Device-Specific Skill Routing via NLU Intent Analysis
Find Innovative SolutionsGenerate Solutions
Solution Overview
Problem
Current speech recognition systems often misinterpret user commands due to a lack of device-specific routing, leading to incorrect device execution of commands without explicit user specification, resulting in an undesirable user experience.
Innovation Solution
The implementation of device-specific skills as top-level skills allows for proper routing of user inputs to appropriate device-specific skills without requiring explicit user reference, using device identifiers and natural language understanding processing to determine intent and prioritize skill invocation.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If device-specific skills are implemented as top-level skills with device identifiers and natural language understanding processing, then command execution accuracy is improved, but system complexity increases
Solution Approach 1:
The system segments skill processing into device-specific top-level skills, each associated with specific device identifiers. This segmentation allows precise routing of commands to the appropriate device context, improving command execution accuracy while maintaining manageable system organization through modular skill components.
Solution Approach 2:
Natural language understanding processing acts as an intermediary layer between user input and skill execution. This mediator interprets user intent and routes commands to the appropriate device-specific skills, enhancing accuracy without requiring direct user specification of device identifiers, thereby managing system complexity through intelligent mediation.
2Device complexity
If explicit user reference to device-specific skills is required, then system complexity is reduced, but ease of operation deteriorates
Solution Approach 1:
The system performs self-service by automatically determining device context and routing commands to appropriate skills without requiring explicit user reference. The natural language understanding processing autonomously interprets user intent and matches it with device-specific skills, improving ease of operation while maintaining organized system architecture through automatic context resolution.
3Measurement precision
If device identifiers are used for routing, then command execution accuracy is improved, but loss of information increases
Solution Approach 1:
Natural language understanding processing serves as an intermediary that preserves user input simplicity while enabling accurate device routing. The mediator translates simple user commands into device-specific operations by inferring device context from the command itself and user profile, maintaining information integrity without requiring explicit device identifiers in user input.
Data Source
AI summary
Techniques for configuring device-specific skills as top-level skills are described. When a system receives a user input the system performs NLU processing to determine an intent of the user input. In some instances, the system may identify a device-specific skill associated with the device interacted with by the user. At least partially in parallel to performing NLU processing to determine the intent of the user input, the system may also perform NLU processing to determine a likelihood that the user input corresponds to an intent actionable by the device-specific skill. Once the system has finished NLU processing, the system may implement one or more prioritization rules to determine whether the user input should be sent to the device-specific skill or another skill of the system.