Method and system for predicting understanding errors in a task classification system
First Claim
1. A method of monitoring natural language understanding of a user'"'"'s input communication in a task classification system that operates on a task objective of a user, the method comprisinga) if the user'"'"'s input communication is sufficiently free of natural language understanding (NLU) errors that the user'"'"'s input communication can be understood, then making a task classification decision, andb) if the user'"'"'s input communication contains NLU errors that make the user'"'"'s input communication not able to be understood, theni) if a probability of understanding the user'"'"'s input communication exceeds a first threshold, conducting further dialog with the user,ii) otherwise, routing the user to a human for further assistance.
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Abstract
This invention concerns a method and system for monitoring an automated dialog system for the automatic recognition of language understanding errors based on a user'"'"'s input communications. The method may include determining whether a probability of understanding the user'"'"'s input communication exceeds a first threshold. If the first threshold is exceeded, further dialog is conducted with the user. Otherwise, the user may be directed to a human for assistance. The method also illustratively determines whether the probability also exceeds a second threshold, the second threshold being higher than the first. If so, then further dialog is conducted with the user using the current dialog strategy. However, if the probability falls between a first threshold and a second threshold, the dialog strategy may be adapted in order to improve the chances of conducting a successful dialog with the user.
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Citations
11 Claims
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1. A method of monitoring natural language understanding of a user'"'"'s input communication in a task classification system that operates on a task objective of a user, the method comprising
a) if the user'"'"'s input communication is sufficiently free of natural language understanding (NLU) errors that the user'"'"'s input communication can be understood, then making a task classification decision, and b) if the user'"'"'s input communication contains NLU errors that make the user'"'"'s input communication not able to be understood, then i) if a probability of understanding the user'"'"'s input communication exceeds a first threshold, conducting further dialog with the user, ii) otherwise, routing the user to a human for further assistance.
Specification