Generating a playlist

Patent metadata

Field	Value
Publication number	US-10055493-B2
Application number	US-201113103445-A
Country	US
Kind code	B2
Filing date	May 9, 2011
Priority date	May 9, 2011
Publication date	Aug 21, 2018
Grant date	Aug 21, 2018

Abstract

Generating a playlist may include designating a seed track in an audio library; identifying audio tracks in the audio library having constructs that are within a range of a corresponding construct of the seed track, where the constructs for the audio tracks are derived from frequency representations of the audio tracks, and the corresponding construct for the seed track is derived from a frequency representation of the seed track; and generating the playlist using at least some of the audio tracks that were identified.

First claim

What is claimed is:

1. A method of generating playlists, comprising:
receiving a user selection of a seed track from audio tracks in an audio library, each of the audio tracks, including the seed track, being represented by a construct, each construct for each of the audio tracks being determined by obtaining metadata tags for a corresponding audio track, the metadata tags relating to one or more attributes of the corresponding audio track, generating a frequency representation of the corresponding audio track, and generating the construct using both the metadata tags and the frequency representation, each construct represented by a vector wherein the frequency representation includes at least one of a stabilized auditory image and a mel-frequency cepstral coefficient;
in response to receiving the user selection of the seed track, cause a user interface element to be presented that generates a playlist based on the seed track;
in response to receiving a selection of the user interface element, identifying audio tracks in the audio library having corresponding constructs that are within a given range of a corresponding construct of the seed track, wherein the corresponding constructs within the range are similar to the corresponding construct of the seed track;
determining distances between the construct for the seed track and the constructs for the identified audio tracks that are within the given range;
assigning weights to artist scores and candidate track scores of the identified audio tracks based on the determined distances to generate weighted artist scores and weighted candidate track scores;
generating the playlist using at least a portion of the identified audio tracks based on the weighted artist scores and the weighted candidate track scores;
in response to generating the playlist, ordering tracks in the playlist in accordance with a randomized decreasing-similarity preference function so that there are no adjacent tracks by the same artist in the ordered tracks in the playlist; and
causing the ordered playlist to be presented.

2. The method of claim 1 , wherein identifying audio tracks in the audio library having corresponding constructs that are within a range of a corresponding construct of the seed track comprises comparing the distances to a designated distance corresponding to the range.

3. The method of claim 2 , wherein the distances are determined using cosine similarity measurements.

4. The method of claim 2 , further comprising applying weights to the distances, the weights being indicative of relative importance of frequency representations of audio tracks in generating the playlist.

5. The method of claim 1 , wherein each audio track is represented by a second construct derived from attributes of the corresponding audio track, and the seed track is represented by a corresponding second construct derived from an attribute associated with the seed track; and
wherein the method further comprises:
determining distances between the second constructs for the audio tracks and the corresponding second construct for the seed track;

wherein identifying audio tracks in the audio library having corresponding constructs that are within a range of a corresponding construct of the seed track comprises comparing the distances to a designated distance corresponding to the range.

6. The method of claim 1 , wherein obtaining the metadata tags comprises:
retrieving information about the audio track from one or more sources; and generating the metadata tags using the information.

7. The method of claim 1 , wherein the construct is generated using a machine-learning technique configured to move, towards each other, audio tracks in a same or similar genre in an N-dimensional space (N2:2), the N-dimensional space being derived from features of the audio tracks.

8. The method of claim 1 , further comprising:
using one or more heuristics to select audio tracks within the range;
wherein the playlist is generated using the audio tracks that were selected using the one or more heuristics.

9. The method of claim 8 , wherein the one or more heuristics comprise limitations on numbers of audio tracks having a specific attribute.

10. The method of claim 1 , wherein each of the audio tracks is represented by a second construct derived from a corresponding artist associated with the audio track, and the seed track is represented by a corresponding second construct derived from an artist associated with the seed track; and
wherein the method further comprises:
determining distances between the second constructs for the audio tracks and the corresponding second construct for the seed track;

wherein identifying audio tracks in the audio library having corresponding constructs that are within a range of a corresponding construct of the seed track comprises comparing the distances to a designated distance corresponding to the range.

11. The method of claim 1 , further comprising designating a second audio track in an audio library;
identifying additional audio tracks in the audio library having second constructs that are within a range of a corresponding second construct of the second audio track, the second constructs for the additional audio tracks being derived from second frequency representations of the additional audio tracks, and the corresponding second construct for the second audio track being derived from a second frequency representation of the seed track; and
wherein the playlist is generated using at least some of the additional audio tracks that were identified.

12. An apparatus comprising a non-transitory machine-readable storage medium having instructions encoded thereon that, in response to execution by a computing device, cause the computing device to perform operations comprising:
receiving a user selection of a seed track from audio tracks in an audio library, each of the audio tracks, including the seed track, being represented by a construct, each construct for each of the audio tracks being determined by obtaining metadata tags for a corresponding audio track, the metadata tags relating to one or more attributes of the corresponding audio track, generating a frequency representation of the corresponding audio track, and generating the construct using both the metadata tags and the frequency representation, each construct represented by a vector wherein the frequency representation includes at least one of a stabilized auditory image and a mel-frequency cepstral coefficient;
in response to receiving the user selection of the seed track, cause a user interface element to be presented that generates a playlist based on the seed track;
in response to receiving a selection of the user interface element, identifying audio tracks in the audio library having corresponding constructs that are within a given range of a corresponding construct of the seed track, wherein the corresponding constructs within the range are similar to the corresponding construct of the seed track;
determining distances between the construct for the seed track and the constructs for the identified audio tracks that are within the given range;
assigning weights to artist scores and candidate track scores of the identified audio tracks based on determined distances to generate weighted artist scores and weighted candidate track scores;
generating the playlist using at least a portion of the identified audio tracks based on the weighted artist scores and the weighted candidate track scores;
in response to generating the playlist, ordering tracks in the playlist in accordance with a randomized decreasing-similarity preference function so that there are no adjacent tracks by the sam

Assignees

• Heitz Iii Geremy A
• Berenzweig Adam
• Weston Jason E
• Weiss Ron J
• Goldman Sally A
• Walters Thomas
• Bengio Samy
• Eck Douglas
• Ponte Jay M
• Rifkin Ryan M
• Google Llc

Inventors

• Heitz Iii Geremy A
• Berenzweig Adam
• Weston Jason E
• Weiss Ron J
• Goldman Sally A
• Walters Thomas
• Bengio Samy
• Eck Douglas
• Ponte Jay M
• Rifkin Ryan M

Classifications

• G06F17/30772 Primary

  Physics · mapped topic

• G06F17/30743

  Physics · mapped topic

• G06F16/683

  using metadata automatically derived from the content · CPC title

• G06F16/639 Primary

  using playlists · CPC title