Cognitive music engine using unsupervised learning

Patent metadata

Field	Value
Publication number	US-2017206875-A1
Application number	US-201715473543-A
Country	US
Kind code	A1
Filing date	Mar 29, 2017
Priority date	Oct 12, 2015
Publication date	Jul 20, 2017
Grant date	—

Abstract

A method for generating a musical composition based on user input is described. A first set of musical characteristics from a first input musical piece is received as an input vector. The first set of musical characteristics is perturbed to create a perturbed input vector as input in a first set of nodes in a first visible layer of an unsupervised neural net. The unsupervised neural net comprised of a plurality of computing layers, each computing layer composed of a respective set of nodes. The unsupervised neural net is operated to calculate an output vector from a higher level hidden layer in the unsupervised neural net. The output vector is used to create an output musical piece.

First claim

Having described our invention, what we now claim is as follows:

1 . A method for generating a musical composition, comprising:
receiving a first set of musical characteristics from a first input musical piece as an input vector; perturbing the first set of musical characteristics to create a perturbed input vector as input in a first set of nodes in a first visible layer of an unsupervised neural net, the unsupervised neural net comprised of a plurality of computing layers, each computing layer composed of a respective set of nodes; operating the unsupervised neural net to calculate an output vector from a higher level hidden layer in the unsupervised neural net; and using the output vector to create an output musical piece.

2 . The method as recited in claim 1 , further comprising receiving an expressed user intent, wherein the perturbing is performed by inserting values into a set of perturbation nodes in the first visible layer according to a rule selected according to the expressed user intent.

3 . The method as recited in claim 2 , wherein in response to an expressed user intent, pitches having an interval from a note in the input piece are inserted into the set of perturbation nodes in the first visible layer.

4 . The method as recited in claim 2 , further comprising:
receiving a user input indicating a degree of similarity for the output musical piece to the first musical input piece; and determining a magnitude of the values inserted into the set of perturbation nodes according to the degree of similarity.

5 . The method as recited in claim 2 , wherein the rule directs a selection of a set of pitches from a key signature associated with the user intent.

6 . The method as recited in claim 2 , wherein the perturbing includes inserting random values into the set of perturbation nodes in the first visible layer.

7 . The method as recited in claim 1 , further comprising:
receiving a second set of musical characteristics from a second input musical piece; receiving user input that the output musical piece should more closely resemble the first input musical piece than the second input musical piece; providing the second set of musical characteristics together with the first set of musical characteristics as the input vector; and wherein the perturbing includes changing the perturbed vector so that the first input musical piece has a greater effect on the output musical piece than the second input musical piece by including the first set of musical characteristics in more nodes of the first set of nodes in the first visible layer of the unsupervised neural net than the second set of musical characteristics.

8 . An apparatus, comprising:
a processor; computer memory holding computer program instructions executed by the processor for generating a musical composition, the computer program instructions comprising:
program code operative to receive a first set of musical characteristics from a first input musical piece as an input vector;
program code operative to perturb the first set of musical characteristics to create a perturbed input vector as input in a first set of nodes in a first visible layer of an unsupervised neural net, the unsupervised neural net comprised of a plurality of computing layers, each computing layer composed of a respective set of nodes;
program code operative to operate the unsupervised neural net to calculate an output vector from a higher level hidden layer in the unsupervised neural net; and
program code operative to use the output vector to create an output musical piece.

9 . The apparatus as recited in claim 8 , wherein the computer program instructions further comprise:
program code operative to receive an expressed user intent; and program code operative to perform the perturbing by inserting values into a set of perturbation nodes in the first visible layer according to a rule selected according to the expressed user intent.

10 . The apparatus as recited in claim 9 , wherein the computer program instructions further comprise program code operative to insert pitches having an interval from a note in the input piece are inserted into the set of perturbation nodes in the first visible layer in response to an expressed user intent.

11 . The apparatus as recited in claim 9 , wherein the computer program instructions further comprise:
program code operative to receive a user input indicating a degree of similarity for the output musical piece to the first musical input piece; and program code operative to determine a magnitude of the values inserted into the set of perturbation nodes according to the degree of similarity.

12 . The apparatus as recited in claim 9 , wherein the computer program instructions further comprise program code operative to direct a selection of rule to insert a set of pitches from a key signature associated with the user intent into the first visible layer.

13 . The apparatus as recited in claim 8 , wherein the computer program instructions further comprise:
program code operative to receive a second set of musical characteristics from a second input musical piece; program code operative to receive user input that the output musical piece should more closely resemble the first input musical piece than the second input musical piece; program code operative to provide the second set of musical characteristics together with the first set of musical characteristics as the input vector; and program code operative to change the perturbed vector so that the first input musical piece has a greater effect on the output musical piece than the second input musical piece by including the first set of musical characteristics in more nodes of the first set of nodes in the first visible layer of the unsupervised neural net than the second set of musical characteristics.

14 . A computer program product in a non-transitory computer readable medium for use in a data processing system, the computer program product holding computer program instructions which, when executed by the data processing system, for generating a musical composition, the computer program instructions comprising:
program code operative to receive a first set of musical characteristics from a first input musical piece as an input vector; program code operative to perturb the first set of musical characteristics to create a perturbed input vector as input in a first set of nodes in a first visible layer of an unsupervised neural net, the unsupervised neural net comprised of a plurality of computing layers, each computing layer composed of a respective set of nodes; program code operative to operate the unsupervised neural net to calculate an output vector from a higher level hidden layer in the unsupervised neural net; and program code operative to use the output vector to create an output musical piece.

15 . The computer program product as recited in claim 14 , wherein the computer program instructions further comprise:
program code operative to receive an expressed user intent; and program code operative to perform the perturbing by inserting values into a set of perturbation nodes in the first visible layer according to a rule selected according to the expressed user intent.

16 . The computer program product as recited in claim 15 , wherein the computer program instructions further comprise program code operative to insert pitches having an interval from a note in the input piece are inserted into the set of perturbation nodes in the first visible layer in response to an expressed user intent.

17 . T

Assignees

• IBM

Inventors

• Hwang Inseok
• Kuang Jente B
• Mukundan Janani

Classifications

• G06N3/047

  Probabilistic or stochastic networks · CPC title

• G10H2210/081

  for automatic key or tonality recognition, e.g. using musical rules or a knowledge base · CPC title

• G10H1/0025 Primary

  Automatic or semi-automatic music composition, e.g. producing random music, applying rules from music theory or modifying a musical piece (automatically producing a series of tones G10H1/26) · CPC title

• G10H2250/311

  Neural networks for electrophonic musical instruments or musical processing, e.g. for musical recognition or control, automatic composition or improvisation · CPC title

• G06N3/088

  Non-supervised learning, e.g. competitive learning · CPC title