고객 사례

XTM을 통해 언어 자산에서 추가적인 가치를 활용할 수 있습니다

XTM 및 SYSTRAN의 새로운 기능

주요 수치

2022

XTM의 기초

260억

매년 번역된 단어

227

고유 언어

+22 블루

포인트 증가 Neural Fuzzy + Specialization을 모두 결합하여

Generic vs Customized Neural Machine Translation

Machine translation usage is becoming more widespread and more strategic for enterprises. Professionals are more and more demanding in terms of quality and productivity. 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.

Throughout the years, machine translation went through major technological shifts:

Rule based MT (RBMT): customization was mandatory for MT to be usable.
Statistical MT (SMT): led to a major leap in quality with the use of massive data but there was little focus on customization at that time.
NMT: introduced a real breakthrough in terms of quality and fluency, still the demand for customization from the professional users increased a lot. Now custom NMT is becoming a standard.

Solution

How does fuzzy matches work ?

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

Validated translation memories are key 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 high-quality translation based on validated content stored in the TM.

*퍼지 매치는 비교적 높은 일치율을 갖는 유사한 문장으로 구성된다. 그것들은 정확히 같은 것은 아니지만 상당히 비슷하다.

정보 XTM

XTM International은 2002년 XTM에 맞는 고품질 엔터프라이즈급 번역 기술이 필요함을 발견하면서 설립되었습니다 빠르게 진화하는 세계화의 요구.. 오늘날, 대량의 컨텐츠를 업데이트하고 로컬라이징하는 기능 - 빠르고 쉽게 - 그 어느 때보다 많은 기업의 비즈니스 크리티컬한 환경 그들의 혁신성 엔터프라이즈 번역 관리 시스템 일체형으로 CAT 도구 이 목표를 달성하도록 도와줍니다. XTM Cloud TMS는 개방형 표준을 기반으로 하며 브라우저를 통해 안전하게 액세스됩니다.

결과

Neural Fuzzy + Specialization > 18 + 4 = +22 BLEU 포인트를 모두 결합하면 성능이 향상될 것으로 예상됩니다.

로널드 에글이

컨텐츠 시스템 관리자 Ariel Corporation

By using XTM and SYSTRAN, we’ve been able to find extra value in our language assets. 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.