Voice Interface Device Leadership Negotiation
Find Innovative SolutionsGenerate Solutions
Solution Overview
Problem
Existing voice interface devices struggle to handle multiple users, coordinate responses among multiple devices, and mitigate noise interference effectively, leading to user confusion and suboptimal performance in noisy environments.
Innovation Solution
A system and method that identify a speaker by comparing voice inputs to trained voice models, negotiate leadership among devices for response, and adapt to noise levels by suggesting alternative wake-up methods, ensuring personalized and clear interactions.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Adaptability or versatility
If multiple voice interface devices are deployed in a location, then device functionality and user convenience are improved, but user confusion increases and coordination becomes difficult
Solution Approach 1:
The system segments the voice interface functionality by assigning a leader device and follower devices. The leader device is designated to respond to wake-word commands while follower devices remain silent, creating clear operational segments that prevent user confusion about which device should respond.
Solution Approach 2:
A cloud-based server acts as an intermediary to coordinate multiple voice interface devices. The server receives wake-word commands, determines which device should be the leader based on predefined criteria, and manages the leadership transitions to ensure smooth coordination without user intervention.
2Speed
If voice interface devices continuously monitor for commands, then responsiveness is improved, but energy consumption increases
Solution Approach 1:
Devices use periodic wake-word detection to monitor for user commands rather than continuous processing. The system periodically checks for wake-word triggers in low-power states and only activates full voice processing when a wake-word is detected, significantly reducing energy consumption while maintaining responsiveness.
Solution Approach 2:
The voice interface system uses self-service mechanisms where devices automatically detect wake-word commands and initiate their own processing sequences without external triggering. This allows the system to remain responsive while maintaining low power consumption by only activating intensive processing when necessary.
3Adaptability or versatility
If voice interface devices operate in noisy environments, then functionality is maintained, but voice recognition accuracy decreases
Solution Approach 1:
The system uses noise level detection to identify when environmental noise interferes with voice recognition. Instead of attempting to process commands in noisy conditions, the system detects the noisy environment and provides alternative wake-word commands or waits for quieter moments, converting the harmful noise condition into a trigger for alternative interaction modes.
Solution Approach 2:
The voice interface system incorporates feedback mechanisms that continuously monitor audio quality and noise levels. When poor audio conditions are detected, the system provides feedback to the user through alternative wake-word commands or visual indicators, allowing the user to adjust their interaction approach to achieve better recognition accuracy.
4Ease of operation
If a leader device is designated to respond to commands, then response coordination is improved, but device autonomy is reduced
Solution Approach 1:
A cloud-based server serves as an intermediary that automatically manages device leadership without requiring complex local coordination protocols. The server receives wake-word commands, determines which device should respond based on criteria like proximity or user configuration, and assigns leadership status, simplifying the overall system architecture while maintaining good response coordination.
Solution Approach 2:
The leadership status of voice interface devices is dynamic rather than fixed. The system can transition between different devices being the leader based on changing conditions such as user proximity, device availability, or environmental factors, allowing the system to adapt to various situations while maintaining coordinated responses.
Data Source
AI summary
The various implementations described herein include methods and systems for determining device leadership among voice interface devices. In one aspect, a method is performed at a first electronic device of a plurality of electronic devices, each having microphones, a speaker, processors, and memory storing programs for execution by the processors. The first device detects a voice input. It determines a device state and a relevance of the voice input. It identifies a subset of electronic devices from the plurality to which the voice input is relevant. In accordance with a determination that the subset includes the first device, the first device determines a first score of a criterion associated with the voice input and receives second scores of the criterion from other devices in the subset. In accordance with a determination that the first score is higher than the second scores, the first device responds to the detected input.