TECHNIQUES FOR UPDATING A PARTIAL DIALOG STATE
First Claim
1. A system configured to:
- receive user input at a first turn;
generate a semantic representation based on the user input at the first turn;
generate a partial dialog state based in part on the semantic representation associated with the first turn;
receive user input at a second turn;
generate the semantic representation based on the user input at the second turn; and
update the partial dialog state for the second turn using a discriminative model using the semantic representation associated with the first turn and the second turn.
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Abstract
Embodiments provide for tracking a partial dialog state as part of managing a dialog state space, but the embodiments are not so limited. A method of an embodiment jointly models partial state update and named entity recognition using a sequence-based classification or other model, wherein recognition of named entities and a partial state update can be performed in a single processing stage at runtime to generate a distribution over partial dialog states. A system of an embodiment is configured to generate a distribution over partial dialog states at runtime in part using a sequence classification decoding or other algorithm to generate one or more partial dialog state hypothesis and/or a confidence score or measure associated with each hypothesis. Other embodiments are included.
50 Citations
20 Claims
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1. A system configured to:
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receive user input at a first turn; generate a semantic representation based on the user input at the first turn; generate a partial dialog state based in part on the semantic representation associated with the first turn; receive user input at a second turn; generate the semantic representation based on the user input at the second turn; and update the partial dialog state for the second turn using a discriminative model using the semantic representation associated with the first turn and the second turn. - View Dependent Claims (2, 3, 4, 5, 6, 7, 8, 9, 10)
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11. A method comprising:
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determining a partial dialog state for a turn based in part on user input associated with the turn; using a discriminative model to update the partial dialog state for a current turn based in part on the partial dialog state associated with the turn; and determining a dialog state based in part on the partial dialog state at the current turn as part of tracking a user goal. - View Dependent Claims (12, 13, 14, 15, 16)
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17. An article of manufacture which stores executable instructions that operate to:
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determine a semantic representation based on user input at a first turn using natural language processing operations; determine a partial dialog state for the first turn based in part on the semantic representation associated with the first turn; determine the semantic representation based on the user input at a second turn; and update the partial dialog state for the second turn based in part on the semantic representation associated with the first turn and the second turn. - View Dependent Claims (18, 19, 20)
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Specification