Voice Command Intent Recognition via Segmented Analysis
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Solution Overview
Problem
Current voice recognition systems often misinterpret user intent due to failure in isolating speech from background noise and incorrectly executing commands based on incomplete or misinterpreted voice inputs, leading to unsatisfactory user experiences.
Innovation Solution
A computer system with a processor and storage medium that includes an input module for receiving voice data, a dispatcher to isolate speech using stereo inputs, and an analysis system executing narrowing cycles to identify concepts and action items, allowing for accurate command execution based on user intent.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If voice data is transmitted to a transcription service for automatic transcription, then text conversion is achieved, but the system cannot accurately capture user intent leading to incorrect command execution
Solution Approach 1:
The patent segments the voice processing task into multiple specialized modules: transcription service for text conversion, sentiment analysis module for emotional context, topic modeling module for subject identification, and intent recognition module for command interpretation. Each module processes a specific aspect of the voice input independently, then their results are integrated to achieve comprehensive understanding that preserves user intent information while maintaining accurate text conversion.
2Adaptability or versatility
If natural language processing analyzes text for synonyms, then language flexibility is improved, but the system fails to distinguish between similar concepts leading to execution errors
Solution Approach 1:
The patent introduces topic modeling and sentiment analysis as intermediary processing layers between text transcription and intent recognition. These intermediaries enrich the text data with contextual metadata (topics, sentiments, entities) before passing to the intent recognition module. This intermediary processing maintains language flexibility for synonym recognition while adding precision through contextual disambiguation, preventing execution errors.
3Loss of information
If the system processes complete voice commands, then comprehensive information is captured, but background noise interferes with accurate speech recognition
Solution Approach 1:
The patent extracts only the relevant speech components from the complete voice input by using topic modeling to identify key subjects and sentiment analysis to detect emotional markers. This extraction process separates meaningful information from background noise and irrelevant portions of the voice command, capturing comprehensive intent information while filtering out noise interference through selective feature extraction.
Data Source
AI summary
The invention provides a computer system for interacting with a user. A set of concepts initially forms a target set of concepts. An input module receives a language input from the user. An analysis system executes a plurality of narrowing cycles until a concept packet having at least one concept has been identified. Each narrowing cycle includes identifying at least one portion of the language and determining a subset of concepts from the target set of concepts to form a new target subset. An action item identifier identifies an action item from the action items based on the concept packet. An action executer that executes an action based on the action item that has been identified.