Categorizer of content in digital signals

• US 20050066176A1
• Filed: 11/04/2004
• Published: 03/24/2005
• Est. Priority Date: 04/24/2001
• Status: Active Grant

• Current Assignee: Microsoft Technology Licensing LLC (Microsoft Corporation)
• Original Assignee: Microsoft Corporation
• Inventors: Venkatesan, Ramarathnam, Mihcak, M. Kivanc
• Granted Patent: US 7,188,065 B2
• Time in Patent Office: Days
• US Class Current: 713/178
• CPC Class Codes: G06F 16/433 using audio data
• CPC Class Codes: G06F 16/634 Query by example, e.g. query by humming
• CPC Class Codes: G06F 16/683 using metadata automatically derived from the content
• CPC Class Codes: G10H 1/0058 Transmission between separate instruments or between individual components of a musical system G10H1/0083 takes precedence

Abstract

Described herein is a technology for facilitating the recognition and categorization of the content of digital signals. This abstract itself is not intended to limit the scope of this patent. The scope of the present invention is pointed out in the appending claims.

Claims

1. A computer-implemented method for recognizing a digital signal, the method comprising:

obtaining a digital signal;

deriving a categorization value representative of the digital signal so that perceptually similar digital signals have proximally similar categorization values.

2. A computer-implemented method as recited in claim 1, wherein the digital signals are selected from a group consisting of digital audio signals, digital video signals, digital image signals, and digital multimedia signals.

3. A computer-implemented method as recited in claim 1 further comprising comparing categorization value of a digital signal to determine if such value is proximally near categorization values of a group of digital signals having proximally clustered categorization values.

4. A computer-implemented method as recited in claim 1 further comprising:

comparing categorization value of the digital signal to determine if such value is proximally near categorization values of a group of digital signals having proximally clustered categorization values;

grouping the digital signal with the group of digital signals if the categorization value of the digital signal is proximally near the categorization values of the group.

5. A computer-implemented method as recited in claim 1, wherein the categorization value is a hash value.

6. A system for recognizing a digital signal, the system comprising means for performing functions comprising:

obtaining a digital signal;

deriving a categorization value representative of the digital signal so that perceptually similar digital signals have proximally similar categorization values.

7. A system as recited in claim 6, wherein the digital signals are selected from a group consisting of digital audio signals, digital video signals, digital image signals, and digital multimedia signals.

8. A system as recited in claim 6, the functions further comprising comparing categorization value of a digital signal to determine if such value is proximally near categorization values of a group of digital signals having proximally clustered categorization values.

9. A system as recited in claim 6, the functions further comprising:

comparing categorization value of the digital signal to determine if such value is proximally near categorization values of a group of digital signals having proximally clustered categorization values;

grouping the digital signal with the group of digital signals if the categorization value of the digital signal is proximally near the categorization values of the group.

10. A system as recited in claim 6, wherein the categorization value is a hash value.

11. One or more computer-readable media having computer-executable instructions thereon that, when executed by a computer, perform acts for recognizing a digital signal, the acts comprising:

obtaining a digital signal;

deriving a categorization value representative of the digital signal so that perceptually similar digital signals have proximally similar categorization values.

12. One or more media as recited in claim 11, wherein the digital signals are selected from a group consisting of digital audio signals, digital video signals, digital image signals, and digital multimedia signals.

13. One or more media as recited in claim 11 further comprising comparing categorization value of a digital signal to determine if such value is proximally near categorization values of a group of digital signals having proximally clustered categorization values.

14. One or more media as recited in claim 11 further comprising:

comparing categorization value of the digital signal to determine if such value is proximally near categorization values of a group of digital signals having proximally clustered categorization values;

grouping the digital signal with the group of digital signals if the categorization value of the digital signal is proximally near the categorization values of the group.

15. One or more media as recited in claim 11, wherein the categorization value is a hash value.

17. One or more media as recited in claim 11, wherein the digital signals are selected from a group consisting of digital audio signals, digital video signals, digital image signals, and digital multimedia signals.

16. One or more computer-readable media having computer-executable instructions thereon that, when executed by a computer, perform acts for recognizing a digital signal, the acts comprising:

deriving a categorization value representative of a digital signal based upon intrinsic characteristics of the digital signal, so that digital signals that are perceptually similar have categorization values that are proximally similar;

comparing categorization value of the digital signal to determine if such value is proximally similar to categorization values of a group of digital signals having proximally clustered categorization values;

grouping the digital signal with a group of digital signals if the categorization value of the digital signal is proximally near the categorization values of the group.

18. A computer-readable medium having stored thereon a data structure, comprising:

a first data field containing a digital signal;

a second data field derived from the first field by deriving a categorization value representative of the digital signal so that perceptually similar digital signals have proximally similar categorization values;

a third data field functioning to delimit the end of the data structure.

19. A computer-readable medium as recited in claim 18, wherein the digital signals are selected from a group consisting of digital audio signals, digital video signals, digital image signals, and digital multimedia signals.