Sharing music essence in a recommendation system

• US 7,613,736 B2
• Filed: 05/23/2006
• Issued: 11/03/2009
• Est. Priority Date: 05/23/2005
• Status: Active Grant

• Current Assignee: Gracenote, Inc. (RR Donnelley & Sons Company)
• Original Assignee: Resonance Media Services Incorporated
• Inventors: Hicken, Wendell T.
• Primary Examiner(s): Woo; Isaac M
• Application Number:
  US11/439,723
• Publication Number:
  US 20060265349A1
• Time in Patent Office: 1,260 Days
• Field of Search: 707 1- 10, 707100-1041, 707200-206
• US Class Current: 1/1
• CPC Class Codes: G06F 16/634 Query by example, e.g. query by humming
• CPC Class Codes: G06F 16/639 using playlists
• CPC Class Codes: G06F 16/68 Retrieval characterised by using metadata, e.g. metadata not derived from the content or metadata generated manually
• CPC Class Codes: G06F 16/683 using metadata automatically derived from the content
• CPC Class Codes: G11B 27/105 of operating discs
• CPC Class Codes: Y10S 707/99942 Manipulating data structure, e.g. compression, compaction, compilation
• CPC Class Codes: Y10S 707/99943 Generating database or data structure, e.g. via user interface
• CPC Class Codes: Y10S 707/99944 Object-oriented database structure
• CPC Class Codes: Y10S 707/99945 Object-oriented database structure processing
• CPC Class Codes: Y10S 707/99948 Application of database or data structure, e.g. distributed, multimedia, or image

Abstract

A system for sharing playlists and playlist essence with different users. A user desiring to share his or her playlist generates the playlist and a playlist characterization. The playlist characterization is based on acoustic analysis data of one or more songs in the playlist. The playlist and playlist characterization is then transmitted to another end user device. The end user device receiving the shared playlist searches the user'"'"'s music collection for the songs in the playlist. If a gap is detected in the playlist because the receiving user does not own a particular song, the receiving end user devices automatically selects another song that is owned by the user to fill-in the gap. The song is selected based on the playlist characterization with the aim of preserving the essence of the shared playlist.

Claims

1. A computer-implemented method for sharing playlists comprising:

selecting one or more songs from a first data store;

generating a playlist based on the selected songs;

retrieving acoustic analysis data of one or more songs in the playlist;

generating a playlist characterization based on the acoustic analysis data;

transmitting the playlist and the playlist characterization to a remote end device coupled to a second data store, wherein at least one of the songs in the playlist is unavailable in the second data store;

generating by the remote end device a modified playlist based on the received playlist characterization, wherein the generating includes automatically replacing the unavailable song in the playlist with a replacement song available in the second data store, the replacement song being automatically selected by the remote end device based on the playlist characterization; and

playing the modified playlist via the remote end device.

2. The method of claim 1, wherein the playlist and the playlist characterization are transmitted to a server for downloading by the remote end device.

3. The method of claim 1, wherein the playlist characterization is based on acoustic analysis data of at least one song in the playlist.

4. The method of claim 1, wherein the playlist characterization is based on a group profile of the playlist, the group profile being generated based on acoustic analysis data of a plurality of songs in the playlist.

5. The method of claim 1, wherein the playlist characterization is based on a group profile of an artist associated with the playlist.

6. The method of claim 1, wherein the playlist characterization is based on a group profile of an album associated with the playlist.

7. The method of claim 1, wherein the playlist characterization is based on the acoustic analysis data of a plurality of the songs in the playlist, the acoustic analysis data being generated via a computerized analysis of acoustic signals of the plurality of the songs.

8. The method of claim 1, wherein the playlist characterization includes acoustic analysis data of the unavailable song, and the replacement song is selected based an a computer-implemented comparison of the acoustic analysis data of the unavailable song and acoustic analysis data of the replacement song.

9. An end user device in a system for sharing playlists, the end user device comprising:

a first data store storing a plurality of songs and acoustic analysis data for the plurality of the songs;

a processor; and

a memory coupled to the processor, and having program instructions stored therein, the processor being operable to execute the program instructions, the program instructions including;

selecting one or more songs from the first data store;

generating a playlist based on the selected songs;

retrieving acoustic analysis data of one or more songs in the playlist; and

generating a playlist characterization based on the acoustic analysis data; and

a network connection for transmitting the playlist and the playlist characterization to a remote end device coupled to a second data store, wherein at least one of the songs in the playlist is unavailable in the second data store, wherein the remote end device is configured to generate a modified playlist based on the received playlist characterization, wherein the generating includes automatically replacing the unavailable song in the playlist with a replacement song available in the second data store, the replacement song being automatically selected by the remote end device based on the playlist characterization, the remote end device being further configured to play the modified playlist.

10. The end user device of claim 9, wherein the playlist and the playlist characterization are transmitted to a server for downloading by the remote end device.

11. The end user device of claim 9, wherein the playlist characterization is based on acoustic analysis data of at least one song in the playlist.

12. The end user device of claim 9, wherein the playlist characterization is based on a group profile of the playlist, the group profile being generated based on acoustic analysis data of a plurality of songs in the playlist.

13. The end user device of claim 9, wherein the playlist characterization is based on a group profile of an artist associated with the playlist.

14. The end user device of claim 9, wherein the playlist characterization is based on a group profile of an album associated with the playlist.