MATCHING AND LEAD PREQUALIFICATION BASED ON VOICE ANALYSIS

• US 20150127343A1
• Filed: 11/04/2014
• Published: 05/07/2015
• Est. Priority Date: 11/04/2013
• Status: Abandoned Application

• Current Assignee: Jobaline Incorporated
• Original Assignee: Jobaline Incorporated
• Inventors: LI, Ying, MULLOR, Miki, SALAZAR G., Luis J., LANETTI, Jose Daniel Contreras
• Application Number:
  US14/532,600
• Publication Number:
  US 20150127343A1
• Time in Patent Office: Days
• US Class Current: 704/244
• CPC Class Codes: G10L 17/26 Recognition of special voice characteristics, e.g. for use in lie detectors; Recognition of animal voices
• CPC Class Codes: G10L 25/12 the extracted parameters being prediction coefficients
• CPC Class Codes: G10L 25/18 the extracted parameters being spectral information of each sub-band
• CPC Class Codes: G10L 25/63 for estimating an emotional state
• CPC Class Codes: G10L 25/90 Pitch determination of speech signals

Abstract

A computing device may perform a feature identification of a received voice segment to recognize physical characteristics of the voice segment. The device may also determine paralinguistic voice characteristics of the voice segment according to the physical characteristics of the voice segment. The device may also indicate a match status of the voice segment according to a comparison of the physical characteristics and the paralinguistic voice characteristics of the voice segment to desired characteristics of matching voice segments.

Claims

1. A system comprising:

a computing device configured to

perform a feature identification of a received voice segment to recognize physical characteristics of the voice segment;

determine paralinguistic voice characteristics of the voice segment according to the physical characteristics of the voice segment; and

indicate a match status of the voice segment according to a comparison of the physical characteristics and the paralinguistic voice characteristics of the voice segment to desired characteristics of matching voice segments.

2. The system of claim 1, wherein the computing device is further configured to perform the feature identification by transforming the voice segment into data elements including one or more of (i) short-term Fast-Fourier Transform;

(ii) frequency domain energy measure; and

(iii) linear prediction coefficient in a frequency domain.

3. The system of claim 1, wherein the physical characteristics include at least one of sound wave pattern, pitch, inflection, compression, and amplitude.

4. The system of claim 1, wherein the paralinguistic voice characteristics include at least one of rate of speech, easiness to understand, and energy level.

5. The system of claim 1, wherein the system further comprises a database of structured voice data configured to maintain associations of clusters of voice segment data that share similar physical characteristics to paralinguistic voice characteristics, and the computing device is further configured to determine the paralinguistic voice characteristics of the voice segment by retrieving associated paralinguistic voice characteristics of clusters of voice segment data that share similar physical characteristics to the physical characteristics of the voice segment.

6. The system of claim 5, wherein the computing device is further configured to train the database of structured voice data to map paralinguistic voice characteristics to predictive feature combinations of physical characteristics.

7. The system of claim 5, wherein the computing device is further configured to train the database of structured voice data according to identified paralinguistic voice characteristic input received from a training user interface.

8. The system of claim 7, wherein the training user interface is provided to validator users by way of a web page in communication with the computing device.

9. The system of claim 1, wherein the computing device is further configured to:

receive, from a lead responder, a voice-based response to a pre-screening inquiry of a lead request, the voice-based response including the voice segment;

identify, from the voice segment, a textual answer to the pre-screening inquiry provided by the lead responder; and

score the lead responder as a potential lead in connection with the lead request based on the textual answer to the pre-screening inquiry and the match status of the voice segment.

10. A computer-implemented method comprising:

performing a feature identification of a received voice segment to recognize physical characteristics of the voice segment;

determining paralinguistic voice characteristics of the voice segment according to the physical characteristics of the voice segment; and

indicating a match status of the voice segment according to a comparison of the physical characteristics and the paralinguistic voice characteristics of the voice segment to desired characteristics of matching voice segments.

11. The method of claim 10, further comprising performing the feature identification by transforming the voice segment into data elements including one or more of (i) short-term Fast-Fourier Transform;

(ii) frequency domain energy measure; and

(iii) linear prediction coefficient in a frequency domain.

12. The method of claim 10, wherein the physical characteristics include at least one of sound wave pattern, pitch, inflection, compression, and amplitude.

13. The method of claim 10, wherein the paralinguistic voice characteristics include at least one of rate of speech, easiness to understand, and energy level.

14. The method of claim 10, further comprising:

maintaining, in a database of structured voice data, associations of clusters of voice segment data that share similar physical characteristics to paralinguistic voice characteristics; and

determining the paralinguistic voice characteristics of the voice segment by retrieving associated paralinguistic voice characteristics of clusters of voice segment data that share similar physical characteristics to the physical characteristics of the voice segment.

15. The method of claim 14, further comprising training the database of structured voice data to map paralinguistic voice characteristics to predictive feature combinations of physical characteristics.

16. The method of claim 14, further comprising training the database of structured voice data according to identified paralinguistic voice characteristic input received from a training user interface.

17. The method of claim 16, wherein the training user interface is provided to validator users by way of a web page interface.

18. The method of claim 10, further comprising:

receiving, from a lead responder, a voice-based response to a pre-screening inquiry of a lead request, the voice-based response including the voice segment;

identifying, from the voice segment, a textual answer to the pre-screening inquiry provided by the lead responder; and

scoring the lead responder as a potential lead in connection with the lead request based on the textual answer to the pre-screening inquiry and the match status of the voice segment.

19. The method of claim 18, further comprising:

receiving match criteria including a description of an advertisement, a selection of pre-screening inquiries, and a selection of paralinguistic voice characteristics;

publishing an interactive advertising unit online corresponding to the advertisement based on the match criteria; and

interacting, via the interactive advertising unit, with a plurality of responders to collect responder information responsive to the pre-screening inquiries, the interacting including capturing the voice-based response to the pre-screening inquiry of the lead request.

20. A non-transitory computer readable medium comprising instructions that, when executed by one or more processors of a computing device, cause the computing device to:

perform a feature identification of a received voice segment to recognize physical characteristics of the voice segment;

determine paralinguistic voice characteristics of the voice segment according to the physical characteristics of the voice segment; and

indicate a match status of the voice segment according to a comparison of the physical characteristics and the paralinguistic voice characteristics of the voice segment to desired characteristics of matching voice segments.

21. The medium of claim 20, further comprising instructions to cause the computing device to perform the feature identification by transforming the voice segment into data elements including one or more of (i) short-term Fast-Fourier Transform;

(ii) frequency domain energy measure; and

(iii) linear prediction coefficient in a frequency domain.

22. The medium of claim 20, wherein the physical characteristics include at least one of sound wave pattern, pitch, inflection, compression, and amplitude.

23. The medium of claim 20, wherein the paralinguistic voice characteristics include at least one of rate of speech, easiness to understand, and energy level.

24. The medium of claim 20, further comprising instructions to cause the computing device to:

maintain, in a database of structured voice data, associations of clusters of voice segment data that share similar physical characteristics to paralinguistic voice characteristics; and

determine the paralinguistic voice characteristics of the voice segment by retrieving associated paralinguistic voice characteristics of clusters of voice segment data that share similar physical characteristics to the physical characteristics of the voice segment.

25. The medium of claim 24, further comprising instructions to cause the computing device to train the database of structured voice data to map paralinguistic voice characteristics to predictive feature combinations of physical characteristics.

26. The medium of claim 24, further comprising instructions to cause the computing device to train the database of structured voice data according to identified paralinguistic voice characteristic input received from a training user interface.

27. The medium of claim 26, wherein the training user interface is provided to validator users by way of a web page in communication with the computing device.

28. The medium of claim 20, further comprising instructions to cause the computing device to:

receive, from a lead responder, a voice-based response to a pre-screening inquiry of a lead request, the voice-based response including the voice segment;

identify, from the voice segment, a textual answer to the pre-screening inquiry provided by the lead responder; and

score the lead responder as a potential lead in connection with the lead request based on the textual answer to the pre-screening inquiry and the match status of the voice segment.