Wakeword-Based Speech Routing With Distinct Voice Feedback
Find Innovative SolutionsGenerate Solutions
Solution Overview
Problem
Current speech processing systems struggle to seamlessly hand off user requests between different speech processing components while providing a transparent and desirable customer experience, often failing to efficiently route commands to the most capable system for processing.
Innovation Solution
The system detects wakewords to determine the appropriate speech processing system for handling user requests, allowing for dynamic selection and handoff between ASR, NLU, and TTS components, while notifying the user through appropriate feedback mechanisms such as voice styles and LED colors, ensuring that requests are routed to the most capable system for processing.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Adaptability or versatility
If the system uses multiple speech processing systems with different capabilities, then the ability to handle diverse user requests improves, but the complexity of routing and coordinating between systems increases
Solution Approach 1:
The speech processing functionality is divided into separate specialized systems (ASR, NLU, TTS, voice activity detection) rather than using a single monolithic system. Each system handles specific aspects of speech processing, allowing the patent to leverage the strengths of different systems for different tasks while maintaining manageable complexity through clear functional boundaries.
Solution Approach 2:
The patent introduces a routing mechanism that acts as an intermediary to coordinate between multiple speech processing systems. This mediator determines which system should handle each user request based on the detected wakeword and request type, simplifying the coordination complexity by providing a centralized decision-making layer.
2Productivity
If the system dynamically selects different speech processing systems based on wakeword detection, then processing efficiency improves, but the complexity of system selection logic increases
Solution Approach 1:
The system performs wakeword detection beforehand to pre-determine which speech processing system should handle the incoming request. By detecting the wakeword in advance, the system can efficiently route the request to the appropriate processor without requiring complex real-time decision-making during the processing phase.
Solution Approach 2:
Different wakewords are associated with different speech processing systems, allowing the system to automatically self-select the appropriate processor based on the detected wakeword. This self-service mechanism reduces the need for complex external coordination logic, as the system autonomously determines the best processing path.
3Loss of information
If the system provides feedback to users about which system is processing their request, then transparency and user experience improve, but the complexity of feedback mechanisms increases
Solution Approach 1:
The system implements feedback mechanisms that notify users about which speech processing system is handling their request. This feedback can include visual indicators (such as LED colors) or auditory cues that provide transparency about the processing path, enhancing user understanding and experience without requiring complex communication protocols.
Data Source
AI summary
A device having a voice-based interface activates or “wakes” when it detects an utterance that includes a wakeword; the device may be installed in a vehicle, such as an automobile. The device may distinguish between different wakewords; a different speech processing system may be associated with each wakeword, and each speech processing engine may have its own speech style and associated applications and functions.