@article {402, title = {Specification Mining For Machine Improvisation With Formal Specifications}, journal = {ACM : Computers in Entertainment (Musical Metacreation)}, volume = {14 Issue 3}, year = {2016}, month = {2016}, 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 learn from symbolic musical data specifications based on 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 musical form. We present a specification mining strategy based on finite state automata and Markov chains, 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 supervised and unsupervised improvisations.}, doi = {10.1145/2967504}, url = {https://dl.acm.org/citation.cfm?doid=3023312.2967504}, attachments = {http://www.adrianfreed.com/sites/default/files/msm16.pdf}, author = {Valle, Rafael and Donz{\'e}, Alexandre and Fremont, Daniel and Akkaya, Ilge and Seshia, Sanjit and Freed, Adrian and Wessel, David} }