Terminology Proposal Engine for Automated Translation
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Solution Overview
Problem
Existing language translators face limitations in accurately and efficiently translating technical content across languages, particularly when English is used as an intermediate language, and manual translation is time-consuming and skill-dependent.
Innovation Solution
A terminology proposal engine that processes source language terminology to determine target language equivalents using a multi-channel approach, integrating complex logic, user-defined configuration profiles, and statistical analysis to provide accurate and efficient translations.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If manual translation by native speakers is used, then translation accuracy is improved, but translation time and cost increase significantly
Solution Approach 1:
The patent uses English as an intermediary language to bridge source languages and target languages. The translation system translates from source language to English, then from English to target language, improving automation capability while maintaining reasonable accuracy through the mediating role of English
Solution Approach 2:
The patent replaces manual mechanical translation work with an automated computer-based translation system. The system uses algorithms and computational methods to perform translation tasks that were previously done manually by native speakers, significantly reducing time and cost
2Productivity
If existing language translators using English as intermediate language are used, then translation efficiency is improved, but translation accuracy deteriorates
Solution Approach 1:
The patent implements feedback mechanisms where translation results are evaluated and used to improve future translations. The system learns from translation outcomes and adjusts its processing accordingly, enhancing accuracy while maintaining efficiency
Solution Approach 2:
The patent performs preliminary processing of source text including terminology extraction and analysis before main translation. This preliminary action prepares the data in advance, enabling more accurate and efficient translation by pre-identifying key terms and their contexts
3Measurement precision
If manual translation processes are used, then translation quality is improved, but productivity and scalability worsen
Solution Approach 1:
The patent creates a universal translation system that can handle multiple source languages and target languages through a common architecture. The system processes various language pairs using the same methodology, improving productivity and scalability while maintaining consistent quality across different language combinations
Solution Approach 2:
The patent segments the translation process into distinct components: terminology extraction, terminology analysis, and translation execution. This segmentation allows each component to be optimized independently and processed in parallel, improving overall productivity while maintaining quality through specialized processing at each stage
Data Source
AI summary
An input terminology is received in a source language to determine a target language proposal. In a proposal engine when a configuration profile is available the following steps are performed. A set of target language equivalents are determined by applying a user-defined set of approaches to the input terminology. Statistics is computed corresponding to the set of target language equivalents. A target language proposal from the set of target language equivalents is determined based on the computed statistics. The target language proposal along with the computed statistics is displayed in a graphical user interface.