Method for designing an automated speech recognition (ASR) interface for a customer call center
View Patent ↗A method of designing a customer interface for a service center, such as an automated speech recognition (ASR) self-service center. Customer activity to an existing service center is monitored, providing customer model, which includes a collection of customer tasks. These tasks are assigned to action-object pairs, which are further assigned to routing destinations. Dialog modules are designed, based on the customer model data, including disambiguation dialogs.
1. A method of designing a customer interface for an automated speech recognition (ASR) call center, comprising:
collecting data for a customer model, the customer model comprising at least recorded opening statements of customers to a call center and persona data representing customer personas;
creating a task model comprising a set of action-object pairs, based on the recorded opening statements;
creating a business rules model, representing routing destinations for customer calls;
linking the customer model to the task model, such that the opening statements are assigned to action-object pairs;
linking the task model to the business rules model, such that each action-object pair is assigned to a routing destination;
creating an action-object frequency table indicative of the relative frequency of each action-object pair, based on the results of the step of linking the customer model to the task model; and
designing an interface module for each action object pair;
wherein the designing step is performed in substantially the order of the frequency table, from higher frequency action-object pairs to lower frequency action-object pairs; and wherein the designing step is based on the personal data.
2. The method of claim 1 , wherein the customer interface is for a how-to-use call center application, and the step of linking the task model to the business rules model comprises linking action-object pairs to the how-to-use call center destination.
3. The method of claim 1 , wherein at least one of dialog modules is activated in response to a direct routing decision.
4. The method of claim 1 , wherein at least one of the dialog modules is activated in response to a clarification routing decision.
5. The method of claim 4 , wherein the dialog module is operable to transfer the customer to one of two routing destinations.
6. The method of claim 4 , wherein the dialog module is a disambiguation dialog module operable to present the customer with choices.
7. The method of claim 1 , wherein the persona data is used to determine language alternatives.
8. The method of claim 1 , wherein at least one of dialog modules is activated in response to a direct routing decision.
9. The method of claim 1 , wherein at least one of the dialog modules is activated in response to a clarification routing decision.
10. The method of claim 9 , wherein the dialog module is operable to transfer the customer to one of two routing destinations.
11. The method of claim 9 , wherein the dialog module is a disambiguation dialog module operable to present the customer with choices.
12. A method of designing a customer interface for a self-service call center application, comprising:
recording opening statements of customers during visits to an existing service center, thereby creating a customer model representing customer tasks;
creating a task model comprising a set of action-object pairs, based on the customer model;
creating a business rules model, representing routing destinations for customer calls;
linking the customer model to the task model, such that the opening statements are assigning to action-object pairs;
linking the task model to the business rules model, such that each action-object pair is assigned to a routing destination;
creating an action-object frequency table indicative of a relative frequency of each of the action-object pairs, based on the results of the results of the linking the customer model to the task model; and
designing an interface module for each action object pair; wherein the designing step is performed in substantially the order of the frequency table, from higher frequency action-object pairs to lower frequency action-object pairs.
13. The method of claim 12 , wherein the customer interface is for an ASR call center.
14. The method of claim 13 , wherein the customer interface is for a how-to-use ASR call center, and the step of linking the task model to the business rules model comprises linking action-object pairs to the how-to-use call center destination.
15. The method of claim 13 , wherein the customer interface is for a web-based self-service center.
16. The method of claim 12 , further comprising the step of collecting customer persona data during customer visits to the existing service center.
17. The method of claim 16 , wherein the personal data is used to determine language alternatives.
18. The method of claim 12 , wherein the customer model data is collected during visits to a call center.
19. The method of claim 12 , wherein the customer model data is collected during visits to a web site via the internet.
20. A method of designing a customer interface for an automated speech recognition (ASR) call center, comprising:
defining a set of action-object pairs based on opening statements of callers to a call center;
assigning each action-object pair is assigned to a routing destination;
creating an action-object frequency table indicative of the relative frequency of each action-object pair ; and
designing an interface module for each action object pair;
wherein the designing step is performed in substantially the order of the frequency table, from higher frequency action-object pairs to lower frequency action-object pairs; and wherein the designing step is based on the persona data.