Script compliance and quality assurance using speech recognition

• US 8,484,030 B1
• Filed: 04/30/2012
• Issued: 07/09/2013
• Est. Priority Date: 02/15/2001
• Status: Expired due to Fees

• Current Assignee: Alorica Incorporated
• Original Assignee: West Corporation
• Inventors: Pettay, Mark J., Vacek, Jill M.
• Primary Examiner(s): YEN, ERIC L
• Application Number:
  US13/459,704
• Time in Patent Office: 435 Days
• Field of Search: 704/9, 704/270, 704/270.1, 704/275
• US Class Current: 704/270
• CPC Class Codes: G10L 15/26 Speech to text systems G10L15/08 takes precedence
• CPC Class Codes: G10L 2015/088 Word spotting

Abstract

Apparatus and methods are provided for using automatic speech recognition to analyze a voice interaction and verify compliance of an agent reading a script to a client during the voice interaction. In one aspect of the invention, a communications system includes a user interface, a communications network, and a call center having an automatic speech recognition component. In other aspects of the invention, a script compliance method includes the steps of conducting a voice interaction between an agent and a client and evaluating the voice interaction with an automatic speech recognition component adapted to analyze the voice interaction and determine whether the agent has adequately followed the script.

Claims

1. A method, comprising:

dividing, via at least one automatic speech recognition component, at least one voice interaction into viewable panel-level segments;

assigning, via the at least one automatic speech recognition component, a score to each of the panel-level segments, each score indicating a match accuracy between the panel-level segment and a corresponding expected text of the panel-level segment; and

evaluating, via the at least one automatic speech recognition component, each score against a standard, the standard defining a required score for each of the panel-level segments to be declared as a match to their corresponding expected texts.

2. The method of claim 1, wherein at least one script includes text corresponding to at least one offer of at least one of goods and services.

3. The method of claim 1, wherein the at least one voice interaction is conducted via at least one of:

a communications network;

a publicly switched telephone network;

Internet; and

a communications network having at least one wireless component.

4. The method of claim 1, comprising:

converting the at least one voice interaction into at least one digital signal comprising at least one spectral representation of the at least one voice interaction,

comparing the at least one digital signal to the standard that includes at least one known vocabulary, and

matching the at least one digital signal to at least one of words and phrases contained in the standard.

5. The method of claim 1, comprising performing at least one action based upon at least one result of the analyzing, wherein the performing includes at least one of:

transmitting at least one signal to at least one agent;

transmitting at least one signal to at least one reviewing authority; and

making at least one entry in at least one script compliance incentive system.

6. The method of claim 1, comprising determining whether at least one agent has adequately followed at least one script by performing at least one of a following action:

defining at least one score assigned by the at least one automatic speech recognition component; and

reading by the at least one agent the at least one script to the at least one client, based at least in part on a comparison of data representing an actual duration of the at least one interaction to data representing an expected duration parameter associated with the at least one interaction.

7. The method of claim 1, comprising comparing data representing an actual duration of at least one interaction to data representing an expected duration parameter associated with the at least one interaction.

8. The method of claim 1, comprising comparing data representing an actual duration of the at least one interaction to data representing an expected duration parameter associated with the at least one interaction.

9. The method of claim 1, comprising determining whether at least one agent has adequately followed at least one script by applying a set of action rules to an output of the analyzing, wherein the set of action rules includes a quality assurance action to be taken.

10. The method of claim 1, comprising comparing each panel-level segment with a corresponding expected text, wherein a confidence level threshold of the automatic speech recognition component is used to evaluate an accuracy of each panel-level segment based on an output of a comparison between each panel-level segment and its corresponding expected text.

11. A non-transitory computer readable medium comprising instructions for:

dividing, via at least one automatic speech recognition component, at least one voice interaction into viewable panel-level segments;

assigning, via the at least one automatic speech recognition component, a score to each of the panel-level segments, each score indicating a match accuracy between the panel-level segment and a corresponding expected text of the panel-level segment; and

evaluating, via the at least one automatic speech recognition component, each score against a standard, the standard defining a required score for each of the panel-level segments to be declared as a match to their corresponding expected texts.

12. The non-transitory computer readable medium of claim 11, comprising:

converting the at least one voice interaction into at least one digital signal comprising at least one spectral representation of the at least one voice interaction,

comparing the at least one digital signal to at least one reference standard that includes at least one known vocabulary, and

matching the at least one digital signal to at least one of words and phrases contained in the at least one reference standard.

13. The non-transitory computer readable medium of claim 11, comprising performing at least one action based upon at least one result of the analyzing, wherein the performing includes at least one of:

transmitting at least one signal to at least one agent;

transmitting at least one signal to at least one reviewing authority; and

making at least one entry in at least one script compliance incentive system.

14. The non-transitory computer readable medium of claim 11, comprising determining whether at least one agent has adequately followed at least one script by performing at least one of a following action:

defining at least one score assigned by the at least one automatic speech recognition component; and

reading by the at least one agent the at least one script to the at least one client, based at least in part on a comparison of data representing an actual duration of the at least one interaction to data representing an expected duration parameter associated with the at least one interaction.

15. The non-transitory computer readable medium of claim 11, comprising comparing data representing an actual duration of at least one interaction to data representing an expected duration parameter associated with the at least one interaction.

16. The non-transitory computer readable medium of claim 11, comprising comparing data representing an actual duration of the at least one interaction to data representing an expected duration parameter associated with the at least one interaction.

17. The non-transitory computer readable medium of claim 11, comprising determining whether at least one agent has adequately followed at least one script by applying a set of action rules to an output of the analyzing, wherein the set of action rules includes a quality assurance action to be taken.

18. The non-transitory computer readable medium of claim 11, comprising comparing each panel-level segment with a corresponding expected text, wherein a confidence level threshold of the automatic speech recognition component is used to evaluate an accuracy of each panel-level segment based on an output of a comparison between each panel-level segment and its corresponding expected text.