Speechless Recognition: Can AI Transcribe a Language It Has Never Heard?
Breakthroughs in multilingual speech models are rapidly expanding language coverage for ASR. But what about endangered languages with little to no training data?
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low-resource languages
Working Around Machine Translation’s Need for Large-Scale Training Data
Unlike some fields in machine learning, machine translation still requires large sets of training data. The solution? Creating more data when none (or not enough) exists.
Synthetic Data Can Improve Machine Translation – New Research from IBM, UCSD
New research from IBM and UC San Diego explores synthetic parallel data as a means of pre-training machine translation models — with promising results.
Low Resource, High Potential — NeuralSpace CEO Felix Laumann on Democratizing NLP
NeuralSpace CEO, Felix Laumann, joins the pod to discuss how they overcome the lack of research, data, and tools when training NLP models in low-resource languages.
More Than Hype: Meta Reveals Two-Pronged Machine Translation Roadmap
Part of the billions of dollars going into the Metaverse will undoubtedly go into these two areas of machine translation. Meta AI reveals its MT roadmap and the people working on it.
MIT Tackles the Ultimate Low-Resource Machine Translation Challenge
MIT’s Computer Science and Artificial Intelligence Laboratory (CSAIL) derives algorithm to handle lack of training data, making it easier to adopt current machine translation methods.
Facebook Says This Is the Culmination of Years of Work in Machine Translation
The new machine translation model, trained on 2,200 language directions, builds on Facebook’s past research on parallel sentences not aligned with English.
US Coast Guard Moves Ahead With Hyper-Ambitious “Language Translator” RFP
US Department of Homeland Security awards California startup in Phase 1 of RFP for “portable language translator.” Call for tenders still open until February 2021.
TWB, Big Tech, Academia Take on Covid-19 Language Challenge
Collaboration between Amazon, Facebook, Google, Microsoft, etc., and Translators Without Borders aims to fight Covid-19 infodemic through machine translation research.
US Coast Guard Opens RFP to Replace ‘Human Translator’ with ‘Portable Translator’
US Department of Homeland Security launches RFP for “portable language translator” device to replace “on-scene human translator.” Budget: USD 800,000.
The Winning Papers from the World’s Largest Natural Language Processing Conference
The world’s largest NLP conference, EMNLP, announces the winners of the 2019 awards for Best Paper, Best Paper Runner-Up, Best Demo Paper and Best Resource Paper.
Slator 2019 US Healthcare Interpreting Report
Slator’s 2019 report on the US healthcare interpreting market, analysis of the competitive landscape, buyer job titles, major hospital systems, and more actionable insights.
What’s so Massive About Google’s Massively Multilingual Neural Machine Translation?
New research by Google AI explores multilingual NMT on an unprecedented scale. Good for low-resource languages, less so for the rest, results show.
As Neural Machine Translation’s Core Model Seems Settled, Focus Shifts to Products
At SlatorCon London 2019, Systran CEO Jean Senellart outlined the latest in NMT developments, called out some myths from vendors, and pointed out what’s missing from the industry.
EU Awards USD 4.8m in Neural MT Grants for Low-Resource Languages
EU’s CEF grants 5 project proposals for the implementation, data collection, and integration of NMT for low-resource languages, a total of EUR 4.3m in funds.
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