Apple Inc.

Ashish Garg

Robert A Walker

Thomas R Gruber

Brandon J Newendorp

Rohit Dasari

Richard Donald Giuli

Jonathan H Russell

Corey J Peterson

Vineet Khosla

Carey E Radebaugh

Rushin N Shah

Matthew S Seigel

Harry Joseph Saddler

Matthias Paulik

Lin Li

Shweta Grampurohit

Xiao Charles Yang

Gennaro Frazzingaro

Mubarak Ali Seyed Ibrahim

Deepak Muralidharan

Blaise Thomson

Justine Kao

Lavanya Colinjivadi Viswanathan

Robert A Walker, Ii

Anuj Kumar

Robert A Ii Walker

Systems and processes for application integration with a digital assistant are provided. In accordance with one example, a method includes, at an electronic device having one or more processors and memory, receiving a natural-language user input; identifying, with the one or more processors, an intent object of a set of intent objects and a parameter associated with the intent, where the intent object and the parameter are derived from the natural-language user input. The method further includes identifying a software application associated with the intent object of the set of intent objects; and providing the intent object and the parameter to the software application.

Application integration with a digital assistant

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

Speech recognition is performed on a received utterance to determine a plurality of candidate text representations of the utterance, including a primary text representation and one or more alternative text representations. Natural language processing is performed on the primary text representation to determine a plurality of candidate actionable intents, including a primary actionable intent and one or more alternative actionable intents. A result is determined based on the primary actionable intent. The result is provided to the user. A recognition correction trigger is detected. In response to detecting the recognition correction trigger, a set of alternative intent affordances and a set of alternative text affordances are concurrently displayed.

User interface for correcting recognition errors

Systems and processes for operating an intelligent automated assistant are provided. An example process receives natural language input and determines a first and a second parsing result for the natural language input. The first and the second parsing results include respective mappings of one or more properties of a domain corresponding to the natural language input to one or more words of the natural language input. The process determines whether the second parsing result corresponds to a data item in a knowledge base, and in accordance with determining that the second parsing result corresponds to the data item in the knowledge base, the process ranks the second parsing result higher than the first parsing result. Based on the ranking, the process generates a task flow using the second parsing result and executes the task flow to provide an output based on the data item.

Knowledge-based framework for improving natural language understanding

Growing community of inventors

Bellevue, WA, United States of America

Ashish Garg