Language Tech Market News
57.6K views | +5 today
Follow
Language Tech Market News
The Home of Language Intelligence
Curated by LT-Innovate
Your new post is loading...
Your new post is loading...
Scooped by LT-Innovate
Scoop.it!

#NLP Crossing the Divide to Low-Resource Languages?

#NLP Crossing the Divide to Low-Resource Languages? | Language Tech Market News | Scoop.it

The opportunities and challenges in the application of Natural Language Processing in low income countries

more...
No comment yet.
Scooped by LT-Innovate
Scoop.it!

Speech Research: Switch From Up-front Data to Adaptive Learning to Digitise Low-Resource Languages

Speech Research: Switch From Up-front Data to Adaptive Learning to Digitise Low-Resource Languages | Language Tech Market News | Scoop.it

Rather than funding research into Welsh speech AI, the Welsh government may well do better by backing research into this new kind of adaptive learning technology.
Because all current speech AI systems handle the speech centrally (it’s not done in the device, but in a remote server farm), these systems could gather data from hundreds of users worldwide (or all over Wales) to rapidly learn. So the message to Welsh speakers today may be to not buy that English-language Google Home or Amazon Alexa if you want Google or Amazon to produce a system that works in Welsh. But if you do have one, as its software develops over the next few years, try speaking Welsh to it as much as possible. It may just surprise you and Siaradwch â chi yn Gymraeg.

more...
No comment yet.
Scooped by LT-Innovate
Scoop.it!

Viterbi Low-Resource MT Project Gets IARPA Grant

Viterbi Low-Resource MT Project Gets IARPA Grant | Language Tech Market News | Scoop.it
The Intelligence Advanced Research Projects Activity presented researchers from the USC Viterbi School of Engineering’s Information Sciences Institute with a $16.7 million grant to develop a tool that will more efficiently translate low-resource languages. The project, titled SARAL, which stands for Summarization and domain-Adaptive Retrieval, will focus on creating systems that will provide automated translations and summaries of those languages.
more...
No comment yet.
Scooped by LT-Innovate
Scoop.it!

@TranslateMe Builds #Blockchain System to Overcome Low-Resource Language Barrier

@TranslateMe Builds #Blockchain System to Overcome Low-Resource Language Barrier | Language Tech Market News | Scoop.it

TranslateMe owner: The single biggest thing missing from any current translation platform is data. It’s why they [market leaders] only support 20 high-quality languages out of 200. They don’t have the data to process” less common languages, or those predominantly spoken-word languages that lack large databases of written material. “13 million people [in South Africa] speak Zulu, and it’s terribly translated on Google.” Lloyd wants to resource data via human contributions, incentivized via the TranslateMe token, as a way to “incentivize human data contributions for more obscure languages.”

more...
No comment yet.
Scooped by LT-Innovate
Scoop.it!

New Models to Bring Low-resource Languages and Spoken Dialects into #NeuralMT

New Models to Bring Low-resource Languages and Spoken Dialects into #NeuralMT | Language Tech Market News | Scoop.it

Microsoft Research. We tackled the challenge of insufficient parallel data using a Semi-Supervised Universal Neural Machine Translation approach that requires only a few thousand parallel sentences for an extremely low-resource language to achieve a high-quality machine translation system. This exciting research will be presented at the 16th Annual Conference of the North American Chapter of the Association for Computational Linguistics: Human Language Technologies (NAACL-2018).

more...
No comment yet.
Scooped by LT-Innovate
Scoop.it!

Another US University to Build #MT for 'Low Resource' Languages

Another US University to Build #MT for 'Low Resource' Languages | Language Tech Market News | Scoop.it

Philipp Koehn, a computer science professor at John Hopkins U's Whiting School of Engineering, is leading a group of 20 professors, research scientists, post-doctoral fellows, and doctoral students in an effort to build a system that can respond to inquiries typed in English based on documents written in so-called "low resource" languages, which means there is relatively little written material in these languages.

LT-Innovate's insight:

Trending? This follows (but with different purpose) a similar project started in S. California.this year 

more...
No comment yet.