Tilde has the great honor of serving as the local partner for the bi-annual ELIA Networking Days, which will take place Riga, Latvia, from April 24-26, 2014. The conference is one of the year’s biggest events for the language industry.
Online language technology journal The Big Wave has published an interview with Tilde’s CEO, Andrejs Vasiļjevs. In the interview, Vasiļjevs discusses the benefits of machine translation for the translation industry. He also introduces Tilde’s machine translation platform LetsMT, which allows users to build customized MT systems.
The head of Tilde's Localization Department, Nansija Lībiete, will give a presentation on the benefits of machine translation at the 6th Riga Symposium on Pragmatic Aspects of Translation on January 30 in Riga.
Representatives from Tilde met with Mongolian Foreign Minister Luvsanvandan Bold and his delegation today at the IT Demo Centre in Riga. During the meeting, customer relations manager Toms Žunna presented Tilde’s language technology products, including the machine translation platform LetsMT.
Tilde’s CEO Andrejs Vasiļjevs will give a presentation at the conference Open Data: Challenges and Opportunities, organized today at the University of Latvia by the Latvian Open Technology Association. Vasiļjevs's talk, scheduled for 16:45, will be entitled Open Data, National Identity, and Europe's Digital Single Market.
Representatives from Tilde have been invited to attend a special event this evening in Riga marking the introduction of the euro in Latvia, hosted by Prime Minister Valdis Dombrovskis. The event’s honorary guests are European Council president Herman Van Rompuy and European Commission President José Manuel Barroso. Latvia officially joined the eurozone on January 1.
A comparative evaluation of three machine translation systems – Tilde’s LetsMT, Google Translate, and Microsoft’s Bing Translator – has confirmed that LetsMT produces higher-quality translations for Baltic languages. The evaluation was performed using the BLEU (Bilingual Evaluation Understudy) score metric, which evaluates how closely a machine-translated text compares with a professional human-translated document.