Context-Aware Output Device Selection for Multi-Device Speech
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Solution Overview
Problem
Existing speech processing systems struggle with efficiently selecting the optimal output device for user inputs across multiple devices in a given space, leading to inconsistent and suboptimal user experiences.
Innovation Solution
A system that determines the best output device based on user preferences and context, using ASR and NLU to identify user intents and select devices capable of providing the requested content, considering factors like device proximity, compatibility, and user history.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If the system automatically selects output devices based on multiple factors (proximity, compatibility, user history), then the user experience consistency is improved, but the device selection complexity increases
Solution Approach 1:
The system performs self-service by automatically selecting the optimal output device based on pre-configured criteria (proximity, compatibility, user history) without requiring manual user intervention. The speech processing system autonomously evaluates available devices and makes selection decisions, thereby improving user experience consistency while avoiding the complexity of manual device selection interfaces.
Solution Approach 2:
The system changes selection parameters dynamically by considering multiple factors including device proximity, content compatibility, and user historical preferences. By adjusting the weight of these parameters based on the specific context, the system achieves reliable and consistent device selection across different scenarios without requiring complex user configuration.
2Manufacturing precision
If the system considers multiple factors for device selection (proximity, compatibility, user history), then the output quality is improved, but the processing time increases
Solution Approach 1:
The system performs preliminary actions by pre-evaluating and caching device compatibility information and user preference data before actual speech processing occurs. This advance preparation allows the system to quickly select output devices during runtime without performing complex real-time analysis, thereby maintaining high output quality while minimizing processing time delays.
3Ease of operation
If the system directs output to the most suitable device regardless of input location, then the user experience is enhanced, but the system coordination complexity increases
Solution Approach 1:
The system implements a universal device selection framework that can handle multiple device types (speakers, displays, audio systems) and multiple selection criteria (proximity, compatibility, user history) through a single coordinated mechanism. This multi-functional approach allows the system to direct output to the most suitable device regardless of input location while managing coordination complexity through a unified selection architecture.
Data Source
AI summary
Example embodiments provide techniques for configuring a system to receive an input at a source device and present an output at another device within the same space as the source device. The output device may be selected based on various factors relating to the capabilities of the output device, the type of output responsive to the user input, whether the output device is active, whether the output device was recently used and others.