Sign Language Interpreter Using Grammar Context Verification
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Solution Overview
Problem
Current language translation systems are inadequate in interpreting sign language into written or auditory forms, as they fail to accurately detect and translate gestures into meaningful language, especially when considering grammar and contextual relevance.
Innovation Solution
A computer-implemented method that uses a capture device to track user gestures, matches them to a lexicon library, and compares successive signs to a grammar library and contextual database to determine their accuracy and meaning, incorporating demographic information for verification.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If multiple sensors and gesture detection algorithms are used to detect sign language gestures, then gesture detection capability is improved, but translation accuracy into meaningful language deteriorates due to inability to consider grammar and context
Solution Approach 1:
The patent introduces an intermediary processing layer between gesture detection and translation output. This layer includes grammar verification modules and contextual analysis components that mediate the translation process, ensuring that detected gestures are translated into grammatically correct and contextually appropriate language while preserving the original meaning
Solution Approach 2:
The system implements feedback mechanisms where translation results are verified against grammar rules and contextual databases. The system continuously refines its translations by comparing output with expected grammatical structures and contextual relevance, improving both gesture detection accuracy and language translation quality simultaneously
2Productivity
If simple gesture-to-word translation is used, then processing speed is improved, but translation meaning accuracy deteriorates
Solution Approach 1:
The patent applies preliminary action by pre-loading grammar rules, contextual databases, and translation dictionaries into the system before processing begins. This allows the system to perform rapid lookups and comparisons during real-time translation without sacrificing accuracy, maintaining both high processing speed and meaningful translation quality
Solution Approach 2:
The translation process is segmented into distinct modular stages: gesture detection, gesture-to-sign matching, grammar verification, contextual analysis, and final translation output. Each segment can be processed independently and in parallel, improving overall processing speed while ensuring that meaning accuracy is maintained through systematic verification at each stage
Data Source
AI summary
A computer implemented method for performing sign language translation based on movements of a user is provided. A capture device detects motions defining gestures and detected gestures are matched to signs. Successive signs are detected and compared to a grammar library to determine whether the signs assigned to gestures make sense relative to each other and to a grammar context. Each sign may be compared to previous and successive signs to determine whether the signs make sense relative to each other. The signs may further be compared to user demographic information and a contextual database to verify the accuracy of the translation. An output of the match between the movements and the sign is provided.