Document Translation via Regex Segmentation and Phonetic Transliteration
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Solution Overview
Problem
The translation of documents into multiple languages faces challenges due to formatting issues caused by differences in font sizes and the need for manual or inaccurate machine translation, making it a cumbersome and expensive process.
Innovation Solution
A method and system that utilize regular-expression codes to identify and translate fixed and variable text in documents, employing a translation dictionary look-up and phonetic transliteration to generate correctly formatted output documents in multiple languages.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Extent of automation
If machine translation is used to translate documents, then translation cost is reduced and automation is improved, but translation accuracy deteriorates
Solution Approach 1:
The document is segmented into fixed text and variable text portions. Fixed text is translated using machine translation while variable text (such as names, numbers, codes) is identified and protected from translation through regex patterns. This segmentation allows automated processing of translatable content while preserving accuracy for non-translatable elements.
Solution Approach 2:
A regex-based identification system acts as an intermediary between the machine translation process and the final output. The system first identifies variable text portions using regex patterns, then applies machine translation only to fixed text portions, thereby mediating the translation process to maintain both automation and accuracy.
2Measurement precision
If manual translation by language experts is used, then translation accuracy is improved, but translation cost increases and automation deteriorates
Solution Approach 1:
The document is divided into fixed text and variable text portions. Only fixed text requires manual review or machine translation, while variable text is automatically identified and preserved. This segmentation reduces the overall workload for manual translation while maintaining accuracy for critical content.
Solution Approach 2:
The system uses regex patterns to automatically identify and protect variable text portions without human intervention. This self-service capability handles the identification task that would otherwise require manual analysis, reducing the need for expensive language experts while maintaining translation quality.
3Productivity
If translation is performed without considering font size differences, then translation speed is improved, but formatting quality deteriorates
Solution Approach 1:
The system performs preliminary identification of variable text portions using regex patterns before the translation process begins. By pre-marking these portions, the subsequent translation process can proceed quickly without needing to analyze each word individually, while still maintaining formatting quality through the pre-established protection markers.
4Manufacturing precision
If regular expression codes are used to identify fixed and variable text, then formatting quality is improved, but processing complexity increases
Solution Approach 1:
The regex-based identification system serves multiple functions: it identifies variable text portions, marks them for protection, and structures the document for subsequent translation processing. This multi-functionality reduces the need for separate processing steps, thereby managing complexity while maintaining formatting quality.
Data Source
AI summary
A method and system for transforming a source document to an output document is disclosed. The method includes preparing a first file that contains a fixed text and a variable text by generating a regular-expression code for the text in the source document. The variable text in the first file is translated from a source language to an output language, wherein the translation is performed on the basis of at least one of a translation dictionary look-up, and a phonetic transliteration. The method then generates the output document in a pre-decided format as required in the output document from the first file.