Translation Quality Control System Using Real-Time Error Detection
Find Innovative SolutionsGenerate Solutions
Solution Overview
Problem
The quality of translations, whether by machine or human translators, is difficult to determine objectively and is often assessed too late in the translation process, leading to variable quality and significant human effort for proofreading, which can be expensive and inadequate.
Innovation Solution
A computing environment with a translation quality control system that assesses translation quality early in the process using an online language test unit and translation quality algorithm, which includes various quality checks and error categorization to prevent submission of low-quality translations, and provides a user interface for quality managers to visualize and correct issues.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If translation quality is assessed during language acceptance testing or post-translation validation, then translation quality can be detected, but the assessment occurs too late in the translation process leading to costly retranslation and significant human effort
Solution Approach 1:
The patent implements quality assessment rules that are executed during the translation process itself rather than after completion. The system evaluates translation quality in real-time by applying predefined rules to source text and detected translation output, enabling early detection of quality issues before the translation is finalized or submitted for acceptance testing.
2Measurement precision
If translation quality is assessed by proofreading, then translation quality can be detected, but significant human effort and expense are required
Solution Approach 1:
The patent replaces the manual proofreading process with an automated computer-implemented system. The system uses a processor to execute quality assessment rules that automatically evaluate translation quality by comparing source text with detected translation output, eliminating the need for human proofreaders while maintaining quality detection capability.
3Productivity
If machine-based translation systems are used, then translation productivity is improved, but translation quality becomes variable and difficult to determine objectively
Solution Approach 1:
The patent implements a feedback mechanism where the computer system automatically evaluates machine translation output using predefined quality assessment rules. The system provides objective quality feedback by comparing the machine translation against the source text and applying linguistic rules, enabling consistent and reliable quality determination that compensates for the variable nature of machine translation.
Data Source
AI summary
Various embodiments of systems, computer program products, and methods to assess translation quality are described herein. In an aspect, a translated text is received during translation of content from a source language to a target language. The received translated text is detected as an incorrect translation by analyzing a number of quality checks in a translation quality algorithm. An error category corresponding to the incorrect translation is determined based on a root cause of the incorrect translation. Further, a counter is incremented in a corresponding error category. When the counter exceeds a threshold, an action to prevent submission of the translation is triggered based on a combined error score. The combined error score is a combined weighted error score from error categories which have exceeded their respective thresholds.