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Methods and apparatus for generating dialog state conditioned language models

  • US 7,542,901 B2
  • Filed: 08/24/2006
  • Issued: 06/02/2009
  • Est. Priority Date: 03/27/2002
  • Status: Expired due to Term
First Claim
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1. A method for use in accordance with a dialog system, the dialog system comprising a processor, the method comprising the steps of:

  • generating by the processor of the dialog system at least one language model, the at least one language model being conditioned on a state of dialog associated with the dialog system; and

    storing the at least one language model for subsequent use in accordance with a speech recognizer associated with the dialog system;

    wherein the step of generating the at least one language model conditioned on a state of dialog associated with the dialog system further comprises the processor of the dialog system performing the steps of;

    dividing training data which is labeled by state into different state sets depending on the state to which the training data belongs; and

    building a separate language model for each of the state sets;

    wherein at least a given state corresponds to an internal state of a natural language understanding portion of the dialog system;

    wherein at least a given state corresponds to a prompt that the dialog system presents to a user;

    wherein at least a given separate language model is interpolated with a base model obtained from available training data for a domain of the dialog system;

    wherein the method further comprises the step of clustering together two or more state sets to reduce the number of states for which a separate language model is built; and

    wherein a decision to cluster two states is based on a distance measure computed between respective word distributions associated with the two stateswherein each separate language model is built using a modified Kneser-Ney smoothing technique.

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