Nowadays the world of translation is turning more and more to machine translation for several reasons. Before going through that, though, we need to make the point of what machine translation is.
By: Geri Mileva As machine translation grows as a field and welcomes new people, there is an increasing contribution of female leaders in the areas of implementation, advocacy, engineering, and computer science. With this article, we hope to provide to highlight the achievements of female leaders in MT and create mentoring opportunities for fresh specialists […]
We’re seeing a rise in the number of projects and requests that rely on raw machine translation. When Custom.MT started, clients wanted to train models to improve the productivity of human translators, and to reduce the cost. Today, more than half of the requests we get are about doing the translation fully automatically, without a […]
In this article, we explain how anonymization works in machine translation (MT) to ensure GDPR compliance. Learn the essential steps for anonymizing data, protecting personal information, and maintaining translation quality. Explore the use of pseudonymization, named entity recognition, and secure processing techniques for translation companies, legal firms, government agencies, and highly-regulated industries. In 2018, the […]
Today’s race for leadership in machine translation (MT) is between IT Giants Google and Microsoft, a few small specialized companies like DeepL and ModernMT, and open-source projects. What does it take, and how does it feel — to expand the boundaries of science and business at the very top of the machine translation field?
In this article, you will discover new ground-breaking opportunities for localization companies and companies in other fields that are willling to optimize their efforts with machine translation. The insights are here to assist you in building a perfect strategy, both tech-intensive and cost-efficient, for 2022. Author: Konstantin Dranch 1. Bigger, Bolder Programs Salvo Giammarresi (AirBnB) […]
Infographic Machine Translation could signify a great boost for humanity, although being a rather niche business. According to research done over the last 2 years, it is calculated to have gained a 16% in growth. Important: MT is at least twice as big as TMS, and growing faster! Custom.MT Co-founder and researcher Konstantin Dranch has […]
The year 2021 marked the arrival of speech to speech translation in the commercial world.
Scientists are working on making the underlying technology smoother and more accurate, engineers are integrating it into practical use cases. At the same time, there is an explosion in neural voices. Between July and September, three companies in this area got funded, Murf.ai, Wellsaid Labs, and Lovo.ai. As a result, localization professionals can now choose from 20+ providers of pre-made voices, or even clone their own voice to generate personalized speeches.
Author: Konstantin Dranch Subtitlers are looking to adopt customized machine translation, but video localization systems are not ready for it yet. Here is what they could do to expedite up the process. Since Google introduced AutoML translation and Microsoft created Custom Translator, text translation management systems (TMS) have developed excellent support for trainable machine translation. […]
Partner Spotlight: Pangeanic Smart governments are hiring data scientists to further automate what governments do for their citizens. These data scientists work on creating data highways, so that the information that flows into systems is structured, and a thousand different applications can spring forth from it in the future. In the meanwhile, Manuel Herranz and his company […]
Authors: Will Pace, Konstantin Dranch and Silvia Schiavoni Globalese is an affordable machine translation system tailored for trainers. Thanks to a great sandbox and a direct connection of users with the company’s founders, Globalese has become a very popular choice with the MT trainer community. Custom.MT presents the story of Globalese and the founders’ views […]
Engines from IT giants such as Google Translate, Microsoft, and Yandex often win in quality because search engine companies possess the whole internet as their data pool. However, with very specialized content and excellent translation memory, this advantage is nullified. In this case study, the engine from a smaller MT vendor Globalese won in all […]