Digital Assistant Intent Routing for Third-Party App Integration
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Solution Overview
Problem
Existing digital assistants cannot effectively integrate with locally stored applications, particularly third-party applications, and lack a natural-language interface with them.
Innovation Solution
A method for a digital assistant to receive natural-language user input, identify an intent and associated parameters, and provide these to a software application, either on the same device or a secondary device, to execute tasks or present a list of compatible applications if the intent cannot be fulfilled locally.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Adaptability or versatility
If digital assistants use traditional interface methods to interact with applications, then they can communicate with built-in applications, but they cannot effectively integrate with third-party applications stored locally on the user device
Solution Approach 1:
The patent implements a universal integration layer that enables the digital assistant to interact with multiple types of applications (built-in and third-party) through a common interface. This layer translates natural language commands into application-specific actions, allowing the assistant to perform functions across diverse applications without requiring separate integration mechanisms for each application type.
Solution Approach 2:
The patent introduces an intermediary component that acts as a mediator between the digital assistant and the application ecosystem. This intermediary layer handles the complexity of application integration by providing standardized communication protocols and translation mechanisms, thereby enabling seamless interaction with third-party applications without directly increasing the core assistant's complexity.
2Ease of operation
If digital assistants provide natural-language interface with applications, then user interaction becomes more intuitive, but existing systems lack the capability to process and execute application-specific intents
Solution Approach 1:
The patent segments the natural language processing pipeline into distinct components: intent detection, parameter extraction, and action execution. Each component handles a specific aspect of the interaction, with intent detection focusing on identifying the user's goal, parameter extraction capturing relevant details, and action execution translating these into application-specific commands. This segmentation improves both the ease of operation and the reliability of intent recognition.
Solution Approach 2:
The patent implements feedback mechanisms where the system validates detected intents against available applications and provides corrective information when mismatches occur. This feedback loop enhances intent recognition accuracy by learning from validation results and adjusting the natural language processing accordingly, while maintaining intuitive user interaction through natural language.
Data Source
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AI summary
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.