Behavioral adaptation engine for discerning behavioral characteristics of callers interacting with an VXML-compliant voice application

Abstract

A behavioral adaptation engine integrated with a voice application creation and deployment system has at least one data input port to receive XML-based client interaction data including audio files attached to the data; at least one data port to send data to and receive data from external data systems and modules; a logic processing component including an XML reader, voice player, and analyzer to process received data; and a decision logic component to process result data against one or more constraints. The engine intercepts client data including dialog from client interaction with a served voice application in real time and processes the received data for behavioral patterns and if attached, voice characteristics of the audio files whereupon the engine according to the results and one or more valid constraints identifies one or a set of possible enterprise responses for return to the client during interaction.

1 . A behavioral adaptation engine integrated with a voice application creation and deployment system comprising: 
 at least one data input port for receiving XML-based client interaction data including audio files attached to the data;    at least one bi-directional data port for sending data to and receiving data from external data systems and modules;    a logic processing component including an XML reader and voice player and analyzer for processing received data; and    a decision logic component for processing result data against one or more constraints;    characterized in that the behavioral adaptation engine intercepts client data including dialog from client interaction with a served voice application in real time and processes the received data for behavioral patterns and if attached, voice characteristics of the audio files whereupon the engine according to the results and one or more constraints identifies one or a set of possible enterprise responses for return to the client during interaction.    
   
   
       2 . The engine of  claim 1  wherein the engine is hosted in a voice application server.  
   
   
       3 . The engine of  claim 2  wherein the server is hosted on the Internet network.  
   
   
       4 . The engine of  claim 1  wherein the voice application and deployment system includes at least one voice portal for facilitation of client access to voice applications.  
   
   
       5 . The engine of  claim 1  wherein the engine is executed to function upon receipt of a trigger event.  
   
   
       6 . The engine of  claim 1  wherein the constraints are related to one or a combination of menu navigation behavior or perceived mood state of the client.  
   
   
       7 . The engine of  claim 1  wherein data from external data resources is used as additional input data for decision processing.  
   
   
       8 . The engine of  claim 1  wherein the received client data includes one or a combination of line identification, number identification, client history data, and voice imprint results.  
   
   
       9 . The engine of  claim 2  wherein voice sampling is used to discern mood state.  
   
   
       10 . The engine of  claim 1  wherein the voice analyzer detects voice inflection variances and volume characteristics of sampled audio to facilitate mood discernment of a client.  
   
   
       11 . The engine of  claim 10  wherein the variances and volume characteristics of an interaction are collected over multiple interactions with a same application to develop statistics used in gauging enterprise response probability values.  
   
   
       12 . A method for identifying an appropriate one or set of a plurality of voice application dialog responses to data input resulting from a client interaction with a voice application comprising: 
 (a) receiving the data input during run of the voice application;    (b) interpreting the data input;    (c) analyzing the input for validity of one or more constraints;    (d) comparing the analyzed results with additional external data;    (e) analyzing the comparison results for continued validity of the one or more constraints; and    (f) identifying one or more available response options according to the valid constraints.    
   
   
       13 . The method of  claim 12  wherein the voice application is VXML compliant.  
   
   
       14 . The method of  claim 12  wherein in step (a) the data input includes client identification data, client dialog data, and digital audio sampled from the dialog.  
   
   
       15 . The method of  claim 12  wherein steps (d) and (e) are optional steps.  
   
   
       16 . The method of  claim 12  wherein in step (c) the constraint validity lends to indication of mood state determination of the client.  
   
   
       17 . The method of  claim 12  wherein in step (c) the constraint validity lends to indication of behavioral state determination of the client.  
   
   
       18 . The method of  claim 12  wherein in step (c) the constraint validity lends to an indication of both mood state and behavioral state of the client.  
   
   
       19 . The method of  claim 12  wherein in step (d) the external data includes statistical data resulting from of past interactions with the same dialog of the same application.  
   
   
       20 . The method of  claim 12  wherein in step (f) identification of one or more available response options includes submitting the one or more response options to an external module for further processing and narrower selection.