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Oct 17, 2019 Video Architecture Search
Posted by Michael S. Ryoo, Research Scientist and AJ Piergiovanni, Student Researcher, Robotics at Google Video understanding is a challenging problem. Because a video contains spatio-temporal data, its feature representation is required to abstract both appearance and motion information. This is not only essential for automated understanding of the semantic content of videos, such as web-video classification or sport activity recognition, but is also crucial for robot perception and learning.
Oct 11, 2019 Exploring Massively Multilingual, Massive Neural Machine Translation
Posted by Ankur Bapna, Software Engineer and Orhan Firat, Research Scientist, Google Research “... perhaps the way [of translation] is to descend, from each language, down to the common base of human communication — the real but as yet undiscovered universal language — and then re-emerge by whatever particular route is convenient.” — Warren Weaver , 1949 Over the last few years there has been enormous progress in the quality of machine ...
Oct 10, 2019 ROBEL: Robotics Benchmarks for Learning with Low-Cost Robots
Posted by Michael Ahn, Software Engineer and Vikash Kumar, Research Scientist, Robotics at Google Learning-based methods for solving robotic control problems have recently seen significant momentum, driven by the widening availability of simulated benchmarks (like dm_control or OpenAI-Gym ) and advancements in flexible and scalable reinforcement learning techniques ( DDPG , QT-Opt , or Soft Actor-Critic ).
Oct 03, 2019 Improving Quantum Computation with Classical Machine Learning
Posted by Murphy Yuezhen Niu and Sergio Boixo, Research Scientists One of the primary challenges for the realization of near-term quantum computers has to do with their most basic constituent: the qubit . Qubits can interact with anything in close proximity that carries energy close to their own—stray photons (i.e., unwanted electromagnetic fields), phonons (mechanical oscillations of the quantum device), or quantum defects (irregularities in the substrate of the chip formed during ...
Oct 02, 2019 Releasing PAWS and PAWS-X: Two New Datasets to Improve Natural Language Understanding Models
Posted by Yuan Zhang, Research Scientist and Yinfei Yang, Software Engineer, Google Research Word order and syntactic structure have a large impact on sentence meaning — even small perturbations in word order can completely change interpretation. For example, consider the following related sentences: Flights from New York to Florida.
Sep 30, 2019 Large-Scale Multilingual Speech Recognition with a Streaming End-to-End Model
Posted by Arindrima Datta and Anjuli Kannan, Software Engineers, Google Research Google's mission is not just to organize the world's information but to make it universally accessible, which means ensuring that our products work in as many of the world's languages as possible. When it comes to understanding human speech, which is a core capability of the Google Assistant, extending to more languages poses a challenge: high-quality automatic speech recognition (ASR) systems ...
Sep 25, 2019 An Inside Look at Flood Forecasting
Sella Nevo, Senior Software Engineer, Google Research, Tel Aviv Several years ago, we identified flood forecasts as a unique opportunity to improve people’s lives, and began looking into how Google’s infrastructure and machine learning expertise can help in this field. Last year, we started our flood forecasting pilot in the Patna region, and since then we have expanded our flood forecasting coverage , as part of our larger AI for Social Good ...
Sep 24, 2019 Contributing Data to Deepfake Detection Research
Posted by Nick Dufour, Google Research and Andrew Gully, Jigsaw Deep learning has given rise to technologies that would have been thought impossible only a handful of years ago. Modern generative models are one example of these, capable of synthesizing hyperrealistic images, speech, music, and even video.
Sep 23, 2019 Assessing the Quality of Long-Form Synthesized Speech
Posted by Tom Kenter, Google Research, London Automatically generated speech is everywhere, from directions being read out aloud while you are driving, to virtual assistants on your phone or smart speaker devices at home. While much research is being done to try to make synthesized speech sound as natural as possible—such as generating speech for low-resource languages and creating human-like speech with Tacotron 2 —how does one evaluate the generated speech? The ...
Sep 18, 2019 Project Ihmehimmeli: Temporal Coding in Spiking Neural Networks
Posted by Iulia-Maria Comșa and Krzysztof Potempa, Research Engineers, Google Research, Zürich The discoveries being made regularly in neuroscience are an ongoing source of inspiration for creating more efficient artificial neural networks that process information in the same way as biological organisms. These networks have recently achieved resounding success in domains ranging from playing board and video games to fine-grained understanding of video .
Sep 13, 2019 Using Deep Learning to Inform Differential Diagnoses of Skin Diseases
Posted by Yuan Liu, PhD, Software Engineer and Peggy Bui, MD, Technical Program Manager, Google Health An estimated 1.9 billion people worldwide suffer from a skin condition at any given time, and due to a shortage of dermatologists, many cases are seen by general practitioners instead.
Sep 11, 2019 Learning Cross-Modal Temporal Representations from Unlabeled Videos
Posted by Chen Sun and Cordelia Schmid, Research Scientists, Google Research While people can easily recognize what activities are taking place in videos and anticipate what events may happen next, it is much more difficult for machines. Yet, increasingly, it is important for machines to understand the contents and dynamics of videos for applications, such as temporal localization , action detection and navigation for self-driving cars .
Sep 10, 2019 Recursive Sketches for Modular Deep Learning
Posted by Badih Ghazi and Joshua R. Wang, Research Scientists, Google Research Much of classical machine learning (ML) focuses on utilizing available data to make more accurate predictions. More recently, researchers have considered other important objectives, such as how to design algorithms to be small , efficient , and robust .
Sep 10, 2019 Joint Speech Recognition and Speaker Diarization via Sequence Transduction
Posted by Laurent El Shafey, Software Engineer and Izhak Shafran, Research Scientist, Google Health Being able to recognize “who said what,” or speaker diarization, is a critical step in understanding audio of human dialog through automated means. For instance, in a medical conversation between doctors and patients, “Yes” uttered by a patient in response to “Have you been taking your heart medications regularly?” has a substantially different implication than a rhetorical “Yes?” ...
Sep 10, 2019 Announcing Two New Natural Language Dialog Datasets
Posted by Bill Byrne and Filip Radlinski, Research Scientists, Google Research Today’s digital assistants are expected to complete tasks and return personalized results across many subjects, such as movie listings, restaurant reservations and travel plans. However, despite tremendous progress in recent years, they have not yet reached human-level understanding.
Sep 09, 2019 Announcement of the 2019 Fellowship Awardees and Highlights from the Google PhD Fellowship Summit
Posted by Susie Kim, Program Manager, University Relations In 2009, Google created the PhD Fellowship Program to recognize and support outstanding graduate students who are doing exceptional research in Computer Science and related fields who seek to influence the future of technology. Now in its eleventh year, these Fellowships have helped support 450 graduate students globally in North America and Europe, Australia, Asia, Africa and India.
Sep 04, 2019 Giving Lens New Reading Capabilities in Google Go
Posted by Rajan Patel, Director, Augmented Reality Around the world, millions of people are coming online for the first time, and many of them are among the 800 million adults worldwide who are unable to read or write, or those who are migrating to towns and cities where they are not able to speak the predominant language.
Sep 03, 2019 On-Device, Real-Time Hand Tracking with MediaPipe
Posted by Valentin Bazarevsky and Fan Zhang, Research Engineers, Google Research The ability to perceive the shape and motion of hands can be a vital component in improving the user experience across a variety of technological domains and platforms. For example, it can form the basis for sign language understanding and hand gesture control, and can also enable the overlay of digital content and information on top of the physical world in ...
Aug 29, 2019 Exploring Weight Agnostic Neural Networks
Posted by Adam Gaier, Student Researcher and David Ha, Staff Research Scientist, Google Research, Tokyo When training a neural network to accomplish a given task, be it image classification or reinforcement learning , one typically refines a set of weights associated with each connection within the network.
Aug 26, 2019 Google at ACL 2019
Andrew Helton, Editor, Google Research Communications This week, Florence, Italy hosts the 2019 Annual Meeting of the Association for Computational Linguistics (ACL 2019), the premier conference in the field of natural language understanding, covering a broad spectrum of research areas that are concerned with computational approaches to natural language.