Cross-Assistant Command Processing via Translation Mediator
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Solution Overview
Problem
Current speech processing systems lack the ability to seamlessly interact and share commands between multiple virtual assistants, limiting their functionality in translating and processing natural language inputs across different language platforms.
Innovation Solution
A virtual assistant system that enables cross-assistant command processing by using a multi-assistant component to detect wakewords and translate commands between different speech-processing systems, allowing for the integration of multiple virtual assistants to process and respond to user commands across various languages.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Adaptability or versatility
If speech processing systems operate independently without cross-assistant integration, then each system maintains simple architecture and clear functionality, but the system lacks the ability to translate and process commands across different language platforms
Solution Approach 1:
The patent introduces a translation service as an intermediary component that mediates between different speech processing systems. When a command is received in one language, the translation service translates it to another language and forwards it to the appropriate assistant system, enabling cross-language command processing without requiring direct integration between all assistant systems.
Solution Approach 2:
The patent creates a universal command processing architecture where a single speech processing system can handle commands intended for multiple different assistant systems. The system determines which assistant should receive the command based on the translated command content, allowing one system to serve multiple functions across different language platforms.
2Adaptability or versatility
If multiple speech processing systems are integrated to enable cross-language command processing, then language platform compatibility improves, but the difficulty of detecting and measuring command routing increases
Solution Approach 1:
The patent implements feedback mechanisms where the system monitors and tracks command routing decisions. The translation service and assistant system communicate back about command processing status and language detection results, allowing the system to learn from previous interactions and improve its ability to detect and measure which assistant should receive which command over time.
3Adaptability or versatility
If cross-assistant command processing is implemented with translation services, then functionality across different languages is enhanced, but processing time increases due to additional translation steps
Solution Approach 1:
The patent implements preliminary action by pre-translating commands before they are routed to assistant systems. The translation service performs the translation in advance, and the system caches or stores translated command patterns for future use, reducing the time required for translation during actual command processing.
Solution Approach 2:
The patent introduces dynamic routing where the system can adapt its command processing path based on real-time conditions. If translation is not strictly necessary or if the command can be understood in the original language by any assistant, the system dynamically bypasses the translation step, reducing processing time while maintaining multi-language capability when needed.
Data Source
AI summary
A speech-processing system may provide access to one or more virtual assistants via a voice-controlled device. A user may leverage a first virtual assistant to translate a natural language command from a first language into a second language, which the device can forward to a second virtual assistant for processing. The device may receive a command from a user and send input data representing the command to a first speech-processing system representing the first virtual assistant. The device may receive a response in the form of a first natural language output from the first speech-processing system along with an indication that the first natural language output should be directed to a second speech-processing system representing the second virtual assistant. For example, the command may be in the first language, and the first natural language output may be in the second language, which is understandable by the second speech-processing system.