Techniques for ordering digital music tracks in a sequence

• US 9,343,054 B1
• Filed: 06/24/2014
• Issued: 05/17/2016
• Est. Priority Date: 06/24/2014
• Status: Active Grant

• Current Assignee: Amazon Technologies, Inc. (Amazon.com, Inc.)
• Original Assignee: Amazon Technologies, Inc. (Amazon.com, Inc.)
• Inventors: McGilliard, Christopher Lon, Latin-Stoermer, Toby Ray
• Primary Examiner(s): Donels, Jeffrey
• Application Number:
  US14/313,183
• Time in Patent Office: 693 Days
• Field of Search: 846/09, 846/15
• US Class Current: 1/1
• CPC Class Codes: G06F 16/635 Filtering based on additional data, e.g. user or group profiles
• CPC Class Codes: G06F 16/639 using playlists
• CPC Class Codes: G06F 16/683 using metadata automatically derived from the content
• CPC Class Codes: G10H 2210/076 for extraction of timing, tempo; Beat detection tempo display G10H2220/081; tempo control G10H2210/375
• CPC Class Codes: G10H 2240/081 Genre classification, i.e. descriptive metadata for classification or selection of musical pieces according to style analysis genre G10H2210/036
• 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: H04N 21/26258 for generating a list of items to be played back in a given order, e.g. playlist, or scheduling item distribution according to such list retrieval of multimedia data based on playlists G06F16/40
• CPC Class Codes: H04N 21/4668 for recommending content, e.g. movies
• CPC Class Codes: H04N 21/8113 comprising music, e.g. song in MP3 format

Abstract

Techniques are described for automatically re-ordering digital music tracks in a sequence for playback on a digital device. The sequence of digital music tracks is algorithmically arranged to provide better transitions between the digital music tracks in the sequence.

Claims

1. A computer implemented method, comprising:

receiving, by one or more computing devices, a request from a client device for playback of musical content by a music delivery service;

receiving, by the one or more computing devices, a plurality of identifiers, each of the identifiers corresponding to one of a plurality of music tracks selected for playback on the client device;

determining, by the one or more computing devices, a sequence of the music tracks with reference to a plurality of track propensity scores, each track propensity score representing a tendency for a particular one of the music tracks to immediately follow another one of the music tracks during playback; and

transmitting, by the one or more computing devices, the music tracks to the client device for playback in the sequence.

2. The method of claim 1, wherein the track propensity scores are based on musical characteristics of the music tracks, the musical characteristics including beats per minute, harmony, or dissonance.

3. The method of claim 1, wherein the track propensity scores are based on sequences of the music tracks selected by a population of users of the music delivery service providing musical content.

4. The method of claim 1, wherein the track propensity scores are further based sequences of the music tracks selected by a population of music providers providing musical content.

5. A computing device, comprising:

one or more processors and memory configured to;

select a plurality of media files for playback;

determine a sequence of the media files with reference to a plurality of propensity scores, each propensity score representing a tendency for a particular one of the media files to follow another one of the files during playback; and

provide the media files for playback in the sequence.

6. The computing device of claim 5, wherein the media files correspond to music tracks and the propensity scores are based on musical characteristics of the music tracks.

7. The computing device of claim 6, wherein the musical characteristics include one or more of beats per minute, harmony, or dissonance.

8. The computing device of claim 5, wherein the media files correspond to music tracks and the propensity scores are based on sequences of the music tracks selected by a population of users of a music delivery service.

9. The computing device of claim 8, wherein the propensity scores are further based on sequences of the musical tracks selected by a population of music providers.

10. The computing device of claim 5, wherein the sequence is determined, at least in part, by comparing the propensity scores to a threshold propensity score range.

11. The computing device of claim 10, wherein transitions between media files corresponding to propensity scores within the threshold propensity score range are included in the sequence, and transitions media files corresponding to propensity scores outside the threshold propensity score range are excluded from the sequence.

12. The computing device of claim 10, wherein the sequence includes a first portion and a second portion, the first portion occurring in the sequence before the second portion, the first portion including transitions between media files corresponding to propensity scores within the threshold propensity score range, the second portion including transitions between media files corresponding to propensity scores outside the threshold propensity score range.

13. A computer program product, comprising one or more non-transitory computer-readable media having computer program instructions stored therein, the computer program instructions being configured such that, when executed by one or more computing devices, the computer program instructions cause the one or more computing devices to:

select a plurality of media files for playback;

determine a sequence of the media files with reference to a plurality of propensity scores, each propensity score representing a tendency for a particular one of the media files to follow another one of the files during playback; and

provide the media files for playback in the sequence.

14. The computer program product of claim 13, wherein the media files correspond to music tracks and the propensity scores are based on musical characteristics of the music tracks.

15. The computer program product of claim 14, wherein the musical characteristics include one or more of beats per minute, harmony, or dissonance.

16. The computer program product of claim 13, wherein the media files correspond to music tracks and the propensity scores are based on sequences of the music tracks selected by a population of users of a music delivery service.

17. The computer program product of claim 16, wherein the propensity scores are further based on sequences of the musical tracks selected by a population of music providers.

18. The computer program product of claim 13, wherein the sequence is determined, at least in part, by comparing the propensity scores to a threshold propensity score range.

19. The computer program product of claim 18, wherein transitions between media files corresponding to propensity scores within the threshold propensity score range are included in the sequence, and transitions of media files corresponding to propensity scores outside the threshold propensity score range are excluded from the sequence.

20. The computer program product of claim 18, wherein the sequence includes a first portion and a second portion, the first portion occurring in the sequence before the second portion, the first portion including transitions between media files corresponding to propensity scores within the threshold propensity score range, the second portion including transitions between media files corresponding to propensity scores outside the threshold propensity score range.