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PROBABILISTIC MATCHING FOR DIALOG STATE TRACKING WITH LIMITED TRAINING DATA

  • US 20180121415A1
  • Filed: 11/03/2016
  • Published: 05/03/2018
  • Est. Priority Date: 11/03/2016
  • Status: Active Grant
First Claim
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1. A method for dialog state tracking in a dialog system for conducting a dialog between a virtual agent and a user, the method comprising:

  • providing an ontology in which a set of values are indexed by slot;

    receiving a user utterance and, with a speech-to-text converter, converting the user utterance to a text string comprising a segment of a dialog;

    detecting mentions in the dialog segment;

    extracting candidate slot values from the ontology, based on the detected mentions;

    ranking the candidate slot values, comprising computing a feature vector for each detected mention and ranking the candidate slot values with a prediction model trained on (slot, value) pair labels and feature vectors for mentions in a set of training dialog segments, the feature vectors include values for lexicalized and delexicalized features for the detected mention; and

    updating a dialog state based on the ranking of the candidate slot values; and

    outputting a dialog act of the virtual agent, based on the updated dialog state,wherein the converting of the utterance, detecting mentions, extracting candidate slot values, ranking the candidate slot values, and updating the dialog state are performed with a processor.

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