Lilt Launches “Lilt Labs” Because Post-Editing is Painful

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New site enables cross-translation industry collaboration to #fixpostediting

Lilt Inc.

Lilt Inc.

Lilt Labs brings together experts from across the entire spectrum of the language industry in a collaborative environment focused on making and evaluating progress within the translation industry

Lilt - the tech startup where humans and machines meet to tear down language barriers - has announced the launch of labs.lilt.com. Lilt Labs is a collaborative effort between computational linguists, scientists and language professionals designed to address a growing and painful problem in the language space.

Although commercial machine translation (MT) systems and computer-aided translation (CAT) tools have claimed to provide some level of increased efficiency for global enterprises, language companies, and translators, the reality is that post-editing is an inefficient use of a translator’s time. In many cases, modifying machine translation output actually takes longer to edit than translating from scratch. Training and retraining MT systems can also take valuable time away from translators.

The founders of Lilt, Spence Green and John DeNero, both PhDs in Computer Science with a focus on Natural Language Processing (NLP), were disappointed with the lack of innovation within the translation industry over the past twenty years. Customers kept buying translation technology, and translators kept complaining about the lack of efficiency. Green and DeNero sided with the industry, and launched Lilt (http://www.lilt.com) to try and address that industry-wide disillusionment.

Described as the place where “research and language professionals meet,” Lilt Labs brings together experts from across the entire spectrum of the language industry in a collaborative environment focused on making and evaluating progress within the translation industry. Anyone can publish quality work, present CAT and MT evaluations, blog about insights, post academic research and attend thought-leadership webinars. The first of those papers is a quantitative assessment of quality from major MT providers including Lilt, Google, Microsoft, SDL and Systran.

“As academic researchers who are passionate about drastically increasing levels of translation productivity and fixing the lack of innovation in our markets, we saw this as an important first step,” said John DeNero, Co-Founder and Chief Scientist at Lilt. “We welcome the entire community to visit, research, and join us in publishing important insights to finally #fixpostediting.”

“Machine translation research has made great progress in the last two decades, but industry adoption and understanding continues to lag behind technology development,” said Franz Och, Chief Architect of Google Translate. “It's great that Lilt is inviting researchers and industry professionals to collaborate together in one place.”

Anyone wishing to join the discussion or register for more information can do so at labs.lilt.com.
Press Contact: press[at]lilt[dot]com

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