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Defining the technology of today and tomorrow.

Philosophy

We strive to create an environment conducive to many different types of research across many different time scales and levels of risk.
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Our researchers drive advancements in computer science through both fundamental and applied research.
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Foundational ML & Algorithms

Algorithms & Theory

Data Management

Data Mining & Modeling

Information Retrieval & the Web

Machine Intelligence

Machine Perception

Machine Translation

Natural Language Processing

Speech Processing

Algorithms & Theory

Data Management

Data Mining & Modeling

Information Retrieval & the Web

Machine Intelligence

Machine Perception

Machine Translation

Natural Language Processing

Speech Processing

Computing Systems & Quantum AI

Distributed Systems & Parallel Computing

Hardware & Architecture

Mobile Systems

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Robotics

Security, Privacy, & Abuse Prevention

Software Engineering

Software Systems

Distributed Systems & Parallel Computing

Hardware & Architecture

Mobile Systems

Networking

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Robotics

Security, Privacy, & Abuse Prevention

Software Engineering

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Climate & Sustainability

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Human-Computer Interaction and Visualization

Climate & Sustainability

Economics & Electronic Commerce

Education Innovation

General Science

Health & Bioscience

Human-Computer Interaction and Visualization
Projects

We regularly open-source projects with the broader research community and apply our developments to Google products.
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Publishing our work allows us to share ideas and work collaboratively to advance the field of computer science.
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Resources

We make products, tools, and datasets available to everyone with the goal of building a more collaborative ecosystem.
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Shaping the future, together.
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Supporting the next generation of researchers through a wide range of programming.
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Participating in the academic research community through meaningful engagement with university faculty.
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Connecting with the broader research community through events is essential for creating progress in every aspect of our work.
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Blog

Leif Johnson

Leif Johnson

Research Areas

Authored Publications

Google

A more general method for pronunciation learning

Antoine Bruguier

Dan Gnanapragasam

Francoise Beaufays

Kanishka Rao

Leif Johnson

Interspeech 2017 (2017)

A Comparison of Sequence-to-Sequence Models for Speech Recognition

Rohit Prabhavalkar

Kanishka Rao

Tara Sainath

Bo Li

Leif Johnson

Navdeep Jaitly

Interspeech 2017, ISCA (2017)

Language Modeling for Automatic Speech Recognition Meets the Web: Google Search by Voice

Ciprian Chelba

Johan Schalkwyk

Boulos Harb

Carolina Parada

Cyril Allauzen

Leif Johnson

Michael Riley

Peng Xu

Preethi Jyothi

Thorsten Brants

Vida Ha

Will Neveitt

University of Toronto (2012)

Large-scale Discriminative Language Model Reranking for Voice Search

Preethi Jyothi

Leif Johnson

Ciprian Chelba

Brian Strope

Proceedings of the NAACL-HLT 2012 Workshop: Will We Ever Really Replace the N-gram Model? On the Future of Language Modeling for HLT, Association for Computational Linguistics, pp. 41-49

Distributed Discriminative Language Models for Google Voice Search

Preethi Jyothi

Leif Johnson

Ciprian Chelba

Brian Strope

Proceedings of ICASSP 2012, IEEE, pp. 5017-5021

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