DIALOG STATE TRACKING USING WEB-STYLE RANKING AND MULTIPLE LANGUAGE UNDERSTANDING ENGINES

摘要

A dialog state tracking system. One aspect of the system is the use of multiple utterance decoders and/or multiple spoken language understanding (SLU) engines generating competing results that improve the likelihood that the correct dialog state is available to the system and provide additional features for scoring dialog state hypotheses. An additional aspect is training a SLU engine and a dialog state scorer/ranker DSR engine using different subsets from a single annotated training data set. A further aspect is training multiple SLU/DSR engine pairs from inverted subsets of the annotated training data set. Another aspect is web-style dialog state ranking based on dialog state features using discriminative models with automatically generated feature conjunctions. Yet another aspect is using multiple parameter sets with each ranking engine and averaging the rankings. Each aspect independently improves dialog state tracking accuracy and may be combined in various combinations for greater improvement.

主权项

1. A method for improving dialog state tracking accuracy in a dialog system, the method comprising:
determining meaning representations for conversational inputs received from a user; enumerating dialog state hypotheses from the meaning representations; extracting the features associated with each dialog state hypothesis using spoken language processing; ranking the dialog state hypotheses; and using at least one member of the ranked set of dialog states hypotheses to determine what action the dialog system should take next.