Thumbnail
Access Restriction
Subscribed

Author Wessel, David ♦ Donzé, Alexandre ♦ Valle, Rafael ♦ Freed, Adrian ♦ Akkaya, Ilge ♦ Fremont, Daniel J. ♦ Seshia, Sanjit A.
Source ACM Digital Library
Content type Text
Publisher Association for Computing Machinery (ACM)
File Format PDF
Language English
Subject Keyword Machine learning ♦ Specification mining ♦ Formal methods ♦ Control improvisation
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.
Description Affiliation: UC Berkeley, Berkeley, CA (Donzé, Alexandre; Fremont, Daniel J.; Akkaya, Ilge; Seshia, Sanjit A.; Wessel, David) || UC Berkeley, CNMAT, Berkeley, CA (Valle, Rafael; Freed, Adrian)
Age Range 18 to 22 years ♦ above 22 year
Educational Use Research
Education Level UG and PG
Learning Resource Type Article
Publisher Date 2008-03-01
Publisher Place New York
Journal Computers in Entertainment (CIE) (CIE)
Volume Number 14
Issue Number 3
Page Count 20
Starting Page 1
Ending Page 20


Open content in new tab

   Open content in new tab
Source: ACM Digital Library