Extraction and Prediction of Musical Chord Progressions for Creative ApplicationsElectronics10.3390/electronics1021263410:21(2634)Online publication date: 28-Oct-2021
https://doi.org/10.3390/electronics10212634
Tatar KPasquier P(2018)Musical agents: A typology and state of the art towards Musical MetacreationJournal of New Music Research10.1080/09298215.2018.1511736(1-50)Online publication date: 10-Sep-2018
https://doi.org/10.1080/09298215.2018.1511736

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