TREND DISCOVERY IN AUDIO SIGNALS

• US 20110044447A1
• Filed: 08/21/2009
• Published: 02/24/2011
• Est. Priority Date: 08/21/2009
• Status: Abandoned Application

• Current Assignee: Nexidia Incorporated (Nice Ltd)
• Original Assignee: Nexidia Incorporated (Nice Ltd)
• Inventors: Morris, Robert W., Gavalda, Marsal, Cardillo, Peter S., Arrowood, Jon A.
• Application Number:
  US12/545,282
• Publication Number:
  US 20110044447A1
• Time in Patent Office: Days
• US Class Current: 379/265.03
• CPC Class Codes: G06T 11/206 Drawing of charts or graphs
• CPC Class Codes: G10L 2015/088 Word spotting
• CPC Class Codes: H04M 2201/38 Displays
• CPC Class Codes: H04M 2203/357 Autocues for dialog assistance
• CPC Class Codes: H04M 3/51 Centralised call answering arrangements requiring operator intervention , e.g. call or contact centers for telemarketing

Abstract

Techniques for processing data representative of text associated with one or more content sources to generate a specification of a set of keyphrases of interest; processing a first set of audio signals collected during a first time period to generate first data characterizing putative occurrences of one or more keyphrases of the set in the first set of audio signals; evaluating the first data to generate keyphrase-specific comparison values for the first set of audio signals; deriving first trending data between the first set of audio signals and a second set of audio signals based in part on an analysis of the keyphrase-specific comparison values for the first set of audio signals relative to stored keyphrase-specific baseline values; and generating a visual representation of at least some of the first trending data and causing the visual representation of the first trending data to be presented on a display terminal.

Claims

1. A method comprising:

processing, by a keyphrase generation engine, data representative of text associated with one or more content sources to generate a specification of a set of keyphrases of interest;

processing, by a word spotting engine, a first set of audio signals collected during a first time period to generate first data characterizing putative occurrences of one or more keyphrases of the set of keyphrases of interest in the first set of audio signals;

evaluating, by an analysis engine, the first data to generate keyphrase-specific comparison values for the first set of audio signals;

deriving, by the analysis engine, first trending data between the first set of audio signals and a second set of audio signals based in part on an analysis of the keyphrase-specific comparison values for the first set of audio signals relative to stored keyphrase-specific baseline values; and

generating, by a user interface engine, a visual representation of at least some of the first trending data and causing the visual representation of the first trending data to be presented on a display terminal.

2. The method of claim 1, wherein the visual representation further includes trending data other than the first trending data.

3. The method of claim 1, wherein the keyphrase generation engine, the word spotting engine, the analysis engine, and the user interface engine form part of a contact center system.

4. The method of claim 3, wherein the first set of audio signals is representative of interactions between contact center callers and contact center agents.

5. The method of claim 3, wherein the display terminal is associated with a contact center user.

6. The method of claim 1, further comprising:

processing, by the word spotting engine, the second set of audio signals collected during a second time period to generate second data characterizing putative occurrences of one or more keyphrases of the set of keyphrases of interest in the second set of audio signals.

7. The method of claim 6, wherein the second set of audio signals is representative of interactions between contact center callers and contact center agents.

8. The method of claim 6, wherein the second time period is prior to the first time period, and the method further includes:

evaluating, by the analysis engine, the second data to generate the keyphrase-specific baseline values; and

storing, by the analysis engine, the keyphrase-specific baseline values in a machine-readable data store.

9. The method of claim 6, wherein the second time period is subsequent to the first time period, and the method further includes

evaluating, by the analysis engine, the second data to generate keyphrase-specific comparison values for the second set of audio signals;

deriving, by the analysis engine, second trending data between the second set of audio signals period and a third set of audio signals based in part on an analysis of the keyphrase-specific comparison values of the second set of audio signals relative to the stored keyphrase-specific baseline values; and

generating, by the user interface engine, a visual representation of at least some of the second trending data and causing the visual representation of the second trending data to be presented on a display terminal.

10. The method of claim 9, wherein the visual representation further includes trending data other than the first trending data and the second trending data.

11. The method of claim 6, wherein the second time period is subsequent to the first time period, and the method further includes

evaluating, by the analysis engine, the second data to generate keyphrase-specific comparison values for the second set of audio signals;

deriving, by the analysis engine, second trending data between the second set of audio signals and the first set of audio signals based in part on an analysis of the keyphrase-specific comparison values of the second set of audio signals relative to the keyphrase-specific comparison values for the first set of audio signals; and

generating, by the user interface engine, a visual representation of at least some of the second trending data and causing the visual representation of the second trending data to be presented on a display terminal.

12. The method of claim 11, wherein the visual representation further includes trending data other than the first trending data and the second trending data.

13. The method of claim 1, wherein the specification of the set of keyphrases of interest includes at least one phonetic representation of each keyphrase of the set.

14. The method of claim 1, wherein for each set of audio signals, the processing includes identifying time locations in the set of audio signals at which a spoken instance of a keyphrase of the set of keyphrases of interest is likely to have occurred based on a comparison of data representing the set of audio signals with the specification of the set of keyphrases of interest.

15. The method of claim 1, wherein evaluating each of the first data and the second data includes computing values representative of one or more of the following:

hit count, call count, call percentage, total call duration.

16. The method of claim 1, further comprising filtering the first set of audio signals prior to processing the first set of audio signals by the word spotting engine.

17. The method of claim 16, wherein the filtering is based on one or more of the following techniques:

clip spotting and natural language processing.

18. A method comprising:

processing, by a keyphrase generation engine, data representative of text associated with one or more content sources to generate a specification of a set of keyphrases of interest;

processing, by a word spotting engine, a first set of audio signals collected during a first time period to generate first data characterizing putative occurrences of one or more keyphrases of the set of keyphrases of interest in the first set of audio signals;

evaluating, by an analysis engine, the first data to identify coocurrences of spoken instances of keyphrases of the set of keyphrases of interest within the first set of audio signals; and

generating, by a user interface engine, a visual representation of at least some of the identified cooccurences of the spoken instances of keyphrases and causing the visual representation to be presented on a display terminal.

19. The method of claim 18, wherein the identified coocurrences of spoken instances of keyphrases represent salient pairs of cooccurring keyphrases of interest.

20. The method of claim 19, further comprising:

deriving, by the analysis engine, first trending data between the first set of audio signals and a second set of audio signals based in part on an analysis of the salient pairs of coocurring keyphrases of interest within the first set of audio signals relative to salient pairs of coocurring keyphrases of interest within a second set of audio signals; and

generating, by the user interface engine, a visual representation of at least some of the first trending data and causing the visual representation of the first trending data to be presented on the display terminal.

21. The method of claim 20, wherein the visual representation further includes trending data other than the first trending data.

22. The method of claim 18, wherein the identified coocurrences of spoken instances of keyphrases represent clusters of keyphrases of interest.

23. The method of claim 22, further comprising:

deriving, by the analysis engine, first trending data between the first set of audio signals and a second set of audio signals based in part on an analysis of the clusters of keyphrases of interest within the first set of audio signals relative to clusters of coocurring keyphrases of interest within a second set of audio signals; and

generating, by the user interface engine, a visual representation of at least some of the first trending data and causing the visual representation of the first trending data to be presented on the display terminal.

24. The method of claim 23, wherein the visual representation further includes trending data other than the first trending data.

25. The method of claim 18, wherein the keyphrase generation engine, the word spotting engine, the analysis engine, and the user interface engine form part of a contact center system.

26. The method of claim 24, wherein the first set of audio signals is representative of interactions between contact center callers and contact center agents.

27. The method of claim 24, wherein the display terminal is associated with a contact center user.

28. The method of claim 18, wherein evaluating the first data comprises:

recording a number of times a spoken instance of a first keyphrase of the set of keyphrases of interest occurs within a predetermined range of another keyphrase of the set of keyphrases of interest;

generating a vector for the first keyphrase based on the recording; and

storing the generated first keyphrase vector in a machine-readable data store for further processing.

29. The method of claim 28, further comprising:

repeating the recording, vector generating, and storing actions for at least some other keyphrases of the set of keyphrases of interest.