Context-Aware Voice Assistant Without Wake Word
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Solution Overview
Problem
Existing voice assistants require a predefined wake-up word to activate voice recognition, limiting their usefulness as users often discuss tasks and needs without remembering to utter the word, rendering the digital assistant ineffective unless explicitly activated.
Innovation Solution
A device with a processor and storage that executes voice recognition on spoken speech without a user command, correlating detected phrases to ancillary information and returning relevant data, such as adding items to a shopping list or calendar, using natural language processing to determine context and appropriateness of voice assistance.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Ease of operation
If voice recognition is activated only by a predefined wake-up word, then the device can process spoken commands, but the assistant remains ineffective when users discuss tasks without remembering to utter the wake-up word
Solution Approach 1:
The system performs preliminary voice recognition processing continuously in the background without requiring a wake-up word. The processor monitors audio input and executes voice recognition algorithms proactively, correlating detected phrases with ancillary information before the user needs to explicitly activate the assistant. This preliminary action ensures tasks are captured naturally during conversation.
2Adaptability or versatility
If the device continuously monitors and processes speech without a wake-up word, then the assistant becomes more useful for natural conversations, but the device complexity and processing requirements increase
Solution Approach 1:
The patent extracts and processes only specific relevant phrases from continuous speech streams. Instead of analyzing all speech equally, the system identifies and correlates particular phrase patterns with ancillary information in databases. This selective extraction reduces processing complexity while maintaining adaptability to natural speech patterns.
Solution Approach 2:
The system introduces an intermediary correlation layer between speech recognition and full voice assistant activation. The processor first recognizes phrases, then correlates them with ancillary information in databases to determine appropriate responses. This intermediary step filters and structures speech data, reducing the complexity burden on the main processing system.
3Productivity
If voice recognition executes without user command, then the assistant provides continuous support, but the risk of false positives and inappropriate responses increases
Solution Approach 1:
The system implements feedback loops where the processor continuously monitors speech patterns, correlates phrases with database entries, and refines recognition accuracy based on correlation results. The feedback mechanism adjusts processing parameters and correlation thresholds dynamically, improving precision while maintaining continuous productivity. Users can also provide feedback to refine the system's understanding of their speech patterns.
Data Source
AI summary
A voice assistant of a device is activated not by a key word being spoken but by recognizing speech and determining whether context of the speech indicates that audible voice assistance is appropriate.