A Recipe for Better Machine Translation
An appeal to everyone involved in the translation ecosystem to realize the full benefits of machine translation.
An appeal to everyone involved in the translation ecosystem to realize the full benefits of machine translation.
The report compares TAUS DeMT performance against available major machine translation engines in 8 language pairs for the eCommerce domain, 18 language pairs for the Medical/Pharma domain, and 4 language pairs for the Financial domain.
TAUS bilingual corpora in the eCommerce, medical/pharmaceutical, and finance domains are now available to Amazon Translate users on the AWS Marketplace
The new service is powered by Amazon Translate and enhanced by TAUS Data
Intento's 2021 State of Machine Translation allows you to choose the best-fit MT engines for your language pair and industry sector.
TAUS gives SYSTRAN access to large volumes of domain-specific language data and both have agreed to integrate their marketplaces.
TAUS and Intento enter into a strategic partnership to realize the full potential of MT technologies
SYSTRAN and TAUS have agreed to collaborate on creating a solid supply of data and models for trainers and developers of machine translation engines.
The TAUS Transcreation Best Practices and Guidelines is published with the hope of forming a useful basis for further, industry-wide discussion around the definitions and processes of transcreation.
TAUS publishes the first DQF Business Intelligence Bulletin for the translation and localization industry.
TAUS launches Matching Data: a new technique of selecting language data for the training and tuning of machine translation (MT) engines. This new approach is a perfect fit for the new generation of Neural MT, which is much more sensitive to the quality of the training data.
24-page report. Blockchain and Translation industry overview. ICOs, business use-cases, solution analysis, crypto chatter and further reading, a cautionary tale.
Lionbridge Technologies announced that several of its company innovators will lead discussions and thought leadership sessions at the TAUS Annual Conference in San Jose, California.
In 2015, four leading European institutions and companies set out to solve machine translation’s four main problems: training, context, scalability, and data collection. After a brief scare when Google Translate went neural, the project is now in beta and set for enterprise-grade release in Q4 2017.
As language translation emerges as a yardstick for progress in artificial intelligence, high quality human translation data becomes a prized asset. The race for AI leadership sees Baidu host translation marathons across China to fill its data trove.
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