MUSICAL ELEMENT GENERATION SUPPORT DEVICE, MUSICAL ELEMENT LEARNING DEVICE, MUSICAL ELEMENT GENERATION SUPPORT METHOD, MUSICAL ELEMENT LEARNING METHOD, NON-TRANSITORY COMPUTER-READABLE MEDIUM STORING MUSICAL ELEMENT GENERATION SUPPORT PROGRAM, AND NON-TRANSITORY COMPUTER-READABLE MEDIUM STORING MUSICAL ELEMENT LEARNING PROGRAM

Information

  • Patent Application
  • 20230298548
  • Publication Number
    20230298548
  • Date Filed
    May 24, 2023
    a year ago
  • Date Published
    September 21, 2023
    a year ago
Abstract
A musical element generation support device includes at least one processor configured to receive a musical element sequence including a plurality of musical elements and a blank portion that are arranged in a time series, and generate, by using a learning model, at least one suitable musical element for the blank portion based on a part of the musical elements that is positioned after the blank portion on a time axis in the musical element sequence. The learning model is configured to generate, from one-part musical element, another-part musical element.
Description
Claims
  • 1. A musical element generation support device comprising: at least one processor configured to receive a musical element sequence including a plurality of musical elements and a blank portion that are arranged in a time series, andgenerate, by using a learning model, at least one suitable musical element for the blank portion based on a part of the musical elements that is positioned after the blank portion on a time axis in the musical element sequence, the learning model being configured to generate, from one-part musical element, another-part musical element.
  • 2. The musical element generation support device according to claim 1, wherein the at least one processor is configured to generate, by using the learning model, the at least one suitable musical element for the blank portion based further on a part of the musical elements that is positioned before the blank portion on the time axis in the musical element sequence.
  • 3. The musical element generation support device according to claim 1, wherein the at least one processor is configured to generate a plurality of suitable musical elements that are suitable for the blank portion and evaluate suitability of each of the plurality of suitable musical elements.
  • 4. The musical element generation support device according to claim 3, wherein the at least one processor is further configured to present only a prescribed number of the plurality of suitable musical elements in order of suitability.
  • 5. The musical element generation support device according to claim 3, wherein the at least one processor is further configured to present, from among the plurality of suitable musical elements, at least one suitable musical element having a higher suitability degree than a prescribed suitability degree.
  • 6. The musical element generation support device according to claim 3, wherein the at least one processor is further configured to select, from among the plurality of suitable musical elements, a suitable musical element with a highest suitability degree.
  • 7. The musical element generation support device according to claim 1, wherein the musical element sequence includes melodies, chord progressions, lyrics, or rhythm patterns.
  • 8. A musical element generation support method comprising: receiving a musical element sequence including a plurality of musical elements and a blank portion that are arranged in a time series; andgenerating at least one musical element for the blank portion based on a part of the musical elements that is positioned after the blank portion on a time axis in the musical element sequence, by using a learning model configured to generate, from one-part musical element, another-part musical element.
  • 9. The musical element generation support method according to claim 8, wherein the generating is performed, by using the learning model, based further on a part of the musical elements that is positioned before the blank portion on the time axis in the musical element sequence.
  • 10. The musical element generation support method according to claim 8, wherein in the generating, a plurality of suitable musical elements that are suitable for the blank portion are generated, andthe musical element generation support method further comprises evaluating suitability of each of the plurality of suitable musical elements.
  • 11. The musical element generation support method according to claim 10, further comprising presenting only a prescribed number of the plurality of suitable musical elements in order of suitability.
  • 12. The musical element generation support method according to claim 10, further comprising presenting, from among the plurality of suitable musical elements, at least one suitable musical element having a higher suitability degree than a prescribed suitability degree.
  • 13. The musical element generation support method according to claim 10, further comprising selecting, from among the plurality of suitable musical elements, a suitable musical element with a highest suitability degree.
  • 14. The musical element generation support method according to claim 8, wherein the musical element sequence includes melodies, chord progressions, lyrics, or rhythm patterns.
  • 15. A musical element learning method comprising: acquiring a plurality of musical element sequences each of which includes a plurality of musical elements arranged in a time series;randomly setting a blank portion in a part of each of the musical element sequences; andconstructing a learning model indicating a relationship between at least one musical element and a musical element for a blank portion, by machine learning a relationship between at least one of the musical elements for the blank portion and at least one of the musical elements for a portion other than the blank portion in each of the musical element sequences.
Priority Claims (1)
Number Date Country Kind
2020-194991 Nov 2020 JP national
Continuations (1)
Number Date Country
Parent PCT/JP2021/042636 Nov 2020 WO
Child 18322967 US