Quality Assurance (QA) of a translated text has been a tedious and time taking task for centuries before the advent of artificial intelligence in the last decade. Traditional QA methods were dependent on human reviewers or proofreaders to catch issues like grammatical errors, inconsistencies, cultural inaccuracies, and stylistic problems. These problems can range from simple typographical and punctuation errors to more complex issues with sentence structure, semantic problems, terminology, and the overall flow of the text. However, the new generation of translation agencies and translators are more reliant on artificial intelligence tools to reduce the time and effort to avoid any inconsistencies in a translated text.
AI tools offer a consistent, fast, and data-driven approach which can solve all of the above issues in a sophisticated and time-bound manner. AI translation quality assurance refers to the use of artificial intelligence to automatically assess the quality of a translated text. These AI translation QA tools use machine learning, natural language processing (NLP), and quality metrics to catch errors, suggest improvements, and provide an overall score for translations. They’re especially valuable in large-scale projects or tight deadlines, where efficiency and reliability matter most. These tools can identify problems in grammar, semantics (meaning), terminology, and style which are often overlooked by human translator. The use of AI QA tools means fewer mistakes, better client satisfaction, and faster delivery.
At ALS, we have AI-powered translation QA tools that are built to integrate seamlessly with popular CAT (Computer-Assisted Translation) and TMS (Translation Management System) platforms. This allows our translators to run quality checks at various stages during pre-processing, mid-translation, and post-editing. This real-time facility allows for immediate quality evaluation, minimizing the chances of errors slipping through and improving overall output consistency. If you’re managing large-scale localization efforts of your SaaS projects with multiple linguists and languages, these tools ensure that everyone adheres to the same quality standards, no matter where they’re working from.