Rich Text Translation via Image-Based Format Validation
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Solution Overview
Problem
The translation of rich text from a source language to a target language is challenging due to the rich-text format syntax, which often confuses translators and leads to mistranslation, especially when dealing with various rich-text segments having different syntax structures.
Innovation Solution
A method that determines one or more candidate formats for source rich text by rendering it in different formats and selecting a target format based on image validation, providing a translation editing environment tailored to the target format to efficiently edit and translate the rich text.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Productivity
If translators directly translate rich text with format syntax, then translation process is simple, but translation accuracy deteriorates due to confusion between format characters and semantic content
Solution Approach 1:
The patent segments rich text into distinct components: format syntax elements (e.g., **, [], $$) and semantic content elements. By identifying and separating these segments, the system can apply different processing rules to each type, preventing format characters from being mistranslated while maintaining efficient processing of actual content.
Solution Approach 2:
The patent introduces an intermediary validation mechanism that checks whether identified format syntax is correct before translation. This intermediary layer acts as a mediator between the raw rich text and the translation process, verifying format validity and preventing incorrect format characters from interfering with translation accuracy.
2Measurement precision
If translators manually identify and handle format syntax, then translation accuracy improves, but translation time increases due to great efforts needed
Solution Approach 1:
The patent implements a self-service mechanism where the system automatically identifies, validates, and processes format syntax elements without requiring manual translator intervention. The validation module autonomously determines whether syntax is correct and handles format characters appropriately, freeing translators to focus on semantic content while maintaining high translation accuracy.
Solution Approach 2:
The patent replaces the manual mechanical process of format identification and handling with an automated computational system. The validation module uses algorithmic approaches to detect and process format syntax, substituting human effort with automated mechanical processing that is both accurate and time-efficient.
3Stability of the object's composition
If rich text format syntax is preserved during translation, then original formatting is maintained, but translation quality deteriorates due to mistranslation of format characters
Solution Approach 1:
The patent applies different quality standards to different parts of the rich text. Format syntax elements receive one type of processing (validation and protection from translation), while semantic content elements receive another type of processing (normal translation). This local differentiation ensures that format characters are not mistranslated while maintaining formatting consistency throughout the document.
Data Source
AI summary
Embodiments of the present disclosure relate to a method, system, and computer program product for translation of rich text. In some embodiments, a method is disclosed. According to the method, one or more candidate formats are determined for source rich text. A target format for the source rich text is selected from the one or more candidate formats based on one or more corresponding images obtained from rendering the source rich text in the one or more candidate formats. Based on the target format, a translation editing environment is provided for editing a translation of the source rich text. In other embodiments, a system and a computer program product are disclosed.