NLP Analysis System for Local Voice Command Interpretation
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Solution Overview
Problem
Current voice recognition systems often misinterpret user intent due to their inability to accurately process and execute commands, particularly when users provide nuanced or context-dependent requests, leading to incorrect results.
Innovation Solution
A computer system that includes a processor, storage medium, and instructions for analyzing user input through a series of narrowing cycles, utilizing components like an affix detector, lexicalizer, and grammar checker to identify concepts and execute relevant actions, allowing for local processing without reliance on remote servers.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If voice data is transcribed and analyzed using remote transcription services and natural language processing modules, then language recognition capability is improved, but system complexity and dependency on external services increase
Solution Approach 1:
The patent extracts the core NLP functionality from remote transcription services and implements it locally within the mobile device. The executable code contains embedded NLP capabilities that were previously external dependencies, allowing the device to perform language analysis independently without requiring continuous connection to remote servers.
Solution Approach 2:
The patent introduces an intermediate NLP module that bridges the gap between raw voice data and application execution. This module processes and interprets natural language inputs locally, serving as a mediator between the user's spoken commands and the device's executable applications, thereby reducing dependency on external transcription services.
2Measurement precision
If multiple narrowing cycles are executed to identify concepts from user input, then command interpretation accuracy is improved, but processing time increases
Solution Approach 1:
The patent performs preliminary processing of user input by converting voice data to text and conducting initial NLP analysis before executing the full command interpretation workflow. This preliminary action prepares the data in advance, allowing subsequent narrowing cycles to operate more efficiently on pre-processed information rather than raw input.
Solution Approach 2:
The patent implements dynamic adjustment of processing depth based on input complexity. For simple commands, fewer narrowing cycles are executed, while complex queries trigger more extensive analysis. This dynamic approach allows the system to adapt processing time to actual needs, maintaining high accuracy for complex commands while minimizing delay for simple ones.
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.