Discriminative Policy Training for Dialog Systems

摘要

Embodiments of a dialog system employing a discriminative action selection solution based on a trainable machine action model. The discriminative machine action selection solution includes a training stage that builds the discriminative model-based policy and a decoding stage that uses the discriminative model-based policy to predict the machine action that best matches the dialog state. Data from an existing dialog session is annotated with a dialog state and an action assigned to the dialog state. The labeled data is used to train the discriminative model-based policy. The discriminative model-based policy becomes the policy for the dialog system used to select the machine action for a given dialog state.

主权项

1. A method of selecting machine actions in a dialog system using a discriminative model-based policy, the method comprising the acts of:
receiving the discriminative model-based policy statistically linking machine actions to dialog states; collecting a utterance from a user; determining a meaning for the utterance; updating a session dialog state based on the utterance; selecting the machine action based on the discriminative model-based policy and the session dialog state; executing the machine action; and outputting the results of the machine action for presentation to the user.