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US Patent 11380310 Low-latency intelligent automated assistant

Patent 11380310 was granted and assigned to Apple (company) on July, 2022 by the United States Patent and Trademark Office.

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Contents

Is a
Patent
Patent
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Patent attributes

Patent Applicant
Apple (company)
Apple (company)
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Current Assignee
Apple (company)
Apple (company)
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Patent Jurisdiction
United States Patent and Trademark Office
United States Patent and Trademark Office
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Patent Number
113803100
Patent Inventor Names
Alejandro Acero0
Hepeng Zhang0
Date of Patent
July 5, 2022
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Patent Application Number
169987860
Date Filed
August 20, 2020
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Patent Citations
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US Patent 10410637 User-specific acoustic models
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US Patent 10372814 Methods and system for fast, adaptive correction of misspells
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US Patent 10389876 Semiautomated relay method and apparatus
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US Patent 10402066 Information processing terminal and control method
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US Patent 10403283 Voice interaction at a primary device to access call functionality of a companion device
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US Patent 10417037 Systems and methods for integrating third party services with a digital assistant
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US Patent 10417554 Methods and systems for neural and cognitive processing
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US Patent 10446142 Crafting feedback dialogue with a digital assistant
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Patent Citations Received
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US Patent 11514897 Systems and methods relating to bot authoring by mining intents from natural language conversations
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US Patent 11984124 Speculative task flow execution
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Patent Primary Examiner
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Edwin S Leland, III
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CPC Code
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G10L 25/87
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G10L 2015/223
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G06F 3/16
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G10L 15/1822
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G10L 25/78
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G10L 13/04
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G10L 15/183
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G10L 15/22
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Systems and processes for operating a digital assistant are provided. In an example process, low-latency operation of a digital assistant is provided. In this example, natural language processing, task flow processing, dialogue flow processing, speech synthesis, or any combination thereof can be at least partially performed while awaiting detection of a speech end-point condition. Upon detection of a speech end-point condition, results obtained from performing the operations can be presented to the user. In another example, robust operation of a digital assistant is provided. In this example, task flow processing by the digital assistant can include selecting a candidate task flow from a plurality of candidate task flows based on determined task flow scores. The task flow scores can be based on speech recognition confidence scores, intent confidence scores, flow parameter scores, or any combination thereof. The selected candidate task flow is executed and corresponding results presented to the user.

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