We develop innovative techniques & algorithms in Natural Language Understanding, focusing on improving Google services and user experiences.
Natural Language Understanding
Our team comprises multiple research groups working on a range of Natural Language Understanding (NLU) projects. We collaborate closely with teams across Google, leveraging efficient algorithms, neural networks, and graphical and probabilistic models to help guide product development and direction. In doing so, the Google NLU team enables natural and assistive communication with users, finds answers to user questions, analyzes app store reviews for developers, and more.
Our researchers are experts in traditional natural language processing and machine learning, and combine methodological research with applied science. All of our NLU engineers are equally involved in long-term research efforts and driving immediate applications of our technology. Our systems also benefit greatly from Google linguists, who provide valuable labelled data and assist in enabling internationalization.
Recent research interests of the Google NLU team include syntax, discourse, conversation, multilingual modeling, sentiment analysis, question answering, summarization, and generally building better learners using labeled and unlabeled data, state-of-the-art modeling, and indirect supervision.
Swabha Swayamdipta, Ankur P. Parikh, Tom Kwiatkowski. Accepted to ICLR 2018.
Proceedings of the 2017 Conference on Empirical Methods in Natural Language Processing, Association for Computational Linguistics, Copenhagen, Denmark, 2879–2885
Association for Computational Linguistics (2016)
Sixth International Conference on Learning Representations (2018)
SLING is an experimental system for parsing natural language text directly into a representation of its meaning as a semantic frame graph.
Based on our examination of the use of Smart Reply in Inbox and our ideas about how humans learn and use language, we have created a new version of Smart Reply for Gmail.
This upgrade incorporates nearly a year’s worth of our research on multilingual language understanding, and is available to anyone interested in building systems for processing and understanding text.
We recently provided many exciting improvements to Gboard for Android, working towards our vision of creating an intelligent mechanism that enables faster input while offering suggestions and correcting mistakes, in any language you choose.
Some of our people
Most of Google’s users interact with us through language. Working on the NLU team means you get to play a critical role in helping our systems understand what users want.
The NLU team provides opportunities to work on ambitious research projects and to share successes along the way with products and the academic community.