Automated Transla...
Follow
Find
7.5K views | +0 today
 
Scooped by K Vashee
onto Automated Translation (MT) Trends
Scoop.it!

Evaluating the Learning Curve of Domain Adaptive Statistical Machine Translation Systems | Matecat

Evaluating the Learning Curve of Domain Adaptive Statistical Machine Translation Systems | Matecat | Automated Translation (MT) Trends | Scoop.it
The new frontier of computer assisted translation technology is the effective integration of statistical MT within the translation workflow.
more...
No comment yet.

From around the web

Automated Translation (MT) Trends
Material related to the use and continued development of machine translation
Curated by K Vashee
Your new post is loading...
Your new post is loading...
Scooped by K Vashee
Scoop.it!

The Singularity is Further Than it Appears | Ramez Naam

The Singularity is Further Than it Appears | Ramez Naam | Automated Translation (MT) Trends | Scoop.it
K Vashee's insight:

Why Kurzweil and the Singularity boy are seriously mistaken

more...
No comment yet.
Rescooped by K Vashee from Metaglossia: The Translation World
Scoop.it!

Google hints at seamless translation into any language

Google hints at seamless translation into any language | Automated Translation (MT) Trends | Scoop.it
Seamless translation into any language via a "lightweight wearable" could soon be a reality, suggested Google's mobile czar Sundar Pichai.

Via Charles Tiayon
more...
No comment yet.
Scooped by K Vashee
Scoop.it!

Say what?

Say what? | Automated Translation (MT) Trends | Scoop.it
TALK into your phone in any of the big European languages and a Google app can now turn your words into a foreign language, either in text form or as an electronic...
more...
No comment yet.
Scooped by K Vashee
Scoop.it!

Misconceptions in Machine Translation and Post-Editing

Misconceptions in Machine Translation and Post-Editing | Automated Translation (MT) Trends | Scoop.it
Misconceptions in Machine Translation and Post-Editing (summary)

The more machine translation (MT) expands in the translation world today, the more criticism arises. In this article, I quote thr...
more...
No comment yet.
Scooped by K Vashee
Scoop.it!

The AI Revolution: Road to Superintelligence - Wait But Why

The AI Revolution: Road to Superintelligence - Wait But Why | Automated Translation (MT) Trends | Scoop.it
The topic everyone in the world should be talking about.
more...
No comment yet.
Scooped by K Vashee
Scoop.it!

Stanford system combines software with human intelligence to improve translation

Stanford system combines software with human intelligence to improve translation | Automated Translation (MT) Trends | Scoop.it
Using software to suggest word choices makes professional translators more productive in the $34-billion-a-year market for foreign language translation.
more...
No comment yet.
Scooped by K Vashee
Scoop.it!

Google Translate Sings: "Wrecking Ball" by Miley Cyrus (PARODY) - YouTube

#ballinthesink And now for something COMPLETELY different, a clothed Google Translate of Wrecking Ball!! Enjoy the silliness!! SUBSCRIBE and be sure to like ...
more...
No comment yet.
Scooped by K Vashee
Scoop.it!

Neural networks draw on context to improve machine translations

Neural networks draw on context to improve machine translations | Automated Translation (MT) Trends | Scoop.it
Dutch researchers have improved the output of a statistical machine translation system by examining the context in which words are found
more...
No comment yet.
Scooped by K Vashee
Scoop.it!

UTIC-2014. Understanding MT ROI & Best Practices — Presentation Videos — Ukrainian Translation Industry Conference

UTIC-2014. Understanding MT ROI & Best Practices — Presentation Videos — Ukrainian Translation Industry Conference | Automated Translation (MT) Trends | Scoop.it
more...
No comment yet.
Scooped by K Vashee
Scoop.it!

Translation and Technology: Where are we heading?

Translation and Technology: Where are we heading? | Automated Translation (MT) Trends | Scoop.it
The effects of new digital means of translation are starting to affect the way we interact with the world. If everyone can understand every foreign language with the use of new technology, how can ...
more...
YourTerm's curator insight, March 27, 5:19 AM

"New technology is really starting to affect the way people interact with language around the world".

Scooped by K Vashee
Scoop.it!

How are machine translation engines trained? A look under the hood.

How are machine translation engines trained? A look under the hood. | Automated Translation (MT) Trends | Scoop.it
How are machine translation engines trained to run like the well-oiled machines? Learn how they continue to produce better quality translations over time.
more...
No comment yet.
Scooped by K Vashee
Scoop.it!

The revolution of machine translation by Gabriel Guzovsky (CAT Tools,Technology) - ProZ.com translation articles

The revolution of machine translation by Gabriel Guzovsky (CAT Tools,Technology) - ProZ.com translation articles | Automated Translation (MT) Trends | Scoop.it
Translation article entitled "The revolution of machine translation" ("The revolution of machine translation" - http://t.co/j7m44OETEb by G.Guzovsky)...
K Vashee's insight:

A translator who does not see MT as the horrific enemy but PT is probably one of the best MT languages for Google

more...
No comment yet.
Scooped by K Vashee
Scoop.it!

Skype Translator Now Fluent in Mandarin Chinese, Italian

Skype Translator Now Fluent in Mandarin Chinese, Italian | Automated Translation (MT) Trends | Scoop.it
Skype Translator has made a huge stride closer to its goal of allowing everyone in the world to be able to converse with each other through technology.
more...
No comment yet.
Scooped by K Vashee
Scoop.it!

Why Machines Alone Cannot Solve the World's Translation Problem

Why Machines Alone Cannot Solve the World's Translation Problem | Automated Translation (MT) Trends | Scoop.it
There is a beautiful simplicity in statistical machine translation, such as Google Translate. Essentially, the more data you have, the better the probability of a high-quality translation as an end result. But what do you do when you don't have enoug...
more...
No comment yet.
Scooped by K Vashee
Scoop.it!

The AI Revolution: Our Immortality or Extinction

The AI Revolution: Our Immortality or Extinction | Automated Translation (MT) Trends | Scoop.it
Superintelligent AI is either going to be a dream or a nightmare for us, and there's not really any in-between.
more...
No comment yet.
Scooped by K Vashee
Scoop.it!

Microsoft Skype Translator Preview: The real-world test

Microsoft Skype Translator Preview: The real-world test | Automated Translation (MT) Trends | Scoop.it
Our conversation was halting at first. Maria in the south of Spain would start to speak and I would reflexively respond, even though I didn’t understand what she was saying. Our...
more...
No comment yet.
Rescooped by K Vashee from Amazing Science
Scoop.it!

A picture is worth a thousand (coherent) words: building a natural description of images

A picture is worth a thousand (coherent) words: building a natural description of images | Automated Translation (MT) Trends | Scoop.it

Via Dr. Stefan Gruenwald
more...
Natural Language Careers's curator insight, November 19, 2014 8:53 AM

Google making progress towards automatic captioning.  Cool stuff.

Scooped by K Vashee
Scoop.it!

What do job trends in the translation industry mean to you?

What do job trends in the translation industry mean to you? | Automated Translation (MT) Trends | Scoop.it
Jobs in the translation industry related to automated translation point to a future of greater automation and faster multilingual content generation.
more...
No comment yet.
Scooped by K Vashee
Scoop.it!

Stanford system combines software with human intelligence to improve translation

Stanford system combines software with human intelligence to improve translation | Automated Translation (MT) Trends | Scoop.it
Using software to suggest word choices makes professional translators more productive in the $34-billion-a-year market for foreign language translation.
more...
No comment yet.
Scooped by K Vashee
Scoop.it!

eMpTy Pages: Understanding The Drivers of Success with the Business Use of Machine Translation

eMpTy Pages: Understanding The Drivers of Success with the Business Use of Machine Translation | Automated Translation (MT) Trends | Scoop.it
more...
No comment yet.
Scooped by K Vashee
Scoop.it!

The Incredible Shrinking Planet

The Incredible Shrinking Planet | Automated Translation (MT) Trends | Scoop.it
What happens when we bridge the geographic and linguistic gaps that have separated us for centuries?
more...
No comment yet.
Rescooped by K Vashee from Metaglossia: The Translation World
Scoop.it!

Essays in English yield information about other languages

Essays in English yield information about other languages | Automated Translation (MT) Trends | Scoop.it

Cambridge, Massachusetts - Computer scientists at MIT and Israel’s Technion have discovered an unexpected source of information about the world’s languages: the habits of native speakers of those languages when writing in English.

The work could enable computers chewing through relatively accessible documents to approximate data that might take trained linguists months in the field to collect. But that data could in turn lead to better computational tools.

“These [linguistic] features that our system is learning are of course, on one hand, of nice theoretical interest for linguists,” says Boris Katz, a principal research scientist at MIT’s Computer Science and Artificial Intelligence Laboratory and one of the leaders of the new work. “But on the other, they’re beginning to be used more and more often in applications. Everybody’s very interested in building computational tools for world languages, but in order to build them, you need these features. So we may be able to do much more than just learn linguistic features. … These features could be extremely valuable for creating better parsers, better speech-recognizers, better natural-language translators, and so forth.”

In fact, Katz explains, the researchers’ theoretical discovery resulted from their work on a practical application: About a year ago, Katz proposed to one of his students, Yevgeni Berzak, that he try to write an algorithm that could automatically determine the native language of someone writing in English. The hope was to develop grammar-correcting software that could be tailored to a user’s specific linguistic background.

Family resemblance

With help from Katz and from Roi Reichart, an engineering professor at the Technion who was a postdoc at MIT, Berzak built a system that combed through more than 1,000 English-language essays written by native speakers of 14 different languages. First, it analyzed the parts of speech of the words in every sentence of every essay and the relationships between them. Then it looked for patterns in those relationships that correlated with the writers’ native languages.

Like most machine-learning classification algorithms, Berzak’s assigned probabilities to its inferences. It might conclude, for instance, that a particular essay had a 51 percent chance of having been written by a native Russian speaker, a 33 percent chance of having been written by a native Polish speaker, and only a 16 percent chance of having been written by a native Japanese speaker.


Via Charles Tiayon
K Vashee's insight:

Interesting way to build new ways to link two languages together

more...
Charles Tiayon's curator insight, July 27, 2014 8:37 PM

Cambridge, Massachusetts - Computer scientists at MIT and Israel’s Technion have discovered an unexpected source of information about the world’s languages: the habits of native speakers of those languages when writing in English.

The work could enable computers chewing through relatively accessible documents to approximate data that might take trained linguists months in the field to collect. But that data could in turn lead to better computational tools.

“These [linguistic] features that our system is learning are of course, on one hand, of nice theoretical interest for linguists,” says Boris Katz, a principal research scientist at MIT’s Computer Science and Artificial Intelligence Laboratory and one of the leaders of the new work. “But on the other, they’re beginning to be used more and more often in applications. Everybody’s very interested in building computational tools for world languages, but in order to build them, you need these features. So we may be able to do much more than just learn linguistic features. … These features could be extremely valuable for creating better parsers, better speech-recognizers, better natural-language translators, and so forth.”

In fact, Katz explains, the researchers’ theoretical discovery resulted from their work on a practical application: About a year ago, Katz proposed to one of his students, Yevgeni Berzak, that he try to write an algorithm that could automatically determine the native language of someone writing in English. The hope was to develop grammar-correcting software that could be tailored to a user’s specific linguistic background.

Family resemblance

With help from Katz and from Roi Reichart, an engineering professor at the Technion who was a postdoc at MIT, Berzak built a system that combed through more than 1,000 English-language essays written by native speakers of 14 different languages. First, it analyzed the parts of speech of the words in every sentence of every essay and the relationships between them. Then it looked for patterns in those relationships that correlated with the writers’ native languages.

Like most machine-learning classification algorithms, Berzak’s assigned probabilities to its inferences. It might conclude, for instance, that a particular essay had a 51 percent chance of having been written by a native Russian speaker, a 33 percent chance of having been written by a native Polish speaker, and only a 16 percent chance of having been written by a native Japanese speaker.