{"id":1811,"date":"2023-10-02T16:10:15","date_gmt":"2023-10-02T14:10:15","guid":{"rendered":"https:\/\/www-staging.systransoft.com\/?post_type=stories&p=1811"},"modified":"2023-12-05T17:27:58","modified_gmt":"2023-12-05T16:27:58","slug":"xtm","status":"publish","type":"stories","link":"https:\/\/www-staging.systransoft.com\/de\/ressourcen\/customer-stories\/xtm\/","title":{"rendered":"XTM"},"content":{"rendered":"\n
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\n KUNDENGESCHICHTE<\/span>\n

With XTM, harnessing extra value from your language assets <\/h1>\n

The new feature of XTM and SYSTRAN<\/p>\n<\/div>\n <\/div>\n

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KEY FIGURES<\/h2>\n
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2022<\/h3>\n

Foundation of XTM<\/p>\n<\/div>\n <\/div>\n <\/div>\n

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26 billion<\/h3>\n

words translated per year<\/p>\n<\/div>\n <\/div>\n <\/div>\n

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227 <\/h3>\n

unique languages<\/p>\n<\/div>\n <\/div>\n <\/div>\n

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+22 BLEU<\/h3>\n

points increase by combining both Neural Fuzzy + Specialization<\/span><\/p>\n<\/div>\n <\/div>\n <\/div>\n <\/div>\n <\/div>\n <\/keys-component>\n\n\n\n\n\n

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Generic vs Customized Neural Machine Translation<\/span><\/h2>\n

Machine translation usage is becoming <\/span>more widespread and more strategic<\/span> for enterprises. Professionals are more and <\/span>more<\/span> demanding in terms of quality and productivity. <\/span>Therefore, the need for customization is higher than ever. Customization must be easy to use and fast to execute in order to serve all the different use cases within a company.\u200b<\/span><\/p>\n

\u200b<\/span>Throughout the years, machine translation went through major technological shifts<\/strong>: \u200b<\/span><\/p>\n

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  1. Rule based MT (RBMT)<\/span><\/strong>: customization was mandatory for MT to be usable.\u200b<\/span><\/li>\n
  2. Statistical MT (SMT)<\/strong>:<\/span> led to a major leap in quality with the use of massive data but there was little focus on customization at that time.\u200b<\/span><\/li>\n
  3. NMT<\/strong>:<\/span> introduced a real breakthrough in terms of quality and fluency, still the demand for customization from the professional users increased a lot.<\/span> Now custom NMT is becoming a standard.<\/span><\/li>\n<\/ol>\n<\/div>\n \n \n \n \n \n <\/div>\n\n \n
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    L\u00f6sung<\/p>\n \n \n

    How does fuzzy matches work ?<\/span><\/h2>\n

    The XTM AI-enhanced TM feature <\/span>sends fuzzy matches<\/span>* to the neural machine translation engine as reference material. Those fuzzy matches come from the translation memory and<\/span> provide additional clues to the MT engine. <\/span>Translation memories and machine translation work hand in hand to find the best translation. The quality of Machine Translation gets <\/span>optimized in real time<\/span> to <\/span>save post-editing efforts.\u200b<\/span><\/p>\n

    \u200b<\/span><\/p>\n

    Validated translation memories <\/span>are key<\/span> here and a very valuable asset for companies who translate contents. With the AI-enhanced TM feature, validated translations from the translation memories help the MT engine produce a <\/span>high-quality translation<\/span> based on validated content stored in the TM.\u200b<\/span><\/p>\n

    \u200b\u200b<\/span>*A fuzzy match consists in a similar sentence with a reasonably high percentage of match. They are not exactly the same, but quite similar.<\/em><\/span><\/p>\n<\/div>\n \n \n \n \n \n <\/div>\n\n \n

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    Info XTM<\/span><\/h2>\n

    XTM International was formed in 2002 when they spotted a need for high-quality, enterprise-class translation technologies that would keep pace with the fast-evolving demands of globalization<\/strong>.\u200b <\/span>\u200b<\/span>Today, the ability to update and localize large volumes of content \u2013 quickly and easily<\/strong> \u2013 is business-critical for more organizations than ever before. Their innovative Enterprise Translation Management System<\/strong> with an integrated CAT tool<\/strong> helps achieve this.\u200b <\/span>\u200b<\/span>XTM Cloud TMS is based on open standards and is securely accessed via a browser.\u200b\u200b<\/span><\/p>\n

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    RESULT<\/h3>\n

    Improvement by combining both Neural Fuzzy + Specialization > 18 + 4 = +22 BLEU points increase expected\u200b<\/span><\/p>\n\n <\/div>\n\n

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    Ronald Egle\u200b<\/h4>\n

    Content Systems Administrator Ariel Corporation<\/h5>\n <\/div>\n <\/div>\n
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    By using XTM and SYSTRAN, we\u2019ve been able to find extra value in our language assets. <\/span>We had a phenomenal setup with our content management system feeding automatically into and out of XTM. Adding SYSTRAN MT to the process made it even better.<\/span><\/p>\n<\/div>\n<\/blockquote>\n

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    VORTEILE<\/p>\n<\/h2>\n <\/div>\n

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    \n \"Symbol\"\n <\/div>\n <\/div>\n

    Costs reduction<\/h3>\n <\/div>\n <\/div>\n
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    \n \"Symbol\"\n <\/div>\n <\/div>\n

    Translation quality enhancement on new content<\/h3>\n <\/div>\n <\/div>\n
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    \n \"Symbol\"\n <\/div>\n <\/div>\n

    Help with the incremental improvement of the NMT engines using validated assets that already exist<\/h3>\n <\/div>\n <\/div>\n
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    \n \"Symbol\"\n <\/div>\n <\/div>\n

    Author style adaptation and consistent brand voice<\/h3>\n <\/div>\n <\/div>\n
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    \n \"Symbol\"\n <\/div>\n <\/div>\n

    Reduction in post-editing effort<\/h3>\n <\/div>\n <\/div>\n \n <\/div>\n <\/div>\n <\/div>\n<\/partnerships-component>\n\n\n\n
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    \n entdecken<\/span>\n

    Sie verwenden auch SYSTRAN<\/h2>\n <\/div>\n
    Weiterlesen\n

    CLAAS<\/h2>\n
    \n \"\"\n <\/div>\n <\/div>\n
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    \n \"Symbol\"<\/span>\n Weiterlesen\n

    weit herholen<\/h2>\n
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    \n \"Symbol\"<\/span>\n Weiterlesen\n

    Lexcelera – TWorks<\/h2>\n
    \n \"\"\n <\/div>\n <\/div>\n <\/div>\n<\/div>\n
    \n Alle entdecken\n
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    \n Blog Daily MT<\/span>\n

    Alles \u00fcber maschinelle \u00dcbersetzung, aktuelle Neuigkeiten und Technologien<\/h2>\n <\/div>\n\n
    \n Entdecken Sie alle unsere Artikel\n
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    \n \"visual\"\n See the article\n
    \n Systran-Soft<\/span>\n <\/div>\n

    What Is Quebec\u2019s Bill 96?<\/h3>\n <\/div>\n
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    \n \"visual\"\n See the article\n
    \n Systran-Soft<\/span>\n <\/div>\n

    Machine Translation Under the Microscope<\/h3>\n <\/div>\n
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    \n \"visual\"\n See the article\n
    \n Systran-Soft<\/span>\n <\/div>\n

    Machine Translation: Does Your Company Truly Control Its Sensitive Data?<\/h3>\n <\/div>\n
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    \n \"visual\"\n See the article\n
    \n Systran-Soft<\/span>\n <\/div>\n

    AI-Powered Search and Automated Translation: The Perfect Match<\/h3>\n <\/div>\n
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    \n \"visual\"\n See the article\n
    \n Systran-Soft<\/span>\n <\/div>\n

    The winning strategy for your business Machine Translation: LLMs vs Specialized AI<\/h3>\n <\/div>\n
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    \n \"visual\"\n See the article\n
    \n Systran-Soft<\/span>\n <\/div>\n

    Shaping a Translation Ecosystem in Biotech<\/h3>\n <\/div>\n <\/div>\n
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    \n Alle entdecken<\/a>\n <\/div>\n\n <\/div>\n <\/blog-swiper-component>\n\n\n\n
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    \n Schlie\u00dfen Sie sich \u00fcber +1000 Unternehmen an, die SYSTRAN nutzen\n <\/h2>\n

    Erweitern Sie Ihr Unternehmen und wachsen Sie mit SYSTRAN<\/p>\n<\/div>\n

    \n 14-t\u00e4gige kostenlose Testversion\n