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Introduction of Smartling’s AI Translation Toolkit; Enhanced XTM Cloud Integration; and Adaptive MT Model in Matecat

A series of translation support solutions and updates featuring superior features, tools, and improvements have just been launched by technology companies. Translators will have powerful aids to create accurate and efficient translations while saving time and effort.

Smartling Launches AI Translation Toolkit

Smartling, Inc. has announced the AI Translation Toolkit, the only end-to-end AI augmentation product for the translation process. This toolkit gives customers access to advanced AI features proven to significantly improve the quality, cost, and speed of translators’ work. In fact, the AI Translation Toolkit can reduce translation costs and turnaround times by 50% while helping translators achieve a quality score of 98 or higher.
Unlike other solutions that only provide necessary components, the AI Translation Toolkit combines all essential capabilities into a streamlined, easy-to-use solution, allowing customers to achieve results similar to Smartling’s AI-powered Human Translation (AIHT) service. Since customers can innovate their processes with AI without having to purchase and integrate different technologies from multiple vendors, the purchasing and implementation process is very easy. The AI Translation Toolkit uses LLMs to effectively leverage translation memory and glossary, improve post-machine translation processing, and provide tools to evaluate the AI translation edit effort, resulting in high-quality, cost-effective translations.
Specific benefits:
  • AI Translation Memory - The AI Translation Toolkit enhances the capabilities of translation memory. In addition to applying SmartMatches and high-match results, the AI Translation Toolkit also performs LLM match corrections.
  • AI Term Insertion—The AI Translation Toolkit takes traditional terminology insertion a step further, ensuring that terminology replacements are contextually appropriate and grammatically correct rather than simply replacing each term. In addition, the tool automatically screens content and formatting to handle issues such as whitespace, missing or extra tags, and placeholders to reduce errors in the content.
  • Edit Effort Estimation—The AI Translation Toolkit assesses each string's level of editing effort and categorizes it into three levels.

XTRF Unveils Enhanced XTM Cloud Integration

XTRF International has released XTRF 9.9, an update that enhances integration between XTM Cloud and XTRF and improves management and invoicing capabilities.

XTRF 9.9 brings together the strengths of XTRF and XTM Cloud, providing users with a seamless experience and unlocking new possibilities in translation management.

Now, projects created in XTRF Smart Projects can be automatically pushed to XTM Cloud, with all project information automatically imported from XTRF. Project managers will be able to manage projects entirely from XTRF, while translators can leverage all the powerful features of XTM Cloud, including advanced terminology features, a robust translation memory, query management functionality, QA checks, and more, to quickly produce high-quality translations.

Matecat Announces Free Adaptive MT Feature

Translated, the leading provider of AI-powered language solutions has released an update to Matecat. The update integrates ModernMT’s adaptive neural machine translation (MT) model as the default MT engine and is provided free of charge to all logged-in Matecat users. This system was recently named the top MT software in IDC’s latest MarketScape on Machine Translation and the most advanced implementation of responsive MT by CSA Research.

Designed to increase translator productivity, Matecat now takes the translation process to the next level by providing users with MT match results that improve in real-time. MT suggestions are now refined after each edit and translation memory update. These suggestions are also adjusted to the user’s style and the style of the project translated. With adaptive MT, translators no longer have to make the same edits. As a result, they can work faster with more contextual and relevant suggestions and can focus more on the nuances that make a difference in overall quality.

Wisdom Admin

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