Alisdair Mans Cornwell, Marketing Specialist || Reading Time: 4 minutes
Customers linguistic assets have transformed how organizations handle and streamline multilingual content. Originally, TMs and TBs were straightforward tools for storing and reusing translated phrases and standardised terms, respectively, helping translators maintain consistency and efficiency. However, over the years, the rapid growth of translation technology and localisation tools has taken these linguistic assets to the next level, improving the quality and accuracy of multilingual content across global markets.
In their earliest forms, TMs allowed translators to access previously translated segments for a specific project, increasing translation speed and ensuring consistency. Termbases, on the other hand, provided a database of approved terms specific to the brand or industry, reducing the likelihood of inconsistent terminology. Together, TMs and TBs became essential linguistic assets for translation quality and terminology management, ensuring that large-scale, multilingual projects adhered to brand standards across languages.
As more businesses recognised the importance of brand-specific language, the demand grew for tools that could integrate highly specialised terminology and adapt to evolving industry language. This led to more advanced and customizable CAT (Computer-Assisted Translation) tools, where TMs and TBs were refined and tailored to suit the unique linguistic needs of each organization. These updates allowed businesses to incorporate linguistic assets management into every project, ensuring the translated content would resonate authentically with diverse, international audiences.
The latest evolution in translation technology has brought AI into the mix, allowing for a new level of sophistication. Modern AI tools can seamlessly incorporate customers TMs and TBs, allowing for advanced customisation and quality in content creation and localisation workflows.
For instance, AI can analyse TMs and TBs to identify patterns in language and context, ensuring that phrases are translated accurately while aligning with brand tone and style. Additionally, AI can help detect inconsistencies across large datasets, allowing teams to refine their TMs and TBs continually, which in turn improves translation quality and reduces costly errors.
The fusion of translation memories and termbases with AI is reshaping the Language Service Industry. As organizations increasingly prioritize high quality and on brand localisations, AI powered tools-enhanced with customers TMs and TBs offer a future-proof solution. By combining these traditional linguistic assets with AI-solutions, organizations can expect higher quality translations that are faster, more accurate, and precisely tailored to each unique market and target audience.
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