Multi-Assistant Replanner Orchestrating Voice Command Handoffs
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Solution Overview
Problem
Current speech processing systems face challenges in seamlessly managing interactions with multiple virtual assistants, particularly in handling commands that require handoffs between different assistants, due to complexities in providing consistent outputs and timing of responses across distinct subsystems.
Innovation Solution
The implementation of a multi-assistant system that includes a replanner component to orchestrate handoffs between command processing subsystems, using plan data to manage user experience and command execution, ensuring smooth transitions and accurate routing of commands between different virtual assistants.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Adaptability or versatility
If multiple command processing subsystems are used to provide diverse virtual assistant functionalities, then the versatility and capabilities of the system are improved, but the complexity of managing interactions and handoffs between subsystems increases
Solution Approach 1:
An orchestrator component is introduced as an intermediary between multiple command processing subsystems. The orchestrator receives user inputs, determines the appropriate subsystem for handling each command, and coordinates handoffs between subsystems. This mediator approach resolves the contradiction by enabling diverse virtual assistant capabilities through multiple subsystems while reducing management complexity through centralized coordination.
Solution Approach 2:
The orchestrator component serves multiple functions: receiving user inputs, identifying appropriate command processing subsystems, managing handoffs between subsystems, and maintaining system state. This multi-functional design allows a single component to handle diverse virtual assistant capabilities while simplifying the overall system architecture.
2Measurement precision
If handoffs between command processing subsystems are implemented to route commands to appropriate virtual assistants, then the precision of command routing is improved, but the timing and coordination of responses become more complex
Solution Approach 1:
The orchestrator pre-identifies the appropriate command processing subsystem for each user input before the actual command execution. By determining the target subsystem in advance and preparing the handoff, the system achieves accurate command routing while minimizing delays. The orchestrator maintains a map of subsystem capabilities and pre-evaluates which subsystem should handle each type of command.
Solution Approach 2:
The orchestrator implements feedback mechanisms to track the state of command processing across subsystems. When a handoff occurs, the orchestrator monitors the response timing and coordination, adjusting its routing decisions based on observed performance. This feedback loop ensures accurate command routing while optimizing response timing through continuous system state awareness.
Data Source
AI summary
A speech-processing system may provide access to multiple virtual assistants via one or more voice-controlled devices. Each assistant may leverage language processing and language generation features of the speech-processing system, while handling different commands and/or providing access to different back applications. Different assistants may be available for use with a particular voice-controlled device based on time, location, the particular user, etc. The voice-controlled device may include components for facilitating user interaction with multiple assistants. For example, a multi-assistant component may facilitate enabling/disabling assistants, assigning gestures and/or wakewords, etc. The multi-assistant component may handle routing commands to a command processing subsystem corresponding to an assistant invoked by the command. The voice controlled device may further include observer components, each configured to monitor the voice-controlled device for invocations of a particular assistant.


