Artificial neural network based system for classification of the emotional content of digital music

• US 9,263,060 B2
• Filed: 08/21/2012
• Issued: 02/16/2016
• Est. Priority Date: 08/21/2012
• Status: Active Grant

• Current Assignee: Marian Mason Publishing Company, LLC
• Original Assignee: Marian Mason Publishing Company, LLC
• Inventors: Sharp, David A.
• Primary Examiner(s): Spooner, Lamont
• Application Number:
  US13/590,680
• Publication Number:
  US 20140058735A1
• Time in Patent Office: 1,274 Days
• Field of Search: 704/500, 704/207, 700/94
• US Class Current: 1/1
• CPC Class Codes: G10H 1/0008 Associated control or indicating means
• CPC Class Codes: G10H 2210/066 for pitch analysis as part of wider processing for musical purposes, e.g. transcription, musical performance evaluation; Pitch recognition, e.g. in polyphonic sounds; Estimation or use of missing fundamental
• CPC Class Codes: G10H 2240/085 Mood, i.e. generation, detection or selection of a particular emotional content or atmosphere in a musical piece
• CPC Class Codes: G10H 2240/131 Library retrieval, i.e. searching a database or selecting a specific musical piece, segment, pattern, rule or parameter set
• CPC Class Codes: G10H 2250/311 Neural networks for electrophonic musical instruments or musical processing, e.g. for musical recognition or control, automatic composition or improvisation
• CPC Class Codes: G10L 25/30 using neural networks
• CPC Class Codes: G10L 25/63 for estimating an emotional state

Abstract

A system for classification of the emotional content of music is provided. An encoder receives a digital audio recording of a piece of music, and encodes it using musical notes and associated amplitudes. The artificial neural network is configured to take a plurality of encoded time slices and provide output indicative of the emotional content of the music.

Claims

1. A method of encoding a digital audio file comprising samples having a first sample rate, said method comprising:

a) dividing said digital audio file into slices, each slice comprising one or more samples;

b) determining one or more frequencies of sound represented in each of said slices;

c) determining one or more amplitudes associated with each of said frequencies in each slice;

d) determining a musical note associated with each of said frequencies in each slice; and

e) outputting a digital representation of each slice, wherein the digital representation comprises a set of musical notes and associated amplitudes, and wherein the outputting the digital representation of each slice comprises outputting the digital representation having a fixed length and comprising a first and a second series of bits, the first series of bits corresponding to a set of predetermined musical notes, and the second series of bits corresponding to predetermined amplitude ranges.

2. The method of claim 1 wherein the set of predetermined musical notes comprise a musical scale.

3. The method of claim 1 wherein the set of predetermined musical notes are substantially consecutive.

4. The method of claim 1 wherein the set of predetermined musical notes comprises a chromatic scale.

5. The method of claim 1, wherein the digital representation is hexadecimal.

6. The method of claim 1, wherein the digital representation is binary.

7. The method of claim 6, wherein each of said first series of bits is set if its corresponding one of the set of predetermined musical note is present in the slice, and is not set if its corresponding one of the set of predetermined musical notes is not present in the slice.

8. The method of claim 1, wherein each of said second series of bits is set if an amplitude within its associated amplitude range exists within the slice and is not set if an amplitude within its associated amplitude range does not exist within the slice.

9. The method of claim 1 wherein said determining one or more frequencies of sound represented in each of said slices comprises performing a Fourier Transform.

10. The method of claim 1 wherein said first sample rate is about 44.1 KHz.

11. The method of claim 1 further comprising resampling said digital audio file from said first sample rate to a second sample rate.

12. The method of claim 11 wherein said second sample rate is about 6 KHz.

13. The method of claim 1 wherein each of said slices comprises substantially the same number of samples.

14. The method of claim 13 wherein the number of samples in a slice is about 750.

15. The method of claim 1 wherein step (e) is repeated for each of a plurality of sets of predetermined musical notes.