Broadening Google Patents

Posted by Jon Orwant, Engineering Manager

Cross-posted with the US Public Policy Blog, the European Public Policy Blog, and Inside Search Blog.

Last year, we launched two improvements to Google Patents: the Prior Art Finder and European Patent Office (EPO) patents. Today we’re happy to announce the addition of documents from four new patent agencies: China, Germany, Canada, and the World Intellectual Property Organization (WIPO). Many of these documents may provide prior art for future patent applications, and we hope their increased discoverability will improve the quality of patents in the U.S. and worldwide.

So if you want to learn about a Chinese dual-drive bicycle, a German valve for inflating bicycle tires, attach a Canadian trailer to your bike, or read the WIPO application for pedalling with one leg, those and millions of other inventions are now available on Google Patents.

Thanks to Google Translate, all patents are available in both their original languages and in English, and you can search across the world’s patents using terms in any of those languages. When there are multiple submission languages, you can move between them with a single click on the tabs at the top of the page, as shown in the screenshot below:

Happy patent searching!

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We are joining the Open edX platform

Posted by Dan Clancy, Director of Research

A year ago, we released Course Builder, an experimental platform for online education at scale. Since then, individuals have created courses on everything from game theory to philanthropy, offered to curious people around the world. Universities and non-profit organizations have used the platform to experiment with MOOCs, while maintaining direct relationships with their participants. Google has published a number of courses including Introduction to Web Accessibility which opens for registration today. This platform is helping to deliver on our goal of making education more accessible through technology, and enabling educators to easily teach at scale on top of cloud platform services.

Today, Google will begin working with edX as a contributor to the open source platform, Open edX. We are taking our learnings from Course Builder and applying them to Open edX to further innovate on an open source MOOC platform. We look forward to contributing to edX’s new site, MOOC.org, a new service for online learning which will allow any academic institution, business and individual to create and host online courses.

Google and edX have a shared mission to broaden access to education, and by working together, we can advance towards our goals much faster. In addition, Google, with its breadth of applicable infrastructure and research capabilities, will continue to make contributions to the online education space, the findings of which will be shared directly to the online education community and the Open edX platform.

We support the development of a diverse education ecosystem, as learning expands in the online world. Part of that means that educational institutions should easily be able to bring their content online and manage their relationships with their students. Our industry is in the early stages of MOOCs, and lots of experimentation is still needed to find the best way to meet the educational needs of the world. An open ecosystem with multiple players encourages rapid experimentation and innovation, and we applaud the work going on in this space today.

We appreciate the community that has grown around the Course Builder open source project. We will continue to maintain Course Builder, but are focusing our development efforts on Open edX, and look forward to seeing edX’s MOOC.org platform develop. In the future, we will provide an upgrade path to Open edX and MOOC.org from Course Builder. We hope that our continued contributions to open source education projects will enable anyone who builds online education products to benefit from our technology, services and scale. For learners, we believe that a more open online education ecosystem will make it easier for anyone to pick up new skills and concepts at any time, anywhere.

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Make Your Websites More Accessible to More Users with Introduction to Web Accessibility

Eve Andersson, Manager, Accessibility Engineering

Cross-posted with Google Developer's Blog

You work hard to build clean, intuitive websites. Traffic is high and still climbing, and your website provides a great user experience for all your users, right? Now close your eyes. Is your website easily navigable? According to the World Health Organization, 285 million people are visually impaired. That’s more than the populations of England, Germany, and Japan combined!

As the web has continued to evolve, websites have become more interactive and complex, and this has led to a reduction in accessibility for some users. Fortunately, there are some simple techniques you can employ to make your websites more accessible to blind and low-vision users and increase your potential audience. Introduction to Web Accessibility is Google’s online course that helps you do just that.



You’ll learn to make easy accessibility updates, starting with your HTML structure, without breaking code or sacrificing a beautiful user experience. You’ll also learn tips and tricks to inspect the accessibility of your websites using Google Chrome extensions. Introduction to Web Accessibility runs with support from Google content experts from September 17th - 30th, and is recommended for developers with basic familiarity with HTML, JavaScript, and CSS.

There’s a lot to learn in the realm of web accessibility, and a lot of work to be done to ensure users aren’t excluded from being able to easily navigate the web. By introducing fundamental tips to improve web usage for users with visual impairments, Introduction to Web Accessibility is a starting point to learn how to build accessibility features into your code. Registration is now open, so sign up today and help push the web toward becoming truly universally accessible.

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A Comparison of Five Google Online Courses

Posted by Julia Wilkowski, Senior Instructional Designer

Google has taught five open online courses in the past year, reaching nearly 400,000 interested students. In this post I will share observations from experiments with a year’s worth of these courses. We were particularly surprised by how the size of our courses evolved during the year; how students responded to a non-linear, problem-based MOOC; and the value that many students got out of the courses, even after the courses ended.

Observation #1: Course size
We have seen varying numbers of registered students in the courses. Our first two courses (Power Searching versions one and two) garnered significant interest with over 100,000 students registering for each course. Our more recent courses have attracted closer to 40,000 students each. It’s likely that this is a result of initial interest in MOOCs starting to decline as well as students realizing that online courses require significant commitment of time and effort. We’d like other MOOC content aggregators to share their results so that we can identify overall MOOC patterns.

*based on surveys sent only to course completers. Other satisfaction scores represent aggregate survey results sent to all registrants.

Observation #2: Completion rates
Comparing these five two-week courses, we notice that most of them illustrate a completion rate (measured by the number of students who meet the course criteria for completion divided by the total number of registrants) of between 11-16%. Advanced Power Searching was an outlier at only 4%. Why? A possible answer can be found by comparing the culminating projects for each course: Power Searching consisted of students completing a multiple choice test; Advanced Power Searching students completed case studies of applying skills to research problems. After grading their work, students also had to solve a final search challenge.

Advanced Power Searching also differed from all of the other courses in the way it presented content and activities. Power Searching offered videos and activities in a highly structured, linear path; Advanced Power Searching presented students with a selection of challenges followed by supporting lessons. We observed a decreasing number of views on each challenge page similar to the pattern in the linear course (see figure 1).

Figure 1. Unique page views for Power Searching and Advanced Power Searching

Students who did complete Advanced Power Searching expressed satisfaction with the course (95% of course completing students would recommend the course to others, compared with 94% of survey respondents from Power Searching). We surmise that the lower completion rate for Advanced Power Searching compared to Power Searching could be a result of the relative difficulty of this course (it assumed significantly more foundational knowledge than Power Searching), the unstructured nature of the course, or a combination of these and other factors.

Even though completion rates seem low when compared with traditional courses, we are excited about the sheer number of students we’ve reached through our courses (over 51,000 earning certificates of completion). If we offered the same content to classrooms of 30 students, it would take over four and a half years of daily classes to teach the same information!

Observation #3: Students have varied goals
We would also like to move the discussion beyond completion rates. We’ve noticed that students register for online courses for many different reasons. In Mapping with Google, we asked students to select a goal during registration. We discovered that

• 52% of registrants intended to complete the course
• 48% merely wanted to learn a few new things about Google’s mapping tools

Post-course surveys revealed that

• 78% of students achieved the goal they defined at registration
• 89% of students learned new features of Google Maps
• 76% reported learning new features of Google Earth

Though a much smaller percentage of students completed course requirements, these statistics show that many of the students attained their learning goals.

Observation #4: Continued interest in post-course access
After each course ended, we kept many of the course materials (videos, activities) available. Though we removed access to the forums, final projects/assessments, and teaching assistants, we have seen significant interest in the content as measured by Google and YouTube Analytics. The Power Searching course pages have generated nearly three million page views after the courses finished; viewers have watched over 160,000 hours (18 years!) of course videos. In the two months since Mapping with Google finished, we have seen over 70,000 unique visitors to the course pages.

In all of our courses, we saw a high number of students interested in learning online: 96% of Power Searching participants agreed or strongly agreed that they would take a course in a similar format. We have succeeded in teaching tens of thousands of students to be more savvy users of Google tools. Future posts will take an in-depth look at our experiments with self-graded assessments, community elements that enhance learning, and design elements that influence student success.

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Google Research Awards: Summer 2013

Posted by Maggie Johnson, Director of Education & University Relations

Another round of the Google Research Awards is complete. This is our biannual open call for proposals on computer science-related topics including machine learning and structured data, policy, human computer interaction, and geo/maps. Our grants cover tuition for a graduate student and provide both faculty and students the opportunity to work directly with Google scientists and engineers.

This round, we received 550 proposals from 50 countries. After expert reviews and committee discussions, we decided to fund 105 projects. The subject areas that received the highest level of support were human-computer interaction, systems and machine learning. In addition, 19% of the funding was awarded to universities outside the U.S.

We noticed some new areas emerging in this round of proposals. In particular, an increase of interest in neural networks, accessibility-related projects, and some innovative ideas in robotics. One project features the use of Android-based multi-robot systems which are significantly more complex than single robot systems. Faculty researchers are looking to explore novel uses of Google Glass such as an indoor navigation system for blind users, and how Glass can facilitate social interactions.

Congratulations to the well-deserving recipients of this round’s awards. If you are interested in applying for the next round (deadline is October 15), please visit our website for more information.

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Computer Science Teaching Fellows Starting Up in Charleston, SC

Posted by Cameron Fadjo, Program Lead, Computer Science Teaching Fellows

Google recently started up an exciting new program to ignite interest in computer science (CS) for K12 kids. Located in our South Carolina data center, the Computer Science Teaching Fellows is a two-year post graduate fellowship for new STEM teachers and CS graduates. The goal is to bring computer science and computational thinking to all children, especially underrepresented minorities and girls, and close the gap between the ever-increasing demand in CS and the inadequate supply. We hope to learn what really works and scale those best practices regionally and then nationally.

The supply of CS majors in the pipeline has been a concern for many years. In 2007, the Computer Science education community was alarmed by the lack of CS majors and enrollments in US colleges and universities.

Source: 2009-2010 CRA Taulbee Survey (http://www.cra.org/resources/)

This prompted the development of several programs and activities to start raising awareness about the demand and opportunities for computer scientists, and to spark the interest of K12 students in CS. For example, the NSF funded curriculum and professional development around the new CS Principles Advanced Placement course. The CSTA published standards for K12 CS and a report on the limited extent to which schools, districts and states provide CS instruction to their students. CS advocacy groups, Computing in the Core and Code.org have played an instrumental role in adding provisions to the reauthorization of the Elementary and Secondary School Act to support CS education. More generally, we have seen innovations in online learning with MOOCs, machine learning to provide personalized learning experiences, and platforms like Khan Academy that allow flipped classrooms.

All of these activities represent a convergence in the CS education space, where existing programs are ready for scale, and technological advancements can support that scale in innovative ways. Our Teaching Fellows will be testing after school programs, classroom curriculum and online CS programs to determine what works and why. They’ll start in the local Charleston area and then spread the best programs and curriculum to South Carolina, Georgia, North Carolina (where we also have large data centers). They are currently preparing programs for the fall semester.

We are very excited about the convergence we are seeing in CS education and the potential to bring many more kids into a field that offers not only great career opportunities but also a shot at really making a difference in the world. We’ll keep you posted on the progress of our Teaching Fellows.

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Under the hood of Croatian, Filipino, Ukrainian, and Vietnamese in Google Voice Search

Posted by Eugene Weinstein and Pedro Moreno, Google Speech Team

Although we’ve been working on speech recognition for several years, every new language requires our engineers and scientists to tackle unique challenges. Our most recent additions - Croatian, Filipino, Ukrainian, and Vietnamese - required creative solutions to reflect how each language is used across devices and in everyday conversations.

For example, since Vietnamese is a tonal language, we had to explore how to take tones into consideration. One simple technique is to model the tone and vowel combinations (tonemes) directly in our lexicons. This, however, has the side effect of a larger phonetic inventory. As a result we had to come up with special algorithms to handle the increased complexity. Additionally, Vietnamese is a heavily diacritized language, with tone markers on a majority of syllables. Since Google Search is very good at returning valid results even when diacritics are omitted, our Vietnamese users frequently omit the diacritics when typing their queries. This creates difficulties for the speech recognizer, which selects its vocabulary from typed queries. For this purpose, we created a special diacritic restoration algorithm which enables us to present properly formatted text to our users in the majority of cases.

Filipino also presented interesting challenges. Much like in other multilingual societies such as Hong Kong, India, South Africa, etc., Filipinos often mix several languages in their daily life. This is called code switching. Code switching complicates the design of pronunciation, language, and acoustic models. Speech scientists are effectively faced with a dilemma: should we build one system per language, or should we combine all languages into one?

In such situations we prefer to model the reality of daily language use in our speech recognizer design. If users mix several languages, our recognizers should do their best in modeling this behavior. Hence our Filipino voice search system, while mainly focused on the Filipino language, also allows users to mix in English terms.

The algorithms we’re using to model how speech sounds are spoken in each language make use of our distributed large-scale neural network learning infrastructure (yes, the same one that spontaneously discovered cats on YouTube!). By partitioning the gigantic parameter set of the model, and by evaluating each partition on a separate computation server, we’re able to achieve unprecedented levels of parallelism in training acoustic models.

The more people use Google speech recognition products, the more accurate the technology becomes. These new neural network technologies will help us bring you lots of improvements and many more languages in the future.

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