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WO2003091990: Robust And Invariant Audio Pattern Matching

Filing Information

Inventor(s) Avery Li-Chun WANG · Daniel CULBERT ·
Assignee(s) SHAZAM ENTERTAINMENT, LTD. ·
Attorney/Agent(s) Marek ALBOSZTA ·
Application Number US312126
Filing date 04/18/2003
Publication date 11/06/2003
U.S. Classifications --
International Classifications 7G 1 0L/1/00  ·
Kind CodeA1
Foreign Priority US37605502 - 04/25/2002 ·
27 Claims, 8 Drawings


Abstract

The present invention provides an innovative technique for rapidly and accurately determining whether two audio samples match, as well as being immune to various kinds of transformations, such as playback speed variation. The relationship between the two audio samples is characterized by first matching certain fingerprint objects derived from the respective samples. A set (230) of fingerprint objects (231, 232), each occurring at a particular location (242), is generated for each audio sample (210). Each location is determined in dependence upon the content of respective audio sample (210) and each fingerprint object (232) characterizes one or more local features (222) at or near the respective particular location (242). A relative value is next determined for each pair of matched fingerprint objects. A histogram of the relative values is then generated. If a statistically significant peak is found, the two audio samples can be characterized as substantially matching.

Independent Claims | See all claims (27)

  1. What is claimed is: 1. A method of characterizing a relationship between a first and a second audio samples, comprising the steps of: generating a first set of fingerprint objects for the first audio sample, each fingerprint object occurring at a respective location within the first audio sample, the respective location being determined in dependence upon the content of the first audio sample, and each fingerprint object characterising one or more features of the first audio sample at or near each respective location;
  2. generating a second set of fingerprint objects for the second audio sample, each fingerprint object occurring at a respective location within the second audio sample, the respective location being determined in dependence upon the content of the second audio sample, and each fingerprint object characterising one or more features of the second audio sample at or near each respective location;
  3. pairing fingerprint objects by matching a first fingerprint object from the first audio sample with a second fingerprint object from the second audio sample that is substantially similar to the first fingerprint object;
  4. generating, based on the pairing step, a list of pairs of matched fingerprint objects;
  5. determining a relative value for each pair of matched fingerprint objects;
  6. generating a histogram of the relative values; and
  7. searching for a statistically significant peak in the histogram, the peak characterizing the relationship between the first and second audio samples.
  8. detecting if the relative pitch and a reciprocal of the relative playback speed are substantially different, in which case the relationship between the first and second audio samples is characterized as nonlinear.
  9. for each pair of matched fingerprint objects in the list, determining a compensated relative time offset value, t-R*t, where t and t are locations in time with respect to the first and second fingerprint objects;
  10. generating a second histogram of the compensated relative time offset values; and
  11. searching for a statistically significant peak in the second histogram of the compensated relative time offset values, the peak further characterizing the relationship between the first and second audio samples.
  12. 17. A computer program product for performing a method according to any preceding • claim.

References Cited

The current document has no citations.

Referenced By

Document NumberAssigneeInventorsIssue/Pub Date
EP1704695 Advestigo Hassane ESSAFI et al. Feb 2008
US7363278 Audible Magic Corporation Richard A. Schmelzer et al. Apr 2008
US7529659 Audible Magic Corporation Erling H. Wold May 2009
US7500007 Audible Magic Corporation Vance E. Ikezoye et al. Mar 2009
US7623823 Integrated Media Measurement, Inc. Tom Zito et al. Nov 2009
EP1864279 Fraunhofer-Gesellschaft zur Frderung der angewandten Forschung e.V. Wolfgang FIESEL et al. Jun 2009
US7565327 Audible Magic Corporation Richard A. Schmelzer Jul 2009
US7562012 Audible Magic Corporation Erling H. Wold et al. Jul 2009
US7877438 Audible Magic Corporation James B. Schrempp et al. Jan 2011
US7881657 Shazam Entertainment, Ltd. Avery Li Chun Wang et al. Feb 2011
US7903751 Fraunhofer-Gesellschaft zur Foerderung der angewandten Forschung e.V. Wolfgang Fiesel et al. Mar 2011
US7707088 Audible Magic Corporation Richard A. Schmelzer Apr 2010
US7711652 Audible Magic Corporation Richard A. Schmelzer May 2010
US7797249 Audible Magic Corporation Richard A. Schmelzer et al. Sep 2010
US7917645 Audible Magic Corporation Vance E. Ikezoye et al. Mar 2011
US8006314 Audible Magic Corporation Erling Wold Aug 2011
US8032361 Sony United Kingdom Limited William Edmund Cranstoun Kentish et al. Oct 2011
US8090579 Landmark Digital Services David L. DeBusk et al. Jan 2012
US8082150 Audible Magic Corporation Erling H. Wold Dec 2011
US8112818 Audible Magic Corporation Erling Wold Feb 2012
US8086445 Audible Magic Corporation Erling H. Wold et al. Dec 2011
US8086171 Shazam Entertainment Ltd. Avery Li Chun Wang et al. Dec 2011
US8130746 Audible Magic Corporation James B. Schrempp Mar 2012
US8121830 The Nielsen Company (US), LLC Venugopal Srinivasan et al. Feb 2012

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