Search Images Maps Play YouTube News Gmail Drive More »
Sign in
Screen reader users: click this link for accessible mode. Accessible mode has the same essential features but works better with your reader.

Patents

  1. Advanced Patent Search
Publication numberUS20030028796 A1
Publication typeApplication
Application numberUS 10/208,189
Publication date6 Feb 2003
Filing date31 Jul 2002
Priority date31 Jul 2001
Also published asEP1421521A2, US8468357, US20100158488, US20100161656, WO2003012695A2, WO2003012695A3
Publication number10208189, 208189, US 2003/0028796 A1, US 2003/028796 A1, US 20030028796 A1, US 20030028796A1, US 2003028796 A1, US 2003028796A1, US-A1-20030028796, US-A1-2003028796, US2003/0028796A1, US2003/028796A1, US20030028796 A1, US20030028796A1, US2003028796 A1, US2003028796A1
InventorsDale Roberts, David Hyman, Stephen White
Original AssigneeGracenote, Inc.
Export CitationBiBTeX, EndNote, RefMan
External Links: USPTO, USPTO Assignment, Espacenet
Multiple step identification of recordings
US 20030028796 A1
Abstract
Multiple information is extracted from an unknown recording and information associated therewith. Associated information includes the filename, if the recording is a computer file in, e.g., MP3 format, or table of contents (TOC) data, if the recording is on a removable medium, such as a compact disc. At least one and preferably several algorithmically determined fingerprints are extracted from the recording using one or more fingerprint extraction methods. The information extracted is compared with corresponding information in a database maintained for reference recordings. Identification starts with the most accurate and efficient method available, e.g., using a hash ID, a unique ID or text. Fingerprint matching is used to confirm other matches and validation is performed by comparing the duration of the unknown and a possibly matching reference recording.
Images(7)
Previous page
Next page
Claims(67)
What is claimed is:
1. A method of identifying recordings, comprising:
extracting information about an unknown recording stored in media possessed by a user and at least one algorithmically determined fingerprint from at least one portion of the unknown recording;
determining a possible identification of the unknown recording using at least one piece of the information extracted from the unknown recording and an identification database of corresponding information for reference recordings; and
identifying the unknown recording when the possible identification based on each of the at least one piece of the information in combination with the at least one algorithmically determined fingerprint identifies a single reference recording with respective confidence levels.
2. A method as recited in claim 1,
wherein the identification database is maintained by a provider of identification services, and
wherein said determining uses a unique identifier from the provider of identification services when the unique identifier is associated with the unknown recording and otherwise uses text associated with the unknown recording when text is associated with the unknown recording.
3. A method as recited in claim 2, further comprising validating said identifying by comparing an extracted length of the unknown recording with a stored length of the single reference recording.
4. A method as recited in claim 3, wherein the text associated with the unknown recording includes a filename of the recording.
5. A method as recited in claim 3, wherein the text associated with the unknown recording includes an ID3 tag for the recording.
6. A method as recited in claim 1, wherein the at least one algorithmically determined fingerprint is extracted from at least one of audio and video information in the at least one portion of the unknown recording.
7. A method as recited in claim 1,
wherein the at least one algorithmically determined fingerprint includes at least two fingerprints, and
wherein said identifying requires each of the at least two fingerprints to identify the single reference recording with respective confidence levels.
8. A method as recited in claim 1, further comprising validating said identifying by comparing an extracted length of the unknown recording with a stored length of the single reference recording.
9. A method as recited in claim 8, further comprising:
repeating said extracting, determining and identifying for a plurality unknown recordings from a plurality users;
monitoring unsuccessful identifications of the unknown recordings; and
detecting a possible error in the identification database from a pattern of errors.
10. A method as recited in claim 9, wherein said monitoring includes receiving information from the users indicating that said identifying was incorrect.
11. A method as recited in claim 9,
wherein said monitoring includes storing the at least one algorithmically determined fingerprint and an identifier of the single reference recording when said validating is not successful, and
wherein said method further comprises indicating the possible error in the identification database when substantially different fingerprints are stored for a single identifier.
12. A method as recited in claim 9, wherein said method further comprises indicating the possible error when the at least one algorithmically determined fingerprint matches one of the reference recordings, but the unknown recording is associated with ID3 Tag information different from that of the one of the reference recordings.
13. A method as recited in claim 9, further comprising correcting the possible error based on the information extracted from the unknown recordings.
14. A method as recited in claim 8, further comprising indicating a possible error in the identification database when the at least one algorithmically determined fingerprint is substantially similar to one of the reference recordings, but substantially different information is extracted from the unknown recording.
15. A method as recited in claim 1, further comprising delivering related data for the unknown recording from a supplemental database to supplement data embedded within the unknown recording for display and user manipulation.
16. A method of identifying recordings, comprising:
extracting fingerprints from at least one portion of an unknown recording using a plurality of algorithms;
determining a possible identification of the unknown recording using at least two of the fingerprints extracted from the unknown recording and at least one database of correspondingly generated fingerprints for reference recordings; and
identifying the unknown recording when the possible identification based on each of the fingerprints identifies a single reference recording with respective confidence levels.
17. A method as recited in claim 16, wherein each fingerprint is extracted from at least one of audio and video information in the at least one portion of the unknown recording.
18. A method as recited in claim 16, further comprising validating said identifying by comparing a length of the unknown recording with a stored length of the single reference recording.
19. A method as recited in claim 18,
wherein said extracting is performed by client equipment possessed by a user,
wherein said determining, identifying and validating are performed by at least one server under control of a provider of identification services, and
wherein said method further comprises:
transmitting a unique identifier associated with the single reference recording from the at least one server to the client equipment after said validating is successful; and
associating the unique identifier with the unknown recording in the client equipment.
20. A method as recited in claim 19, further comprising:
comparing the unique identifier with a permission list of stored identifiers in the at least one database;
indicating that the recording may be shared if there is a match for the unique identifier in the permission list.
21. A method as recited in claim 19, further comprising:
comparing the unique identifier with a block list of stored identifiers in the at least one database;
indicating that the recording may not be shared if there is a match for the unique identifier in the block list.
22. A method of obtaining reference information stored in a database used to identify unknown recordings, comprising:
obtaining non-waveform data associated with a recording possessed by a user of the database for identification of recordings possessed by the user;
extracting at least one fingerprint from at least one portion of the recording; and
storing the at least one fingerprint as identifying information for the recording, when a match is found in the database for the non-waveform data.
23. A method as recited in claim 22, wherein the non-waveform data indicates the length of the recording.
24. A method as recited in claim 23, wherein the recording is permanently stored on a removable medium and the non-waveform data is derived from table of contents data for the recording.
25. A method as recited in claim 22, wherein the non-waveform data includes text associated with the recording.
26. A method as recited in claim 25, wherein the non-waveform data includes and ID3 tag.
27. A method as recited in claim 26,
wherein the ID3 tag includes encoded information,
wherein the database is maintained by a provider of identification services and the encoded information is generated under control of the provider of identification services, and
wherein said method further comprises validating the non-waveform data by decoding the encoded information prior to said storing of the identifying information in the database.
28. A method as recited in claim 25, wherein the non-waveform data includes a watermark.
29. A method as recited in claim 25, wherein the non-waveform data includes media information regarding source media type.
30. A method as recited in claim 29, wherein the media information identifies the source media type as CD-R.
31. A method as recited in claim 29, wherein the media information identifies the source media type as CD-DA.
32. A method as recited in claim 29, wherein the media information identifies the source media type as a digital file.
33. A method as recited in claim 29, wherein the media information identifies the source media type as a digital versatile disc.
34. A method as recited in claim 25, wherein the text includes a filename of the recording.
35. A method as recited in claim 25, wherein the text includes a title of the recording.
36. A method as recited in claim 25, wherein the text includes an artist name of a participant in creation of the recording.
37. A method as recited in claim 25, wherein the text includes an album name associated with the recording.
38. A method as recited in claim 22, wherein said obtaining and extracting are performed by client equipment possessed by a plurality users for different copies of the recording and different users extract different fingerprints from the recording.
39. A method as recited in claim 38, further comprising:
maintaining the database on at least one server under control of a provider of identification services, and
transmitting from the at least one server to the client equipment, extraction instructions on which of the different fingerprints each of the client equipment extracts.
40. A method as recited in claim 39, further comprising:
transmitting the non-waveform data from the client equipment to the at least one server; and
selecting the extraction instructions by the at least one server for said transmitting to the client equipment based on the non-waveform data.
41. A method as recited in claim 40, further comprising updating the extraction instructions based at least in part on frequency of receipt of the non-waveform data for the recording.
42. A method as recited in claim 40, wherein said selecting of the extraction instructions is based at least in part on type of the client equipment receiving the extraction instructions.
43. A method as recited in claim 40, wherein said selecting of the extraction instructions is based at least in part on geographical location of the client equipment receiving the extraction instructions.
44. A method as recited in claim 40, wherein said selecting of the extraction instructions is based at least in part on software operating on the client equipment receiving the extraction instructions.
45. A method as recited in claim 40, further comprising updating the extraction instructions based at least in part on number of users who have supplied the identifying information.
46. A method as recited in claim 40, wherein said selecting of the extraction instructions is based at least in part on quality of the copies of the recording.
47. A method as recited in claim 40, further comprising transmitting the at least one fingerprint from the client equipment to the at least one server at a time specified by the extraction instructions.
48. A method as recited in claim 47, further comprising storing the at least one fingerprint at the client equipment until a specified number of fingerprints are ready for said transmitting.
49. A method as recited in claim 47, wherein said transmitting of the at least one fingerprint occurs when a communication channel with the at least server is available.
50. A method as recited in claim 47, wherein said transmitting of the at least one fingerprint for a first recording accessed by a piece of client equipment occurs with said transmitting of the non-waveform data for a second recording accessed by the piece of client equipment.
51. A method as recited in claim 47,
wherein the recording is permanently stored on a removable medium and the client equipment generates at least one encoded file from the recording, and
wherein said transmitting transmits the at least one fingerprint before encoding the recording.
52. A method as recited in claim 47,
wherein the recording is permanently stored on a removable medium and the client equipment generates at least one encoded file from the recording, and
wherein said transmitting transmits the at least one fingerprint after encoding one track of the removable medium.
53. A method as recited in claim 47,
wherein the recording is permanently stored on a removable medium and the client equipment generates at least one encoded file from the recording, and
wherein said transmitting transmits the at least one fingerprint after receiving an indication that encoding of the removable medium has been completed.
54. A method as recited in claim 22, wherein the database includes the identifying information for musical recordings.
55. A method as recited in claim 22, wherein the database includes the identifying information for video recordings.
56. A method as recited in claim 22, further comprising:
detecting a quality of the at least one fingerprint;
identifying another copy of the recording using the at least one fingerprint; and
replacing the at least one fingerprint with a higher quality fingerprint when the other copy of the recording produces the higher quality fingerprint.
57. A method as recited in claim 56, wherein said detecting of the quality is based on an encoding technique used for the recording.
58. A method as recited in claim 56, wherein said detecting of the quality is based on a media type used to store the recording.
59. A method as recited in claim 56, wherein said detecting of the quality is based on error correction capability of user equipment accessing the recording.
60. A method as recited in claim 59, wherein said detecting of the quality assigns higher quality when hardware error correction is used than when software error correction is by the user equipment.
61. A method as recited in claim 56, wherein said detecting of the quality is based on number of errors detected during said extracting of the fingerprint.
62. A method as recited in claim 22,
wherein said obtaining and extracting are performed by client equipment possessed by a plurality users for different copies of the recording, and
wherein said method further comprises:
comparing the at least one fingerprint obtained from one of the users with the at least one fingerprint extracted from at least one other user; and
updating the at least one fingerprint in the database based on said comparing.
63. A method as recited in claim 62, wherein said updating is performed after said comparing determines that fingerprints from different users have a predetermined correlation.
64. A method as recited in claim 62, wherein said updating combines fingerprints from different users for storage in the database.
65. A system for identifying recordings, comprising:
an extraction unit to extract information about an unknown recording stored in media possessed by a user and at least one algorithmically determined fingerprint from at least one portion of the unknown recording; and
an identification unit, coupled to said extraction unit, to make a possible identification of the unknown recording using at least one piece of the information extracted from the unknown recording and an identification database of corresponding information for reference recordings, and to identify the unknown recording when the possible identification based on each of the at least one piece of the information in combination with the at least one algorithmically determined fingerprint identifies a single reference recording with respective confidence levels.
66. A system for identifying recordings, comprising:
an extraction unit to extract fingerprints from at least one portion of an unknown recording using a plurality of algorithms; and
an identification unit, coupled to said extraction unit, to make a possible identification of the unknown recording using at least two of the fingerprints extracted from the unknown recording and at least one database of correspondingly generated fingerprints for reference recordings, and to identify the unknown recording when the possible identification based on each of the fingerprints identifies a single reference recording with respective confidence levels.
67. A system for obtaining reference information stored in a database used to identify unknown recordings, comprising:
a receiving unit to obtain non-waveform data associated with a recording possessed by a user of the database for identification of recordings possessed by the user;
an extraction unit to extract at least one fingerprint from at least one portion of the recording; and
a storage unit, coupled to said receiving unit and said extraction unit, to store the at least one fingerprint as identifying information for the recording, when a match is found in the database for the non-waveform data.
Description
    CROSS-REFERENCE TO RELATED APPLICATION(S)
  • [0001]
    This application is related to and claims priority to U.S. provisional application entitled DIGITAL MUSIC MULTIPLE STEP IDENTIFICATION METHOD AND SYSTEM having serial No. 60/308,594, by Dale T. Roberts, et al., filed Jul. 31, 2001, and incorporated by reference herein.
  • BACKGROUND OF THE INVENTION
  • [0002]
    1. Field of the Invention
  • [0003]
    The present invention is directed to recognition of recordings from their content, and, more particularly to combining fingerprint recognition with other information about a recording to increase reliability of recognition and to accomplish reliable recognition efficiently by using the least expensive forms of recognition first and layering on more complex forms as needed.
  • [0004]
    2. Description of the Related Art
  • [0005]
    There are many uses for recognition of audio (and video) recordings. Many of the uses relate to compensation or control by the rights holders for reproduction and performance of the works recorded. This use of such systems has increased in importance since the development of file sharing software, such as Napster, and the many other similar services available at the end of the twentieth century and the beginning of the twenty first century. Although the need for accurate recognition has been significant for several years, no system has been successful in meeting this need.
  • [0006]
    Another use of recording recognition is to provide added value to users when listening (or watching) recordings. One example is the CDDB Music Recognition Service from Gracenote, Inc. of Berkeley, Calif. which recognizes compact discs (CDs) and supplies information regarding a recognized CD, such as album name, artist, track names and access to related content on the Internet, including album covers, artist and fan websites, etc. While the CDDB service is effective for recognizing compact discs, there are several draw backs in using it to recognize files that are not stored on a removable disc, such as CD or DVD.
  • [0007]
    All audio fingerprinting techniques have “blind spots”, places where a system using that technique sees similarities and differences in audio where it shouldn't. By relying on just one fingerprinting technique, single source solutions are less accurate when encountering a ‘blind spot’.
  • [0008]
    One of the more popular uses for the Gracenote CDDB system is in applications that digitally encode audio files into MP3 and other formats. These encoding applications utilize Gracenote's CDDB service to recognize the compact disc being encoded and to write the correct metadata into the title and ID tags. Gracenote's CDDB service returns a unique ID (TUID) for each track and supports the insertion of such IDs in the ID3V2 tags for MP3 files. The TUID is both hashed and proprietary, and can only be read by the Gracenote system. However, the ID3V2 tags can easily be manipulated to store a TUID for one file in the ID3V2 tag for another file and therefore, the TUID alone is not a reliable identifier of the audio content in a file.
  • [0009]
    Gracenote's CDDB service also provides text matching capability that can be utilized to identify digital audio files from their file names, file paths, ID tags (titles), etc. by matching the text extracted by a client device to a metadata database of track, artist, and album names. Although this text matching utilizes user-generated spelling variants associated with each record to improve recognition, there has been no way to verify that the text matches the audio content of the recording once the recording has been separated from a compact disc and stored in a file in any format.
  • SUMMARY OF THE INVENTION
  • [0010]
    An aspect of the present invention is maximizing identification of recordings while minimizing resource usage.
  • [0011]
    Another aspect of the present invention is using multiple identification methods so that resource intensive methods, such as audio fingerprinting, are employed only when necessary.
  • [0012]
    A further aspect of the invention is minimization of processing of unidentified data.
  • [0013]
    Yet another aspect of the present invention is to use the least expensive recognition technique, with progressively more expensive recognition techniques layered onto the process until a desired confidence level is reached.
  • [0014]
    A still further aspect of the invention is validation of content-based identification of a recording by comparing text associated with an unidentified recording and text associated with identification records.
  • [0015]
    Yet another aspect of the present invention is use of recording identification methods from different sources to increase reliability.
  • [0016]
    A still further aspect of the invention is validation of content-based recording identification using fuzzy track length analysis.
  • [0017]
    Yet another aspect of the invention is automatic extraction of identification data for use in a reference database and for identification of recordings.
  • [0018]
    A still further aspect of the invention is that unidentified recordings are periodically re-run through the system to determine if recently added data or recently improved techniques will result in recognition.
  • [0019]
    The above aspects can be attained by a method of identifying recordings by extracting information about an unknown recording stored in media possessed by a user and at least one algorithmically determined fingerprint from at least one portion of the unknown recording; determining a possible identification of the unknown recording using at least one piece of the information extracted from the unknown recording and an identification database of corresponding information for reference recordings; and identifying the unknown recording when the possible identification based on each of the at least one piece of the information in combination with the at least one algorithmically determined fingerprint identifies a single reference recording with respective confidence levels. The at least one portion of the unknown recording may contain audio, video or both.
  • [0020]
    Preferably, the database is maintained by a provider of identification services which supplies unique identifiers that can be recognized only by servers under the control of the provider of identification services. The unique identifiers are associated with recordings once they have been identified. Subsequently, copies of the recordings are recognized using the unique identifiers to greatly speed up the process. The unique identifiers optionally are cached in high-speed RAM or specially indexed database tables.
  • [0021]
    When non-waveform data is not available for an unknown recording, the unknown recording is preferably identified by extracting fingerprints from at least one portion of the unknown recording using a plurality of algorithms; determining a possible identification of the unknown recording using at least two of the fingerprints extracted from the unknown recording and at least one database of correspondingly generated fingerprints for reference recordings; and identifying the unknown recording when the possible identification based on each of the fingerprints identifies a single reference recording with respective confidence levels.
  • [0022]
    Preferably, an existing database, used to identify recordings possessed by users, which does not contain fingerprint information is expanded by obtaining non-waveform data associated with a recording possessed by a user of the database; extracting at least one fingerprint from at least one portion of the recording; and storing the at least one fingerprint as identifying information for the recording, when a match is found in the database for the non-waveform data. One example is that during the process of encoding digital music files from an audio CD possessed by a user, a recognition system can be used to identify the audio CD so that fingerprints extracted during the encoding process can be directly associated with the audio CD using a unique ID system.
  • [0023]
    Recognition of recordings using either fingerprints or unique identifiers is preferably validated by other information maintained in the identification database, such as the length of the recording or a numeric identifier embedded within the recording. Information about recordings that do not pass validation or match some, but not all of the information used for identification, may be stored for later analysis of the reason for the error. If the fingerprints are obtained as described above, there may have been an error in obtaining the fingerprint. Therefore, errors may be output to an operator, or the system could correct the information stored in the database, based on recognition of patterns in the information that is stored for improper matches. For example, if a large percentage of matching fingerprints are stored, but the other information consistently does not match them, there could be an error in the fingerprint database which needs to be flagged to an operator.
  • [0024]
    The present invention includes a system for identifying recordings that includes an extraction unit to extract information about an unknown recording stored in media possessed by a user and at least one algorithmically determined fingerprint from at least one portion of the unknown recording; and an identification unit, coupled to the extraction unit, to make a possible identification of the unknown recording using at least one piece of the information extracted from the unknown recording and an identification database of corresponding information for reference recordings, and to identify the unknown recording when the possible identification based on each of the at least one piece of the information in combination with the at least one algorithmically determined fingerprint identifies a single reference recording with respective confidence levels.
  • [0025]
    The present invention also includes a system for identifying recordings that includes an extraction unit to extract fingerprints from at least one portion of an unknown recording using a plurality of algorithms, and an identification unit, coupled to said extraction unit, to make a possible identification of the unknown recording using at least two of the fingerprints extracted from the unknown recording and at least one database of correspondingly generated fingerprints for reference recordings, and to identify the unknown recording when the possible identification based on each of the fingerprints identifies a single reference recording with respective confidence levels.
  • [0026]
    In either of the systems described above, the extraction unit is typically a client unit connected by a network, such as the Internet, to at least one server as the identification unit. The client device may be a personal computer with a drive accessing the recording, a consumer electronics device with a network connection, or a server computer transmitting the unknown recording from one location to another. Furthermore, a portion of the database may be available locally and the extraction unit and identification unit may reside in the same device and share components.
  • [0027]
    The present invention also includes a system for obtaining reference information stored in a database used to identify unknown recordings, including a receiving unit to obtain non-waveform data associated with a recording possessed by a user of the database for identification of recordings possessed by the user; an extraction unit to extract at least one fingerprint from at least one portion of the recording; and a storage unit, coupled to said receiving unit and said extraction unit, to store the at least one fingerprint as identifying information for the recording, when a match is found in the database for the non-waveform data.
  • [0028]
    These together with other aspects and advantages which will be subsequently apparent, reside in the details of construction and operation as more fully hereinafter described and claimed, reference being had to the accompanying drawings forming a part hereof, wherein like numerals refer to like parts throughout.
  • BRIEF DESCRIPTION OF THE DRAWINGS
  • [0029]
    [0029]FIG. 1 is a functional block diagram of a system according to the present invention.
  • [0030]
    [0030]FIG. 2 is flowchart of a fingerprint extraction according to the present invention.
  • [0031]
    [0031]FIG. 3 is a flowchart of a method of recognizing unknown recordings.
  • [0032]
    FIGS. 4A-4C are a block diagram of a system according to the present invention.
  • DETAILED DESCRIPTION OF THE PREFERRED EMBODIMENTS
  • [0033]
    According to the present invention, a suite of identification components are provided in a system like that illustrated in FIG. 1 to facilitate analysis and identification of audio (and video) files utilizing multiple methods. Preferably, an existing database 90 containing recording identifiers and text data is combined with text-based digital audio and audio fingerprinting identification methods. Preferably, the text data in database 90 is obtained from user submissions and includes user-submitted spelling variants. One such database is available as the CDDB Music Recognition Service from Gracenote, Inc..
  • [0034]
    As illustrated in FIG. 1, a recording 100 is accessed by client device 110 via any conventional method, such as reading a digital audio file from a hard drive or a compact disc. Information is extracted from recording 100 and associated information (metadata). Fingerprints are extracted from recording 100, as described in more detail below. The information that is extracted from the metadata includes the duration of the recording which is the track length (from the TOC) for a CD track, the filename and ID3 tag if the recording is in an MP3 file, and the table of contents (TOC) data if the recording is on a CD. If the file containing the recording was produced by a client device operating according to the invention, a unique ID will be extracted from the ID3 file, but initially it will be assumed that information is not available.
  • [0035]
    In an exemplary embodiment, the extracted information is sent from client 110 to server 120 to determine a possible identification of the unknown recording using at least one piece of the information extracted from recording 100 and a database 130 of correspondingly generated fingerprints for reference recordings. If text or a unique ID were extracted, an attempt is made to find a match. If a match is found using the text or unique ID, at least one algorithmically determined fingerprint is compared with the fingerprint(s) stored in the matching records to determine whether there is a single reference recording that matches the information extracted from recording 100 with respective confidence levels for each item of information that matches. If no matches can be found based on text and unique ID, an attempt is made to identify the a single reference recording using at least two of the fingerprints extracted from recording 100. If a single reference recording is located using either method, preferably the duration of recording 100 is compared with the duration of the single reference recording as a final validation step.
  • [0036]
    Preferably related metadata is used for validation of the match obtained by fingerprint recognition. Like any recognition system fingerprinting can produce erroneous results. Without a validation component such an error can propagate throughout the system and return erroneous data to large percentages of users. The use of validation criteria such as track length comparison enables the system to catch potential errors and flag them for validation.
  • [0037]
    A system according to the present invention preferably includes custom result reporting and flexible administrative interfaces 130 to enable weighting of various identification methods and the order of their engagement. Analysis of successful match rates for specific identification methods allows an administrator to manipulate the identifying criteria for each component to maximize the identification probability. A system according to the present invention preferably incorporates usage data from over 28 million users utilizing the CDDB database via Gracenote Data Services division, to help guide results 140.
  • [0038]
    The flexibility of a system according to the present invention allows different configurations to be used for identifying recordings in different environments. An application that monitors streaming audio, for example, requires a very different system and solution architecture than one that identifies files in a peer-to-peer system, or one that identifies analog input. However the present invention can be configured for identification of recordings in each of these situations.
  • [0039]
    A system according to the present invention maximizes identification while minimizing resource usage. The use of multiple identification methods ensures that more resource intensive methods, such as audio fingerprinting are employed only when necessary. The use of multiple audio fingerprinting technologies reduces data collision and covers any “blind spots” in a given audio fingerprint technology. The “blind spots” found in single source fingerprinting systems, are avoided by using multiple sources for different fingerprinting techniques. This also provides the ability to fine tune deployment for specific target applications.
  • [0040]
    Preferably, fingerprints are obtained using multiple fingerprint recognition services using the method illustrated in FIG. 2. This increases the ability of the system to accurately recognize recordings of various types.
  • [0041]
    As illustrated in FIG. 2, when unidentified (unknown) recording 100 is accessed by fingerprint extraction client 110, if possible conventional TOC/file recognition is performed by recognition system 210 and results 220 are returned to fingerprint client 110. Results 220 include a unique identifier (TUID) that points into a master metadata database (not shown in FIG. 2), if the TUID is found. Recording 100 is also processed by fingerprint extractor 230 using at least one and preferably several different algorithmically derived fingerprint extraction systems to obtain fingerprint(s) which are stored in fingerprint/ID send cache 240. As described below in more detail, instructions are received regarding when fingerprint uploader 250 should send the fingerprints to fingerprint recognition server 120.
  • [0042]
    In fingerprint recognition server 120, the fingerprints transmitted by fingerprint uploader 250 are initially stored in fingerprint receive cache 260. The fingerprints then undergo fingerprint validation 270 using an algorithmic comparator that attempts to cross-correlate fingerprints for a recording with fingerprints uploaded and extracted by different end users. If it is found that the fingerprints are substantially similar, they would be validated. This is not the only method that's available for validation, but serves as one example of a process that could be used to reject bad data.
  • [0043]
    In this embodiment, fingerprints that are determined to be valid and related undergo stitching 280. For example, if fingerprints are taken from 30 second segments of the recording, the fingerprints are assembled into a continuous fingerprint stream. This could simplify recognition of segments of the recording. The resulting fingerprints are stored in fingerprint database 290 associated with existing database 90 (FIG. 1).
  • [0044]
    The CDDB database has in part been generated through user submissions to create a metadata database with over 12 million tracks and 900,000 albums as of mid-2002. This database contains both basic metadata (artist, album, and track names) as well as extended data (genre, label, etc.).
  • [0045]
    A similar distributed collection method may be utilized in the creation of a waveform database using the system illustrated in FIG. 1. In the case where recording 100 is a raw audio waveform, e.g., when a CD is encoded into another format, such as an MP3 file, client device 110 obtains non-waveform data associated with recording 100 which is possessed by a user of database 90 and executes extraction algorithm(s) to extract fingerprints from at least one portion of the recording. The fingerprints are then sent to server 120 with a unique ID, preferably derived from the TOC of the CD. When the unique ID is available, i.e., , when a match is found in the database for the non-waveform data, server 120 is able to associate the appropriate metadata in database 90 and the fingerprint(s) with same level of accuracy as identification of CDs by the existing database 90 which is provided for identification of recordings possessed by users. Fingerprints dynamically gathered in this manner may be sent to a fingerprint collection server (not shown in FIG. 1) which would accumulate fingerprints from authenticated clients, as described in more detail below, prior to storing the at least one fingerprint as identifying information for the recording.
  • [0046]
    Multiple fingerprint gathering extractors can also be run over a set of static waveforms from a commercial encoder such as Loudeye or Muse. The challenge with this approach is associating the fingerprints with the appropriate metadata. The method described above enables audio fingerprints to be logically associated with parent records and associated back to the original audio source. In the preferred embodiment, the unique ID provides differentiation between live and studio versions of the same song while simultaneously linking those records to the same artist and their respective albums.
  • [0047]
    Preferably server(s) 120 store information in a parallel record set that are linked with unique IDs. When client 110 asks server 120 to recognize media (CD, digital audio file, video file) server 120 may also return a record about how fingerprints should be gathered for this particular CD. This is called the Gathering Instructions Record (GIR). The GIR may include a set of instructions that the remote fingerprint gathering code follows. The record may be pre-computed in off hours or may be dynamically computed at the time of recognition.
  • [0048]
    Server 120 may use information it knows about the popularity of a CD to drive decisions about gathering. Everything about a rare CD could be gathered, because the opportunity to get the fingerprints would not want to be missed (even if it was somewhat burdensome to the user). The opposite situation could be true for a very popular CD. The load may be distributed across many users so that they would not even notice that any work for fingerprint gathering was occurring.
  • [0049]
    The rules and procedures for building the GIR may be manual, automated and may change over time. They may also be applied uniquely to specific users, applications or geographic locations.
  • [0050]
    In one embodiment, the server dynamically gathers fingerprints by modifying the GIR to remove fingerprints that have been gathered previously. The frequency of updating GIRs may vary from instant to delays of days, weeks or months. Some example instructions that may be included in the GIR are:
  • [0051]
    A list of track and segments to be gathered and their priority.
  • [0052]
    A fingerprint generator algorithm to use.
  • [0053]
    Parameters that tell the fingerprint generator how to process the fingerprint, such as:
  • [0054]
    Frequency of audio samples
  • [0055]
    Bands of the frequency domain to process
  • [0056]
    Resolution of the fingerprint
  • [0057]
    Desired Quality of Audio
  • [0058]
    When to do the fingerprint gathering, such as
  • [0059]
    Before encoding the track
  • [0060]
    After encoding the track
  • [0061]
    In parallel with encoding the track
  • [0062]
    Instructions for caching the fingerprint and when to transmit it back to the server, such as
  • [0063]
    Before encoding the track
  • [0064]
    After encoding the track
  • [0065]
    After the CD has been fully encoded
  • [0066]
    When the communication channel back to the server is not busy
  • [0067]
    When the next CD is looked up
  • [0068]
    When a group of fingerprints is ready for transmission
  • [0069]
    Instructions to take CPU power into the process so as to not overload the computer
  • [0070]
    Preferably, the system attempts to improve the quality of the fingerprints during operation. Quality of the source signal, the parameters used for fingerprinting, along with improvements in the fingerprinting algorithms will result in a complex quality matrix that is used by server 120 to determine what fingerprints to gather if higher quality is available. An example of source quality is provided below: Preferably, database 90 or a similar database maintained by fingerprint collection server(s) stores the source quality for fingerprints stored in the database, so that when a fingerprint from higher quality source is available, the fingerprint may be replaced.
    Source Quality Table
    Name Bit Rate Compression Error Correction Quality Index
    CD_Audio_HEC 44100 kbps None Hardware 1
    CD_Audio_SEC 44100 kbps None Software 2
    CD_Audio 44100 kbps None None 3
    CDR_Audio 44100 kbps None None 4
    CDR_Made_From_MP3 44100 kbs mp3 None 5
    MP3_File  160 kbps mp3 None 6
  • [0071]
    Fingerprints dynamically gathered may contain information that helps validate quality. Information such as errors while reading from the media may be sent up to the fingerprint collector. The system may reject fingerprints that had high error rates from the source media.
  • [0072]
    As noted above, instead of immediately storing a fingerprint, multiple fingerprints for a recording may be gathered in by a fingerprint collection server prior to being added to the database. These fingerprints may be compared algorithmically to determine their correlation. If correlation is not adequate then additional fingerprints may be gathered until adequate correlation is achieved and one of the fingerprints or a composite fingerprint is stored in the database. This prevents bad fingerprints from becoming part of the database.
  • [0073]
    Stitching of the segmented fingerprints may be necessary since slight variations in timing could result in overlap of the fingerprints. Algorithmic stitching could result in a higher quality continuous fingerprint. Simple stitching appends segmented fingerprints in order of appearance in the recording. Complex stitching could involve scaling different qualities of fingerprints to the lowest common denominator and then appending them in order of their appearance in the recording. Preferably some form of mathematical fitting is utilized if the fingerprint segmentation contains jitter, so that appending is a fuzzy process rather simple addition of the datastream.
  • [0074]
    One example of audio fingerprinting that can be used is described in the U.S. patent application entitled Automatic Identification of Sound Recordings, filed by Maxwell Wells et al. on Jul. 22, 2002 and incorporated herein by reference. However, any known algorithmically derived fingerprinting technique may be used, not only for digital audio, but also video, TV programs (both analog and digital) and DVDs. Appropriate identifiers and recognition techniques will be used for the media to be recognized in a particular application.
  • [0075]
    The present invention provides great flexibility and can be utilized for a wide variety of environments, including MP3 recognition in a peer-to-peer environment, or identification of an audio stream for monitoring and reporting purposes. No other solution is known to use multiple recognition components; so it is the only solution that can be customized to meet the needs of any audio (or video) recognition application.
  • [0076]
    A functional description for a deployment of the present invention in a peer-to-peer application will be described below with reference to FIG. 3. In this embodiment, audio files are identified before providing public access to them, to determine if the files are allowed in the system, a process known as “filter-in”.
  • [0077]
    Client device 110 (FIG. 1) extracts information 310 (FIG. 3) from an audio file at the time of upload to server 120 (FIG. 1). The extracted information preferably includes non-waveform data, such as a unique ID, ID3 tag, filename text data, track duration, etc. and fingerprint(s) extracted from the recording and sent to server 120 for recognition.
  • [0078]
    The initial match 320 is performed against the unique ID, if present. Use of Gracenote's TUID enables a match to be returned with 99.9% accuracy. This is also the least resource intensive recognition method and can achieve very fast recognition rates. If the unique ID is present the system moves to the validation stage. If no unique ID is present the system attempts identification using the next recognition methods 330.
  • [0079]
    In this embodiment, text-based identification is tried next, using a metadata database, such as the Gracenote CDDB service which contains over 900,000 albums and over 12 million songs. Text matching utilizes available text, such as the filename, file path or text within the ID3 tag for MP3 files, to provide a set of data from which to attempt recognition. If an acceptable match is returned, the system moves to the validation stage. If a successful match is not returned, the system attempts identification utilizing the next recognition method.
  • [0080]
    The next step is fingerprint identification, in this case using audio fingerprints. The fingerprints from an unknown recording are compared to the fingerprints in database 90 for reference recordings, one fingerprint at a time (or in parallel using different processors for different fingerprints). Each fingerprinting technology returns a match and a level of confidence. If a single reference recording has acceptable confidence levels the system moves to the validation stage. If an unsuccessful match is returned the system can, depending on the target application, ask the user for validation of the most likely result or it can return a “no match found” result.
  • [0081]
    Validation is a key component to any successful recognition system. Preferably, key file attributes such as the duration of the recoding, are used to validate that a file is what the recognition system says it is by comparing an extracted length of the unknown recording with a stored length of the single reference recording.
  • [0082]
    Preferably heuristic and voting algorithms 340 are used to determine if a match is what the system says it is. This self-monitoring reduces the possibility that the system returns inaccurate data that pollutes the system. The heuristics may be manually controlled or algorithmically controlled to produce the best match. These heuristics may also be used to determine which recognition techniques to apply and in what sequence.
  • [0083]
    The administrator of each application can determine the level of accuracy needed by each stage (or component) of the system, and therefore has explicit control in optimizing the system. For example, if a 90% aggregate match is required the system administrator can use administrative interfaces 130 to adjust the levels of acceptable return to 90% and a successful result will not be generated unless that threshold is met. The administrator can also set result levels for each component. For example, a 99% text match can be required but only an 85% audio fingerprint match.
  • [0084]
    Once a successful identification is returned the file will be retagged 350 with the unique ID allowing for population of the file with the correct ID throughout the system. As a result, future identification of the file will require the least resource intensive recognition method.
  • [0085]
    The unique ID (TUID) assigned to the file is then matched 360 against a list 370 of TUIDs populated through the submission of Title/Artist pairs 370 by labels, publishers, and content owners of those files allowed in the system. In one embodiment, if the TUID is present in the database, the file is allowed to be shared, but if the TUID is not present in the database, the file is blocked. In another embodiment, if the TUID is present in the database, the file is blocked. Either of these embodiments could be applied to files recognized as they are accessed by a user, or transmitted from one computer to another.
  • [0086]
    As illustrated in FIG. 4A, an embodiment of the present invention uses a plurality of related databases. Master metadata database 410 contains information on title, artist/author name, owner name and date. Related databases include audio fingerprint database 430 and video fingerprint database 440 which form fingerprint database 290 (FIG. 2). Also included are track length/TOC database 450, text database 460, and hash ID database 470 and guaranteed unique ID database 480.
  • [0087]
    As illustrated in FIG. 4B, when unidentified (unknown) recording 100 is accessed by client device 110, information is extracted, including fingerprints 540, 550, metadata 560 and unique ID 570, if present. In addition, the duration 580 of the recording is determined and a numerical hash 590 is calculated. The extracted fingerprints are compared with fingerprints 600, 610. Similarly, matching 620, 630, 640 is performed on the numerical hash, text and unique ID. If a reference recording is located, validation is performed by comparing the duration of unidentified recording 100 with the duration of the reference recording. Results 660-710 with a level of confidence for each method of comparison is supplied to result aggregator 730.
  • [0088]
    If no reference recording is found 750 matching unidentified recording 100, the extracted information 540-590 and results are stored in unrecognized holding bin 760 for periodic resubmission to recognition server 120 (FIGS. 2 & 4B). In this embodiment, if a reference recording is located 770 with a low aggregate confidence level, post recognition processing 780 is performed by applying heuristics 790, or a manual review 810, e.g., by presenting one or more possible matches to the user and receiving the user's selection in response. The results of such user selections may be included in the heuristics stored in heuristics database 820. If post recognition processing 780 results in identification of a single reference recording or result aggregator 730 outputs recognized results 770 with a high aggregate confidence level, the hash ID is generated 810 and sent to hash database 480 and client device 110, so that the hash and unique ID (TUID) can be stored in the ID3 tag, if a file is being created.
  • [0089]
    In one embodiment, the system learns by watching errors in repeated attempts at recognition of similar files to improve its results. It also may receive manual stimulus from users who indicate that there are errors in the results. This allows recognition to be continuously validated over time. For example a file could be recognized by a system according to the invention, then over time the system determines that recognition of that file was flawed, and indicates to an operator that there was something wrong. In another embodiment, the system determines what is wrong by monitoring non-fingerprint based data and changing the recognition results accordingly.
  • [0090]
    The present invention can be utilized to identify any audio content for tracking purposes. Digital audio streams, analog inputs or local audio files, can all be tracked. Such a tracking system could be a server side tracking system deployed at the point of audio delivery and integrated with a reporting, digital rights management (DRM) system, or rights payment system. If the audio content being tracked was from a non-participating third party a client version of the system may be deployed to monitor the content being distributed. In either case, multiple identification methods would be utilized to ensure the highest rate of accuracy.
  • [0091]
    Utilizing waveform recognition as a digital rights management component is possible, and can be deployed to compare user created digital audio files with lists of approved content. This enables a filter-in approach within a peer-to-peer file sharing architecture such as the one described above.
  • [0092]
    Audio fingerprinting technologies can be used as an anti-piracy tool, and can be customized to the type of audio being investigated. In the case of pirated CDs, the Gracenote's CDDB CD service may be utilized to provide table of content (TOC) recognition to augment audio fingerprinting technologies.
  • [0093]
    Identification is the enabling component to deliver value-added services. Without explicit knowledge of the content being distributed it is impossible to distribute value-added content and services that relates to that audio content.
  • [0094]
    The many features and advantages of the invention are apparent from the detailed specification and, thus, it is intended by the appended claims to cover all such features and advantages of the invention that fall within the true spirit and scope of the invention. Further, since numerous modifications and changes will readily occur to those skilled in the art, it is not desired to limit the invention to the exact construction and operation illustrated and described, and accordingly all suitable modifications and equivalents may be resorted to, falling within the scope of the invention. For example the system and method have been described as using a unique identifier. However, a hashed identifier could be used instead.
Patent Citations
Cited PatentFiling datePublication dateApplicantTitle
US4843562 *24 Jun 198727 Jun 1989Broadcast Data Systems Limited PartnershipBroadcast information classification system and method
US5751672 *26 Jul 199512 May 1998Sony CorporationCompact disc changer utilizing disc database
US5884298 *20 Dec 199616 Mar 1999Cygnet Storage Solutions, Inc.Method for accessing and updating a library of optical discs
US5918223 *21 Jul 199729 Jun 1999Muscle FishMethod and article of manufacture for content-based analysis, storage, retrieval, and segmentation of audio information
US5925843 *12 Feb 199720 Jul 1999Virtual Music Entertainment, Inc.Song identification and synchronization
US5987525 *15 Apr 199716 Nov 1999Cddb, Inc.Network delivery of interactive entertainment synchronized to playback of audio recordings
US6061680 *16 Jul 19999 May 2000Cddb, Inc.Method and system for finding approximate matches in database
US6154773 *15 Apr 199828 Nov 2000Cddb, Inc.Network delivery of interactive entertainment complementing audio recordings
US6161132 *24 Aug 199912 Dec 2000Cddb, Inc.System for synchronizing playback of recordings and display by networked computer systems
US6230192 *16 Jul 19998 May 2001Cddb, Inc.Method and system for accessing remote data based on playback of recordings
US6230207 *16 Jul 19998 May 2001Cddb, Inc.Network delivery of interactive entertainment synchronized to playback of audio recordings
US6240459 *16 Jul 199929 May 2001Cddb, Inc.Network delivery of interactive entertainment synchronized to playback of audio recordings
US6304523 *5 Jan 199916 Oct 2001Openglobe, Inc.Playback device having text display and communication with remote database of titles
US6330593 *24 Aug 199911 Dec 2001Cddb Inc.System for collecting use data related to playback of recordings
US6345256 *1 Dec 19985 Feb 2002International Business Machines CorporationAutomated method and apparatus to package digital content for electronic distribution using the identity of the source content
US6400996 *1 Feb 19994 Jun 2002Steven M. HoffbergAdaptive pattern recognition based control system and method
US6453252 *15 May 200017 Sep 2002Creative Technology Ltd.Process for identifying audio content
US6505160 *2 May 20007 Jan 2003Digimarc CorporationConnected audio and other media objects
US6829368 *24 Jan 20017 Dec 2004Digimarc CorporationEstablishing and interacting with on-line media collections using identifiers in media signals
US6931451 *28 Mar 200016 Aug 2005Gotuit Media Corp.Systems and methods for modifying broadcast programming
US6941275 *5 Oct 20006 Sep 2005Remi SwierczekMusic identification system
US6990453 *20 Apr 200124 Jan 2006Landmark Digital Services LlcSystem and methods for recognizing sound and music signals in high noise and distortion
US7174293 *13 Jul 20016 Feb 2007Iceberg Industries LlcAudio identification system and method
US7194752 *19 Oct 199920 Mar 2007Iceberg Industries, LlcMethod and apparatus for automatically recognizing input audio and/or video streams
US7302574 *21 Jun 200127 Nov 2007Digimarc CorporationContent identifiers triggering corresponding responses through collaborative processing
US7328153 *22 Jul 20025 Feb 2008Gracenote, Inc.Automatic identification of sound recordings
US7349552 *6 Jan 200325 Mar 2008Digimarc CorporationConnected audio and other media objects
US7415129 *10 Jul 200719 Aug 2008Digimarc CorporationProviding reports associated with video and audio content
US7461136 *2 Nov 20052 Dec 2008Digimarc CorporationInternet linking from audio and image content
US7548851 *11 Oct 200016 Jun 2009Jack LauDigital multimedia jukebox
US7587602 *11 Jan 20068 Sep 2009Digimarc CorporationMethods and devices responsive to ambient audio
US7590259 *29 Oct 200715 Sep 2009Digimarc CorporationDeriving attributes from images, audio or video to obtain metadata
US8468357 *9 Mar 201018 Jun 2013Gracenote, Inc.Multiple step identification of recordings
US20010004338 *30 Oct 199721 Jun 2001Sony Electronics Inc.Compact disc changer utilizing disc database
US20020033844 *11 Sep 200121 Mar 2002Levy Kenneth L.Content sensitive connected content
US20020052885 *11 Sep 20012 May 2002Levy Kenneth L.Using embedded data with file sharing
US20020059208 *26 Jul 200116 May 2002Mototsugu AbeInformation providing apparatus and method, and recording medium
US20020083060 *20 Apr 200127 Jun 2002Wang Avery Li-ChunSystem and methods for recognizing sound and music signals in high noise and distortion
US20020116195 *21 Feb 200222 Aug 2002International Business Machines CorporationSystem for selling a product utilizing audio content identification
US20020133499 *20 Aug 200119 Sep 2002Sean WardSystem and method for acoustic fingerprinting
US20030037010 *3 Apr 200220 Feb 2003Audible Magic, Inc.Copyright detection and protection system and method
US20030061490 *23 Sep 200227 Mar 2003Abajian Aram ChristianMethod for identifying copyright infringement violations by fingerprint detection
US20030105739 *11 Oct 20025 Jun 2003Hassane EssafiMethod and a system for identifying and verifying the content of multimedia documents
US20040034650 *15 Aug 200219 Feb 2004Microsoft CorporationMedia identifier registry
US20080052783 *26 Oct 200728 Feb 2008Levy Kenneth LUsing object identifiers with content distribution
US20090158318 *9 Dec 200818 Jun 2009Levy Kenneth LMedia Methods and Systems
US20100281545 *13 Jul 20104 Nov 2010Levy Kenneth LUsing Embedded Data with File Sharing
Referenced by
Citing PatentFiling datePublication dateApplicantTitle
US697345110 Oct 20036 Dec 2005Sony CorporationMedium content identification
US699353230 May 200131 Jan 2006Microsoft CorporationAuto playlist generator
US702442411 Mar 20054 Apr 2006Microsoft CorporationAuto playlist generator
US708239425 Jun 200225 Jul 2006Microsoft CorporationNoise-robust feature extraction using multi-layer principal component analysis
US724871520 Sep 200124 Jul 2007Digimarc CorporationDigitally watermarking physical media
US7269596 *17 Oct 200311 Sep 2007Sony United Kingdom LimitedAudio and/or video generation apparatus
US727776624 Oct 20002 Oct 2007Moodlogic, Inc.Method and system for analyzing digital audio files
US729603111 Mar 200513 Nov 2007Microsoft CorporationAuto playlist generator
US731357131 Oct 200525 Dec 2007Microsoft CorporationAuto playlist generator
US731359118 Jul 200325 Dec 2007Microsoft CorporationMethods, computer readable mediums and systems for requesting, retrieving and delivering metadata pages
US7334023 *26 Mar 200319 Feb 2008Kabushiki Kaisha ToshibaData transfer scheme for reducing network load using general purpose browser on client side
US7359900 *29 Jul 200315 Apr 2008All Media Guide, LlcDigital audio track set recognition system
US74285728 Sep 200523 Sep 2008Microsoft CorporationTransferring metadata to a client
US744097521 Dec 200521 Oct 2008Musicgiants, Inc.Unified media collection system
US745107830 Dec 200411 Nov 2008All Media Guide, LlcMethods and apparatus for identifying media objects
US747773921 Jan 200313 Jan 2009Gracenote, Inc.Efficient storage of fingerprints
US752650623 Sep 200528 Apr 2009Microsoft CorporationInterlinking sports and television program listing metadata
US754893430 Mar 200616 Jun 2009Microsoft CorporationAuto playlist generator
US754905211 Feb 200216 Jun 2009Gracenote, Inc.Generating and matching hashes of multimedia content
US7549175 *17 Apr 200716 Jun 2009Sony CorporationRecording medium, recording method, recording apparatus, reproduction apparatus, data transmission method, and server device
US756789930 Dec 200428 Jul 2009All Media Guide, LlcMethods and apparatus for audio recognition
US7574451 *2 Nov 200411 Aug 2009Microsoft CorporationSystem and method for speeding up database lookups for multiple synchronized data streams
US764407721 Oct 20045 Jan 2010Microsoft CorporationMethods, computer readable mediums and systems for linking related data from at least two data sources based upon a scoring algorithm
US764712822 Apr 200512 Jan 2010Microsoft CorporationMethods, computer-readable media, and data structures for building an authoritative database of digital audio identifier elements and identifying media items
US766805911 Jul 200523 Feb 2010Sony CorporationCommercial/non-commercial medium test
US767287310 Sep 20042 Mar 2010Yahoo! Inc.Music purchasing and playing system and method
US768521030 Dec 200523 Mar 2010Microsoft CorporationMedia discovery and curation of playlists
US77065709 Feb 200927 Apr 2010Digimarc CorporationEncoding and decoding auxiliary signals
US77072212 Apr 200327 Apr 2010Yahoo! Inc.Associating and linking compact disc metadata
US771156427 Jun 20024 May 2010Digimarc CorporationConnected audio and other media objects
US77118389 Nov 20004 May 2010Yahoo! Inc.Internet radio and broadcast method
US772085222 Jun 200618 May 2010Yahoo! Inc.Information retrieval engine
US774786429 Jun 200629 Jun 2010Mircosoft CorporationDVD identification and managed copy authorization
US776151318 May 200420 Jul 2010Sony CorporationInformation recording device, information recording method, and information recording program
US77886848 Oct 200331 Aug 2010Verance CorporationMedia monitoring, management and information system
US784913112 May 20067 Dec 2010Gracenote, Inc.Method of enhancing rendering of a content item, client system and server system
US785334416 Aug 200714 Dec 2010Rovi Technologies CorporationMethod and system for analyzing ditigal audio files
US78774085 Feb 200825 Jan 2011Rovi Technologies CorporationDigital audio track set recognition system
US789037424 Oct 200015 Feb 2011Rovi Technologies CorporationSystem and method for presenting music to consumers
US790450321 Aug 20018 Mar 2011Gracenote, Inc.Method of enhancing rendering of content item, client system and server system
US79212967 May 20075 Apr 2011Gracenote, Inc.Generating and matching hashes of multimedia content
US7958485 *21 Nov 20077 Jun 2011General Electric CompanyMethods and systems for managing content dependency deployment
US797946411 Apr 200712 Jul 2011Motion Picture Laboratories, Inc.Associating rights to multimedia content
US800525825 Sep 200923 Aug 2011Verance CorporationMethods and apparatus for enhancing the robustness of watermark extraction from digital host content
US800572426 Mar 200323 Aug 2011Yahoo! Inc.Relationship discovery engine
US806925518 Jun 200329 Nov 2011AT&T Intellectual Property I, .L.P.Apparatus and method for aggregating disparate storage on consumer electronics devices
US812184323 Apr 200721 Feb 2012Digimarc CorporationFingerprint methods and systems for media signals
US8131708 *30 Oct 20086 Mar 2012Vobile, Inc.Methods and systems for monitoring and tracking videos on the internet
US815009623 Mar 20063 Apr 2012Digimarc CorporationVideo fingerprinting to identify video content
US817027327 Apr 20101 May 2012Digimarc CorporationEncoding and decoding auxiliary signals
US825993819 Jun 20094 Sep 2012Verance CorporationEfficient and secure forensic marking in compressed
US827133330 Oct 200118 Sep 2012Yahoo! Inc.Content-related wallpaper
US828010319 Nov 20102 Oct 2012Verance CorporationSystem reactions to the detection of embedded watermarks in a digital host content
US831623825 Oct 200620 Nov 2012Verizon Patent And Licensing Inc.Method and system for providing image processing to track digital information
US834034828 Sep 201125 Dec 2012Verance CorporationMethods and apparatus for thwarting watermark detection circumvention
US83465676 Aug 20121 Jan 2013Verance CorporationEfficient and secure forensic marking in compressed domain
US835225920 Jun 20098 Jan 2013Rovi Technologies CorporationMethods and apparatus for audio recognition
US835233130 Apr 20018 Jan 2013Yahoo! Inc.Relationship discovery engine
US845108630 Jan 201228 May 2013Verance CorporationRemote control signaling using audio watermarks
US8458156 *18 May 20124 Jun 2013Google Inc.Learning common spelling errors through content matching
US84683579 Mar 201018 Jun 2013Gracenote, Inc.Multiple step identification of recordings
US848342320 Apr 20069 Jul 2013Sony Pictures Entertainment Inc.Fingerprinting of data
US8490131 *5 Nov 200916 Jul 2013Sony CorporationAutomatic capture of data for acquisition of metadata
US8495075 *8 Mar 200623 Jul 2013Apple Inc.Fuzzy string matching of media meta-data
US85334813 Nov 201110 Sep 2013Verance CorporationExtraction of embedded watermarks from a host content based on extrapolation techniques
US85380664 Sep 201217 Sep 2013Verance CorporationAsymmetric watermark embedding/extraction
US854930729 Aug 20111 Oct 2013Verance CorporationForensic marking using a common customization function
US859531519 Oct 201126 Nov 2013At&T Intellectual Property I, L.P.Apparatus and method for aggregating disparate storage on consumer electronics devices
US860150420 Jun 20033 Dec 2013Verance CorporationSecure tracking system and method for video program content
US86151043 Nov 201124 Dec 2013Verance CorporationWatermark extraction based on tentative watermarks
US8615506 *27 Jan 201224 Dec 2013Vobile, Inc.Methods and systems for monitoring and tracking videos on the internet
US862096711 Jun 200931 Dec 2013Rovi Technologies CorporationManaging metadata for occurrences of a recording
US867740030 Sep 200918 Mar 2014United Video Properties, Inc.Systems and methods for identifying audio content using an interactive media guidance application
US868197817 Dec 201225 Mar 2014Verance CorporationEfficient and secure forensic marking in compressed domain
US86820263 Nov 201125 Mar 2014Verance CorporationEfficient extraction of embedded watermarks in the presence of host content distortions
US868933727 Feb 20071 Apr 2014Vobile, Inc.Systems and methods of fingerprinting and identifying video objects
US8700641 *1 Aug 201115 Apr 2014Google Inc.Detecting repeating content in broadcast media
US872630413 Sep 201213 May 2014Verance CorporationTime varying evaluation of multimedia content
US873835419 Jun 200927 May 2014Microsoft CorporationTrans-lingual representation of text documents
US874540323 Nov 20113 Jun 2014Verance CorporationEnhanced content management based on watermark extraction records
US874540420 Nov 20123 Jun 2014Verance CorporationPre-processed information embedding system
US87819677 Jul 200615 Jul 2014Verance CorporationWatermarking in an encrypted domain
US879178924 May 201329 Jul 2014Verance CorporationRemote control signaling using audio watermarks
US880651710 May 201012 Aug 2014Verance CorporationMedia monitoring, management and information system
US88116554 Sep 201219 Aug 2014Verance CorporationCircumvention of watermark analysis in a host content
US88389775 Apr 201116 Sep 2014Verance CorporationWatermark extraction and content screening in a networked environment
US88389785 Apr 201116 Sep 2014Verance CorporationContent access management using extracted watermark information
US886922213 Sep 201221 Oct 2014Verance CorporationSecond screen content
US888653113 Jan 201011 Nov 2014Rovi Technologies CorporationApparatus and method for generating an audio fingerprint and using a two-stage query
US89183828 May 201323 Dec 2014Google Inc.Learning common spelling errors through content matching
US891842813 Mar 201223 Dec 2014United Video Properties, Inc.Systems and methods for audio asset storage and management
US89235483 Nov 201130 Dec 2014Verance CorporationExtraction of embedded watermarks from a host content using a plurality of tentative watermarks
US89770671 Apr 201310 Mar 2015Google Inc.Audio identification using wavelet-based signatures
US900948226 Sep 201314 Apr 2015Verance CorporationForensic marking using a common customization function
US905523919 Jul 20079 Jun 2015Verance CorporationSignal continuity assessment using embedded watermarks
US9069771 *8 Dec 200930 Jun 2015Xerox CorporationMusic recognition method and system based on socialized music server
US91069648 Feb 201311 Aug 2015Verance CorporationEnhanced content distribution using advertisements
US91172702 Jun 201425 Aug 2015Verance CorporationPre-processed information embedding system
US915300615 Aug 20146 Oct 2015Verance CorporationCircumvention of watermark analysis in a host content
US918995528 Jul 201417 Nov 2015Verance CorporationRemote control signaling using audio watermarks
US920833425 Oct 20138 Dec 2015Verance CorporationContent management using multiple abstraction layers
US925154923 Jul 20132 Feb 2016Verance CorporationWatermark extractor enhancements based on payload ranking
US926279414 Mar 201416 Feb 2016Verance CorporationTransactional video marking system
US9282346 *27 Dec 20138 Mar 2016Turner Broadcasting System, Inc.Method and system for automatic content recognition (ACR) integration for smartTVs and mobile communication devices
US932390213 Dec 201126 Apr 2016Verance CorporationConditional access using embedded watermarks
US934915127 Jun 201324 May 2016Sony CorporationFingerprinting of data
US936812316 Oct 201214 Jun 2016The Nielsen Company (Us), LlcMethods and apparatus to perform audio watermark detection and extraction
US20020023123 *26 Jul 199921 Feb 2002Justin P. MadisonGeographic data locator
US20020028000 *21 Jun 20017 Mar 2002Conwell William Y.Content identifiers triggering corresponding responses through collaborative processing
US20020095429 *14 Jan 200218 Jul 2002Lg Electronics Inc.Method of generating digital item for an electronic commerce activities
US20020111993 *9 Feb 200115 Aug 2002Reed Erik JamesSystem and method for detecting and verifying digitized content over a computer network
US20020126872 *19 Dec 200112 Sep 2002Brunk Hugh L.Method, apparatus and programs for generating and utilizing content signatures
US20020146148 *20 Sep 200110 Oct 2002Levy Kenneth L.Digitally watermarking physical media
US20020157099 *12 Jul 200124 Oct 2002Schrader Joseph A.Enhanced television service
US20020157101 *12 Jul 200124 Oct 2002Schrader Joseph A.System for creating and delivering enhanced television services
US20020178410 *11 Feb 200228 Nov 2002Haitsma Jaap AndreGenerating and matching hashes of multimedia content
US20030021441 *27 Jun 200230 Jan 2003Levy Kenneth L.Connected audio and other media objects
US20030046399 *10 Jul 20016 Mar 2003Jeffrey BoulterOnline playback system with community bias
US20030061490 *23 Sep 200227 Mar 2003Abajian Aram ChristianMethod for identifying copyright infringement violations by fingerprint detection
US20030167173 *6 Jan 20034 Sep 2003Levy Kenneth L.Connected audio and other media objects
US20030174861 *6 Jan 200318 Sep 2003Levy Kenneth L.Connected audio and other media objects
US20030187960 *26 Mar 20032 Oct 2003Kabushiki Kaisha ToshibaData transfer scheme for reducing network load using general purpose browser on client side
US20030229537 *26 Mar 200311 Dec 2003Dunning Ted E.Relationship discovery engine
US20030236661 *25 Jun 200225 Dec 2003Chris BurgesSystem and method for noise-robust feature extraction
US20040009763 *20 Jun 200315 Jan 2004Stone Chris L.Secure tracking system and method for video program content
US20040030725 *11 Jul 200312 Feb 2004Pioneer CorporationInformation reproducing and recording apparatus, method for reproducing and recording information and information recorded medium
US20040034441 *16 Aug 200219 Feb 2004Malcolm EatonSystem and method for creating an index of audio tracks
US20040073916 *8 Oct 200315 Apr 2004Verance CorporationMedia monitoring, management and information system
US20040085342 *17 Oct 20036 May 2004Williams Michael JohnAudio and/or video generation apparatus
US20040249859 *15 Mar 20049 Dec 2004Relatable, LlcSystem and method for fingerprint based media recognition
US20050010671 *18 Jun 200313 Jan 2005Sbc Knowledge Ventures, L.P.Apparatus and method for aggregating disparate storage on consumer electronics devices
US20050015551 *18 Jul 200320 Jan 2005Microsoft CorporationMethods, computer readable mediums and systems for requesting, retrieving and delivering metadata pages
US20050027689 *29 Jul 20033 Feb 2005Aec One Stop Group, Inc.Digital audio track set recognition system
US20050091268 *3 Dec 200428 Apr 2005Meyer Joel R.Systems and methods of managing audio and other media
US20050187968 *28 Apr 200525 Aug 2005Dunning Ted E.File splitting, scalable coding, and asynchronous transmission in streamed data transfer
US20050197906 *10 Sep 20048 Sep 2005Kindig Bradley D.Music purchasing and playing system and method
US20050198061 *17 Feb 20058 Sep 2005David RobinsonProcess and product for selectively processing data accesses
US20050229204 *22 Apr 200313 Oct 2005Koninklijke Philips Electronics N.V.Signal processing method and arragement
US20050249075 *11 Jul 200510 Nov 2005Laronne Shai ACommercial/non-commercial medium test
US20060020879 *8 Sep 200526 Jan 2006Microsoft CorporationTransferring metadata to a client
US20060041753 *11 Aug 200323 Feb 2006Koninklijke Philips Electronics N.V.Fingerprint extraction
US20060075237 *31 Oct 20036 Apr 2006Koninklijke Philips Electronics N.V.Fingerprinting multimedia contents
US20060090020 *8 Oct 200427 Apr 2006Time Trax Technologies CorporationConnector for satellite radio-computer interface
US20060106867 *2 Nov 200418 May 2006Microsoft CorporationSystem and method for speeding up database lookups for multiple synchronized data streams
US20060136502 *21 Dec 200522 Jun 2006Musicgiants, Inc.Unified media collection system
US20060149533 *30 Dec 20046 Jul 2006Aec One Stop Group, Inc.Methods and Apparatus for Identifying Media Objects
US20060149552 *30 Dec 20046 Jul 2006Aec One Stop Group, Inc.Methods and Apparatus for Audio Recognition
US20060156374 *14 Feb 200313 Jul 2006Hu Carl CAutomatic synchronization of audio and video based media services of media content
US20060177096 *20 Apr 200610 Aug 2006Sony Pictures Entertainment, Inc.Fingerprinting of Data
US20060229878 *27 May 200412 Oct 2006Eric ScheirerWaveform recognition method and apparatus
US20060242193 *22 Jun 200626 Oct 2006Dunning Ted EInformation retrieval engine
US20060242198 *22 Apr 200526 Oct 2006Microsoft CorporationMethods, computer-readable media, and data structures for building an authoritative database of digital audio identifier elements and identifying media items
US20060253207 *22 Apr 20059 Nov 2006Microsoft CorporationMethods, computer-readable media, and data structures for building an authoritative database of digital audio identifier elements and identifying media items
US20070050409 *16 Dec 20051 Mar 2007Harris CorporationSystem, methods, and program product to trace content genealogy
US20070073649 *18 May 200429 Mar 2007Hiroyuki KikkojiInformation recording device, information recording method, and information recording program
US20070078773 *31 Aug 20065 Apr 2007Arik CzerniakPosting digital media
US20070106405 *21 Aug 200610 May 2007Gracenote, Inc.Method and system to provide reference data for identification of digital content
US20070110089 *27 Nov 200317 May 2007AdvestigoSystem for intercepting multimedia documents
US20070110272 *16 May 200617 May 2007Sharma Ravi KEncoding and Decoding Signals for Digital Watermarking
US20070156268 *28 Nov 20065 Jul 2007Galvin Brian MProviding audiographs through a web service
US20070168388 *30 Dec 200519 Jul 2007Microsoft CorporationMedia discovery and curation of playlists
US20070195460 *17 Apr 200723 Aug 2007Sony CorporationRecording medium, recording method, recording apparatus, reproduction apparatus, data transmission method, and server device
US20070214130 *8 Mar 200613 Sep 2007Apple Computer, Inc.Fuzzy string matching of media meta-data
US20070239675 *29 Mar 200611 Oct 2007Microsoft CorporationWeb search media service
US20070250716 *23 Apr 200725 Oct 2007Brunk Hugh LFingerprinting of Media Signals
US20080002854 *19 Jul 20073 Jan 2008Verance CorporationSignal continuity assessment using embedded watermarks
US20080005802 *29 Jun 20063 Jan 2008Microsoft CorporationDVD identification and managed copy authorization
US20080027931 *27 Feb 200731 Jan 2008Vobile, Inc.Systems and methods for publishing, searching, retrieving and binding metadata for a digital object
US20080040807 *27 Feb 200714 Feb 2008Vobile, Inc.Systems and methods of fingerprinting and identifying digital versatile disc
US20080104404 *25 Oct 20061 May 2008Mci, Llc.Method and system for providing image processing to track digital information
US20080126323 *5 Feb 200829 May 2008Vladimir Askold BogdanovDigital audio track set recognition system
US20080133575 *17 Oct 20075 Jun 2008Kabushiki Kaisha ToshibaAudio reproducing apparatus, metadata acquiring system for audio reproducing apparatus and metadata acquiring method for audio reproducing apparatus
US20080140702 *31 Oct 200712 Jun 2008Iofy CorporationSystem and Method for Correlating a First Title with a Second Title
US20080183845 *16 Oct 200731 Jul 2008Kabushiki Kaisha ToshibaData transfer scheme for reducing network load using general purpose browser on client side
US20080201201 *25 Sep 200721 Aug 2008Sms.AcMethods and systems for finding, tagging, rating and suggesting content provided by networked application pods
US20080209502 *11 Apr 200728 Aug 2008Seidel Craig HAssociating rights to multimedia content
US20080255685 *15 Mar 200516 Oct 2008Fumio IsozakiAudio Information Output Apparatus, Audio Information Output Method, and Computer Product
US20080263360 *7 May 200723 Oct 2008Gracenote, Inc.Generating and matching hashes of multimedia content
US20080274687 *2 May 20076 Nov 2008Roberts Dale TDynamic mixed media package
US20080288365 *17 May 200720 Nov 2008Fisher Iii William WMethods, media, and systems for payment determination
US20080288411 *17 May 200720 Nov 2008Devon CopleyMethods, media, and systems for tracking and encrypting content usage
US20080288504 *17 May 200720 Nov 2008Fisher Iii William WMethods, media, and systems for recording and reporting content usage
US20080288629 *17 May 200720 Nov 2008Fisher Iii William WMethods, media, and systems for tracking content usage over a network
US20090106297 *13 Mar 200823 Apr 2009David Howell WrightMethods and apparatus to create a media measurement reference database from a plurality of distributed sources
US20090132587 *21 Nov 200721 May 2009David John SteinerMethods and systems for managing content dependency deployment
US20090133067 *19 Nov 200721 May 2009Itay ShermanMulti-media enhancement channel
US20090259690 *20 Jun 200915 Oct 2009All Media Guide, LlcMethods and apparatus for audio recognitiion
US20090324006 *30 Oct 200831 Dec 2009Jian LuMethods and systems for monitoring and tracking videos on the internet
US20100158488 *9 Mar 201024 Jun 2010Gracenote, Inc.Multiple step identification of recordings
US20100161656 *9 Mar 201024 Jun 2010Gracenote, Inc.Multiple step identification of recordings
US20100318586 *11 Jun 200916 Dec 2010All Media Guide, LlcManaging metadata for occurrences of a recording
US20100322468 *27 Apr 201023 Dec 2010Sharma Ravi KEncoding and Decoding Auxiliary Signals
US20100324883 *19 Jun 200923 Dec 2010Microsoft CorporationTrans-lingual representation of text documents
US20110035035 *18 Oct 201010 Feb 2011Rovi Technologies CorporationMethod and system for analyzing digital audio files
US20110041154 *14 Aug 200917 Feb 2011All Media Guide, LlcContent Recognition and Synchronization on a Television or Consumer Electronics Device
US20110078020 *30 Sep 200931 Mar 2011Lajoie DanSystems and methods for identifying popular audio assets
US20110078729 *30 Sep 200931 Mar 2011Lajoie DanSystems and methods for identifying audio content using an interactive media guidance application
US20110102684 *5 Nov 20095 May 2011Nobukazu SugiyamaAutomatic capture of data for acquisition of metadata
US20110137855 *8 Dec 20099 Jun 2011Xerox CorporationMusic recognition method and system based on socialized music server
US20110173185 *13 Jan 201014 Jul 2011Rovi Technologies CorporationMulti-stage lookup for rolling audio recognition
US20110231436 *26 May 201122 Sep 2011Seidel Craig HAssociating rights to multimedia content
US20120059845 *1 Aug 20118 Mar 2012Google Inc.Detecting Repeating Content In Broadcast Media
US20120179666 *27 Jan 201212 Jul 2012Vobile, Inc.Methods and systems for monitoring and tracking videos on the internet
US20120330987 *16 Jan 201227 Dec 2012Nhn CorporationContent providing method and system for transmitting metadata extracted from content
US20140282657 *27 Dec 201318 Sep 2014Turner Broadcasting System, Inc.Method and system for automatic content recognition (acr) integration for smarttvs and mobile communication devices
CN1742492B14 Feb 200320 Jul 2011汤姆森特许公司Automatic synchronization of audio and video based media services of media content
EP1595200A2 *20 Feb 200416 Nov 2005Sony Electronics Inc.Medium content identification
EP1872199A2 *16 Mar 20062 Jan 2008Microsoft CorporationMethods, computer-readable media, and data structures for building an authoritative database of digital audio identifier elements and identifying media items
EP1872199A4 *16 Mar 20061 Sep 2010Microsoft CorpMethods, computer-readable media, and data structures for building an authoritative database of digital audio identifier elements and identifying media items
EP2074527A2 *25 Oct 20071 Jul 2009Verizon Business Global LLCMethod and system for providing image processing to track digital information
EP2811416A1 *6 Jun 201310 Dec 2014Vestel Elektronik Sanayi ve Ticaret A.S.An identification method
WO2004017180A2 *18 Aug 200326 Feb 2004Neuros Audio, LlcSystem and method for creating an index of audio tracks
WO2004017180A3 *18 Aug 200315 Jul 2004Digital Innovations LlcSystem and method for creating an index of audio tracks
WO2006112843A1 *19 Apr 200526 Oct 2006Sean WardDistributed acoustic fingerprint based recognition
WO2006115617A216 Mar 20062 Nov 2006Microsoft CorporationMethods, computer-readable media, and data structures for building an authoritative database of digital audio identifier elements and identifying media items
WO2006115617A3 *16 Mar 200623 Apr 2009Microsoft CorpMethods, computer-readable media, and data structures for building an authoritative database of digital audio identifier elements and identifying media items
WO2010071455A1 *15 Dec 200924 Jun 2010Muller Montgomerie Media LimitedFile transfer method and apparatus
WO2011019473A1 *15 Jul 201017 Feb 2011Rovi Technologies CorporationContent recognition and synchronization on a television or consumer electronics device
Classifications
U.S. Classification713/193, 707/E17.028, 707/E17.009
International ClassificationG10L15/10, G10L11/00, G10L15/00, G06F17/30
Cooperative ClassificationG06F17/30758, G06F17/30787, G06F17/30817, G06F17/30825, G06F17/30796, G06F17/30743
European ClassificationG06F17/30V2, G06F17/30V3E, G06F17/30V1T, G06F17/30V1A, G06F17/30U3E, G06F17/30U1
Legal Events
DateCodeEventDescription
13 May 2004ASAssignment
Owner name: GRACENOTE, INC., CALIFORNIA
Free format text: CHANGE OF NAME;ASSIGNOR:CDDB, INC.;REEL/FRAME:015341/0243
Effective date: 20020625
13 Jun 2008ASAssignment
Owner name: GRACENOTE, INC., CALIFORNIA
Free format text: ASSIGNMENT OF ASSIGNORS INTEREST;ASSIGNORS:ROBERTS, DALE T.;HYMAN, DAVID C.;WHITE, STEPHEN HELLING;REEL/FRAME:021097/0860;SIGNING DATES FROM 20080505 TO 20080605
19 Mar 2014ASAssignment
Owner name: JPMORGAN CHASE BANK, N.A., AS COLLATERAL AGENT, IL
Free format text: SECURITY INTEREST;ASSIGNOR:GRACENOTE, INC.;REEL/FRAME:032480/0272
Effective date: 20140314