Picture-Based Semantic Interlingua for Multilingual Conversion
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Solution Overview
Problem
Current language conversion systems face challenges in efficiently converting a generic, semantically-oriented interlingua into any natural language, particularly for individuals with language processing impairments or disabilities, as they often require direct translation rather than an intermediary language.
Innovation Solution
A computerized method and system that utilizes a cascade of rule engines to convert a picture-based semantic interlingua into natural languages, employing graph and tree representations to generate sentences, allowing for the selection and manipulation of attributes and relations, and incorporating a prediction module to improve communication functionality.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Adaptability or versatility
If a picture-based semantic interlingua is used as an intermediary language, then language conversion between different natural languages is enabled, but the system complexity increases due to the need for multiple rule engines and conversion modules
Solution Approach 1:
The patent implements a picture-based semantic interlingua as an intermediary representation that mediates between different natural languages. The system converts source language text to picture-based semantic representations, then converts these representations to target language text, enabling multilingual conversion without direct language pairs. This intermediary approach allows the system to handle multiple language conversions through a unified intermediate format.
Solution Approach 2:
The conversion system is segmented into distinct functional modules: a first conversion module that converts natural language text to picture-based semantic interlingua, and a second conversion module that converts the interlingua back to natural language text. This segmentation allows each module to specialize in specific conversion tasks and enables independent optimization and maintenance of conversion rules for different language directions.
2Productivity
If direct translation is provided instead of using an intermediary language, then communication efficiency is improved, but the system cannot serve individuals with language processing impairments who benefit from picture-based communication
Solution Approach 1:
The system dynamically adapts its communication mode based on user needs. For individuals with language processing impairments, the system provides picture-based semantic representations that enhance understanding. For typical users, the system can operate in direct translation mode for efficiency. The conversion modules can be selectively activated or deactivated based on the communication context and user profile.
Solution Approach 2:
The patent applies different conversion qualities to different user groups. For users with language processing impairments, the system provides enhanced picture-based semantic representations with detailed visual semantics. For other users, the system provides standard text-based translation. This local quality differentiation allows the system to optimize for accessibility where needed while maintaining efficiency elsewhere.
3Measurement precision
If a cascade of rule engines is used to convert interlingua to natural language, then conversion accuracy is improved, but the processing time and computational resources increase
Solution Approach 1:
The system performs preliminary conversion of source text to picture-based semantic interlingua representations before final translation to target language. This preliminary action creates a standardized intermediate form that captures the semantic meaning independently of the target language structure, allowing for more accurate and context-aware translation in the second conversion stage.
Solution Approach 2:
The patent replaces traditional direct mechanical translation mechanisms with a two-stage conversion process using picture-based semantic representations. Instead of directly mapping source language structures to target language structures, the system substitutes this with conversion through semantic picture representations, which encode meaning in a language-independent format that facilitates more accurate translation.
Data Source
AI summary
The embodiments herein achieve a picture based communication system. The system allows users option to select one or more pictures, and any associated attributes. The selection of one or more pictures, and any associated attributes is taken as input. The selected words and attributes are converted to a graph representation, and subsequently the graph representation is converted to a sentence in target language. The method further involves predicting new relations, words, and attributes for further selection by user.