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Task-independent conversational systems

  • US 10,339,919 B1
  • Filed: 04/20/2018
  • Issued: 07/02/2019
  • Est. Priority Date: 04/20/2018
  • Status: Active Grant
First Claim
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1. A method comprising:

  • obtaining multi-task training data, the multi-task training data comprising a plurality of sequences of conversational inputs, wherein each sequence corresponds to a respective task, and the multi-task training data comprises sequences corresponding to multiple different tasks, wherein the multi-task training data comprises a respective reward and a respective conversational output for each conversational input, and wherein the respective rewards are generated based on one or more observable metrics that relate to a quality of conversational outputs generated by the conversational machine learning model; and

    training a conversational machine learning model on the multi-task training data to determine trained values of the parameters of the conversational machine learning model, wherein the conversational machine learning model is configured to receive as input a conversational input and to generate as output a conversational output that defines a response to a user that is independent of a task being performed when the conversational input was generated, wherein training the conversational machine learning model comprises training the conversational machine learning model using the respective rewards using reinforcement learning.

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