System and Method for Providing Acoustic Analysis Data

• US 20080215173A1
• Filed: 05/15/2008
• Published: 09/04/2008
• Est. Priority Date: 06/28/1999
• Status: Abandoned Application

• Current Assignee: Gracenote, Inc. (RR Donnelley & Sons Company)
• Original Assignee: Musicip Corporation (AmpliFIND Music Services, Inc.)
• Inventors: Hicken, Wendell T., Campbell, Marc Elroy, Holm, Frode, Clune, James Edmond
• Application Number:
  US12/120,963
• Publication Number:
  US 20080215173A1
• Time in Patent Office: Days
• US Class Current: 700/94
• CPC Class Codes: G06F 16/634 Query by example, e.g. query by humming
• 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 16/68 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: G06F 16/90324 using system suggestions
• CPC Class Codes: G06Q 30/0631 Item recommendations
• CPC Class Codes: G11B 2220/2545 CDs
• CPC Class Codes: G11B 2220/2562 DVDs [digital versatile discs]; Digital video discs; MMCDs; HDCDs
• CPC Class Codes: G11B 27/105 of operating discs
• CPC Class Codes: G11B 27/11 by using information not detectable on the record carrier
• CPC Class Codes: G11B 27/34 Indicating arrangements indicating means incorporated in magazine or cassette G11B23/046 and G11B23/0875; indicating measured values in general G01D
• CPC Class Codes: H04L 67/306 User profiles

Abstract

A music recommendation system receives a user selection of desired music, retrieves analysis data associated with the selected music, and generates a playlist of songs based on the analysis data. The analysis data is generated based on a processing of one or more audio signals associated with the selected music. The analysis data may downloaded from a central server. If the analysis data is not available from the central server, it is generated locally at a user end, and uploaded to the central server. A plurality of user-selectable shuffling mechanisms are provided to allow the order of the songs to be shuffled according to the selected shuffling mechanism. The end user device may also receive recommendation of new music from different providers based on the analysis data of music for which the recommendation is to be based.

Claims

1. In a recommendation system including a server coupled to an end user device over a data communications network, the server comprising:

a first data store storing an acoustic analysis database of acoustic analysis data for a plurality of audio pieces, the acoustic analysis data being generated based on an automatic processing of audio signals of one or more audio pieces, the acoustic analysis data providing numerical measurements for a plurality of predetermined acoustic attributes;

means for receiving a query for first acoustic analysis data associated with a first audio piece;

means for searching the acoustic analysis database for the first acoustic analysis data;

means for transmitting the first acoustic analysis data to the end user device responsive to a determination that the first acoustic analysis data is stored in the first data store and

means for receiving the first acoustic analysis data from the end user device responsive to a determination that the first acoustic analysis data is not stored in the first data store, the received acoustic analysis data being generated by the end user device by processing audio signals for the first audio piece.

2. The server of claim 1 further comprising:

a computer-readable medium storing computer instructions for processing audio signals and making recommendations based on the processed audio signals.

3. The server of claim 2, wherein the instructions further include instructions for generating a fingerprint of a particular audio piece.

4. The server of claim 2, wherein the means for searching the acoustic analysis database includes searching the database based on a fingerprint generated for the first audio piece.

5. The server of claim 2, wherein the computer instructions are transmitted to the end user device.

6. The server of claim 2, wherein the instructions, when executed by a processor, causes the processor to retrieve a second acoustic analysis data for the second audio piece, calculate a distance between the first acoustic analysis data and the second acoustic analysis data, and recommend the second audio piece based on the comparison.