Music analysis and generation method

• US 20090071315A1
• Filed: 05/05/2008
• Published: 03/19/2009
• Est. Priority Date: 05/04/2007
• Status: Abandoned Application

• Current Assignee: Dedalus Enterprises LLC
• Original Assignee: Dedalus Enterprises LLC
• Inventors: Fortuna, Joseph A.
• Application Number:
  US12/151,278
• Publication Number:
  US 20090071315A1
• Time in Patent Office: Days
• US Class Current: 84/609
• CPC Class Codes: G10H 1/0025 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 Class Codes: G10H 2210/151 using templates, i.e. incomplete musical sections, as a basis for composing
• CPC Class Codes: G10H 2250/015 Markov chains, e.g. hidden Markov models [HMM], for musical processing, e.g. musical analysis or musical composition

Abstract

A system for the creation of music based upon input provided by the user. A user can upload a number of musical compositions into the system. The user can then select from a number of different statistical methods to be used in creating new compositions. The system utilizes a selected statistical method to determine patterns amongst the inputs and creates a new musical composition that utilizes the discovered patterns. The user can select from the following statistical methods: Radial Basis Function (RBF) Regression, Polynomial Regression, Hidden Markov Models (HMM) (Gaussian), HMM (discrete), Next Best Note (NBN), and K-Means clustering. After the existing musical pieces and the statistical method are chosen, the system develops a new musical composition.

Claims

1. A method of generating a musical composition, comprising:

a) providing a digital database comprising a plurality of digital song files;

b) selecting at least one song from said database for training;

c) selecting a training approach; and

d) using statistical methods based upon the selected training approach, creating an output file comprising a new song file.

2. The method of generating a musical composition of claim 1, wherein said training approach is selected from the group consisting of:

RBF Regression;

Polynomial Regression;

Next Best Note;

Hidden Markov Model-discrete;

Hidden Markov Model-Gaussian; and

K-means.

3. The method of generating a musical composition of claim 1, wherein said plurality of digital song files comprises MIDI files.

4. The method of generating a musical composition of claim 1, wherein said output file comprise a playable song file.

5. The method of generating a musical composition of claim 4, wherein said output file comprises a MIDI file.

6. The method of generating a musical composition of claim 4, wherein said output file can be stored in a user selectable location.

7. The method of generating a musical composition of claim 1, wherein songs in said plurality of song files are coded by genre.

8. The method of generating a musical composition of claim 7, said step of selecting at least one song from said database further comprising:

selecting said at least one song based on a selected genre.

9. The method of generating a musical composition of claim 1, said step of using statistical methods based upon the selected training approach to create an output file further comprising:

determining patterns in said at least one song from said database; and

creating a new musical composition using said patterns.