Apple Inc.

Blaise Thomson

Gennaro Frazzingaro

Thorvaldur Pall Helgason

Thomas David Voice

Stephen J Young

Rushin N Shah

Ashish Garg

Matthew S Seigel

Lin Li

Silvia Frias Delgado

Luca Simonelli

Diarmuid Ó Séaghdha

Thomas Benedict Gunter

Anuj Kumar

Federico Flego

Diarmuid Ó Śeaghdha

Dain Kaplan

David J Vandyke

Anders Johannsen

Systems and processes for operating an intelligent automated assistant are provided. In accordance with one example, a method includes, at an electronic device with one or more processors and memory, obtaining a first set of data corresponding to one or more interactions between a user and the digital assistant on the electronic device; obtaining a second set of data corresponding to one or more interactions between the user and an application on the electronic device; and storing the first set of data and the second set of data. The method further includes receiving a set of executable instructions; processing, based on the received set of executable instructions, the first set of data and the second set of data to obtain a third set of data; and transmitting the third set of data to a remote electronic device.

Feedback analysis of a digital assistant

Systems and processes for optimizing dialogue policy decisions for digital assistants using implicit feedback are provided. In an example process, a user utterance is received. Based on a text representation of the user utterance, one or more user intents corresponding to the user utterance are determined. A policy action is selected from a plurality of candidate policy actions based on a belief state for the one or more user intents and a policy model. The policy action is performed, including outputting results of the policy action for presentation. A success score for the policy action is determined based on whether one or more predetermined types of implicit user feedback are detected after performing the policy action. A set of parameter values of the policy model is modified using the determined success score.

Optimizing dialogue policy decisions for digital assistants using implicit feedback

Systems and processes for operating a digital assistant using a hierarchical belief state are disclosed. In an example process, a user utterance of a dialog is received. A belief state for the dialog is determined. The belief state comprises a plurality of dialog slots. Each dialog slot of the plurality of dialog slots includes a respective marginal certainty for a concept or property represented by the respective dialog slot. A first dialog slot of the plurality of dialog slots further includes one or more joint certainties for one or more interpretations arising from the first dialog slot. Based on the marginal certainty of each dialog slot of the plurality of dialog slots and the one or more joint certainties of the first dialog slot, a policy action is selected from a plurality of candidate policy actions that correspond to the belief state. The selected policy action is performed.

Hierarchical belief states for digital assistants

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Cambridge, United Kingdom

Blaise Thomson