Machine Translation User Interface Correction Feedback Loop
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Solution Overview
Problem
Conventional machine translation methods require significant time, cost, and manpower to achieve high-quality translations, even with the latest machine translation technologies, as they often necessitate reviewer corrections.
Innovation Solution
A machine translation apparatus and method that includes a user interface unit for displaying initial and corrected translation results, analyzing differences, and using these corrections to improve subsequent translations within a document, while considering translation direction information and user preferences.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Productivity
If machine translation technology is applied, then translation speed is improved, but translation quality deteriorates
Solution Approach 1:
The system implements feedback by analyzing the difference between the corrected translation result and the initial machine translation result, then reflecting this analysis to perform machine translation for subsequent sentences. This creates a continuous improvement loop where user corrections are systematically incorporated to enhance future translation quality without requiring manual review of each sentence.
Solution Approach 2:
The system performs preliminary analysis of the correction pattern between initial and corrected translations, extracting translation direction information and unique features before applying them to subsequent translations. This preliminary processing enables the system to proactively improve translation quality for future sentences rather than reactively correcting each one.
2Manufacturing precision
If reviewer correction is performed to achieve high-quality translation, then translation quality is improved, but time and cost increase
Solution Approach 1:
The system applies partial correction by analyzing only the difference between initial and corrected translations to extract translation direction information, rather than requiring complete manual review and correction of all translations. This partial analysis approach achieves quality improvement while significantly reducing the time and effort required compared to full manual review.
Solution Approach 2:
The system enables self-service by automatically reflecting the analysis result of correction differences back into subsequent machine translation operations. The translation system serves itself by learning from corrections and autonomously improving its own performance for subsequent sentences without requiring continuous human intervention.
3Device complexity
If machine translation is performed for each sentence independently, then processing simplicity is maintained, but translation consistency deteriorates
Solution Approach 1:
The system achieves universality by using the same translation model for both initial machine translation and corrected translation generation, while incorporating translation direction information extracted from correction analysis. This allows the single translation model to adapt to different contexts and maintain consistency across sentences without requiring separate processing systems.
Data Source
AI summary
Proposed are a machine translation apparatus and a machine translation method for displaying a translation result through a user interface. The machine translation method may include: display an initial machine translation result for a first translation target sentence; correcting the initial machine translation result according to a manipulation result of a user on the user interface unit, and displaying the corrected machine translation result; and analyzing a difference between the corrected machine translation result and the initial machine translation result, and reflecting the analysis result to perform machine translation on a second translation target sentence. The machine translation apparatus and the method can be used to efficiently acquire a high-quality translation within a short time while minimizing time, cost and effort of a user, which used to be required for a conventional machine translation process.