Method and apparatus for customizing conversation agents based on user characteristics using a relevance score for automatic statements, and a response prediction function

A non-transitory computer-readable storage medium storing instructions that when executed by a computer cause the computer to perform a method, the method comprising:

• receiving a user-statement from a user during a simulated conversation with the user;
• determining a set of automatic-statements that each responds to the user-statement;
• determining a set of behavior-characteristics associated with the user;
• computing relevance scores for the automatic-statements based on the behavior-characteristics, wherein a respective relevance score indicates an outcome quality that the user is likely to perceive for the automatic-statement as a response to the user-statement, wherein computing the respective relevance score for a respective automatic-statement involves computing a template-relevance score using a response-prediction function that takes as input a response template and the user's behavior-characteristics, and wherein the template-relevance score indicates how well the response template matches a conversation style for a user having the behavior characteristics;
• selecting an automatic-statement that has a highest relevance score from the set of automatic-statements;
• and
• providing the selected automatic-statement to the user.

An apparatus, comprising:

• a communication module to receive a user-statement from a user during a simulated conversation with the user;
• a response-generating module to determine a set of automatic-statements that each responds to the user-statement;
• a response-scoring module to compute relevance scores for the automatic-statements based on behavior-characteristics associated with the user, wherein a respective relevance score indicates an outcome quality that the user is likely to perceive for the automatic-statement as a response to the user-statement, wherein computing the respective relevance score for a respective automatic-statement involves computing a template-relevance score using a response-prediction function that takes as input a response template and the user's behavior-characteristics, and wherein the template-relevance score indicates how well the response template matches a conversation style for a user having the behavior characteristics;
• and
• a response-selecting module to select an automatic-statement that has a highest relevance score from the set of automatic-statements;
• wherein the communication module is further configured to provide the selected automatic-statement to the user.