Natural Language Processing & Speech

Breaking down language barriers

We want to break down language barriers across the world for everyone to understand and communicate with anyone—no matter what language you speak.

Our natural language processing and speech researchers focus on the interaction between people and computers using human languages, both in diverse written and spoken forms, to remove the barrier of language from the ability to communicate. The challenges are immense, from the billions of users on Facebook across the 6,000 languages in the world—some even without a writing system, to the informal tone, slang and typos people use on Facebook. Our researchers work on the complex problems that span deep learning/neural networks, natural language processing, language identification, text normalization, word sense disambiguation, and machine learning, to break down the problems, and build and deploy robust language translation solutions.

“Connecting the world, regardless of where you live or what language you speak, is our grand challenge. Our teams of researchers are giving people the ability to do just that with innovate new solutions that break down language barriers and make connecting with anyone, anywhere possible.” Benoit Dumoulin, Engineering Manager

Latest Publications

All Publications

Weak-Attention Suppression For Transformer Based Speech Recognition

Yangyang Shi, Yongqiang Wang, Chunyang Wu, Christian Fuegen, Frank Zhang, Duc Le, Ching-Feng Yeh, Michael L. Seltzer

Interspeech - October 26, 2020

Lemotif: An Affective Visual Journal Using Deep Neural Networks

X. Alice Li, Devi Parikh

ICCC - September 7, 2020

Unsupervised Quality Estimation for Neural Machine Translation

Marina Fomicheva, Shuo Sun, Lisa Yankovskaya, Frédéric Blain, Francisco (Paco) Guzman, Mark Fishel, Nikolaos Aletras, Vishrav Chaudhary, Lucia Specia

TACL - August 31, 2020

Information Extraction of Clinical Trial Eligibility Criteria

Yitong Tseo, M. I. Salkola, Ahmed Mohamed, Anuj Kumar, Freddy Abnousi

KDD - August 24, 2020

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