Assistant Arbitration in Multi-Assistant Speech Systems
Find Innovative SolutionsGenerate Solutions
Solution Overview
Problem
Current speech processing systems face challenges in determining the appropriate virtual assistant to handle user commands, especially when multiple assistants are involved, leading to inefficient command execution and user confusion due to the lack of seamless assistant arbitration and handoff mechanisms.
Innovation Solution
The system implements an assistant arbitration process that uses the assistant metadata component to select the most capable assistant for executing a command, involving the multi-assistant skill to perform handoffs by updating the active assistant profile and notifying the user through audible or visual indications, ensuring that the correct assistant handles the request based on the command's intent and associated skills.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Adaptability or versatility
If multiple virtual assistants are deployed to handle different commands, then system capability and versatility are improved, but assistant selection complexity and user confusion increase
Solution Approach 1:
The patent introduces an assistant arbitration component as an intermediary that mediates between multiple virtual assistants and user commands. This component receives the natural language input, evaluates which assistant is best suited to handle the command based on available skills and capabilities, and routes the command to the appropriate assistant. This mediator approach resolves the contradiction by maintaining multiple assistants (improving versatility) while centralizing the selection logic (reducing complexity for users).
Solution Approach 2:
The system performs preliminary evaluation and arbitration of assistant suitability before the user interacts with the command execution. The assistant arbitration component pre-assesses which assistant should handle incoming commands based on their skill sets and capabilities, so that when a user issues a command, the routing decision has already been made. This preliminary action eliminates the need for users to manually select assistants, reducing selection complexity while maintaining multiple capable assistants.
2Reliability
If assistant arbitration is implemented to select the most capable assistant, then command execution accuracy is improved, but processing time and system complexity increase
Solution Approach 1:
The assistant arbitration component performs preliminary assessment of assistant capabilities and command suitability before actual command execution. By pre-evaluating which assistant should handle each type of command based on their skill sets, the system ensures accurate routing (improving reliability) while making the selection process efficient through pre-established evaluation criteria (minimizing processing time).
Solution Approach 2:
The system implements feedback mechanisms where the assistant arbitration component continuously learns from command execution outcomes. By monitoring which assistants successfully handle commands and which require arbitration, the system refines its routing decisions over time. This feedback loop improves command execution accuracy while optimizing processing time by learning from past performance patterns.
3Ease of operation
If seamless handoff mechanisms are implemented between assistants, then user experience is improved, but system complexity and notification overhead increase
Solution Approach 1:
The assistant arbitration component serves as an intermediary that manages handoffs between virtual assistants. When a command requires transfer from one assistant to another, the arbitration component coordinates this transition seamlessly, handling the complexity of state transfer and user notification. This mediator approach improves user experience by making handoffs invisible to users while containing system complexity within the arbitration component rather than distributing it throughout the entire system.
Data Source
AI summary
A speech-processing system may provide access to multiple virtual assistants. Speech-processing systems may perform actions for or on behalf of users with the aid of skills; e.g., a shopping skill, navigation skill, communications skill, etc. Some skills may be associated with more than one assistant. The speech-processing system may determine which assistant to invoke upon receiving a command from a user device. The identity of the virtual assistant is propagated to the skill and the device, as well as other components of the speech-processing system. In some cases, however, a multi-assistant skill may determine that an assistant other than the one initially selected by the speech-processing system is to handle the command. The skill may send the identity of the new assistant back to the speech-processing system. The speech-processing system may restart the command dissemination process to provide each component of the system with the updated assistant identity.