IMUG Past Events Archive: 2024

 

 

 

2024 Events:

 

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2024 Events Archive

June 19, 2024, 6:30-8:30 PM
(Attendee chat/networking 6:30-7:00 PM)

Keyboard Design for Indigenous Languages
Hosted by Google in Mountain View, CA

Video: https://youtu.be/_lQmoYB0dWk new page

Screen shotYou take your seat in a crowded room. Suddenly, phones beep and everyone begins reading and typing urgently.

But not you. You cannot read the messages they are feverishly responding to.

Are they alerts? Important safety instructions? Are they texting loved ones? Maybe it is exciting news they are relaying.

Your phone works fine. However, your language is not supported. No one can produce text in your language and send you critical information. And you cannot send questions or share information on any of the numerous text based apps available to those around you.

Using voice is slow and mostly person to person, so not practical in urgent large scale situations.

The Keyboard Creation project of Translation Commons is building virtual keyboards for communities that want access to digital applications in their native language.

In this talk, you will learn about the challenges to creating these keyboards, how we solve them, and the impact the keyboards have had for many communities. These activities are performed by Translation Commons volunteers for free. You will learn how you can nominate projects and even learn how to create keyboards yourself!

Join this discussion to learn about this important step in language digitization and bringing digitally disadvantaged languages to a connected world.

Speakers:

Craig Cornelius is a senior software engineer on the International Engineering team at Google, Inc., joining in 2007. He works on language support across Google, including Android, Search, GMail, and Google Translate. He contributes to the open source Unicode Standard and the work of the Unicode Technical Committees.

Craig’s indigenous language experience began with Cherokee, and he continues to collaborate on projects with the Cherokee Nation and other communities. He serves on the governing boards of the Endangered Languages Project (www.endangeredlanguages.com), Translation Commons (translationcommons.org), and Endangered Alphabets (endangeredalphabets.com). He is a contributing author to “Zero To Digital: A Guide to Bring Your Language Online” with Translation Commons. IMUG presentations include Bringing the Internet to Myanmar in 2017.

He has enjoyed a variety of academic and industry positions, from teaching to academic research and medical imaging. Craig holds a B.A. in chemistry and mathematics from Luther College, and both a Ph.D. in Chemistry and an M.S. in Computer Science from Stanford University.”

Tex Texin is an industry thought leader and consultant specializing in software globalization services.

Tex, and his consulting company XenCraft, helped numerous companies create successful global products and guided companies in taking business to new regional markets.

Tex has contributed to several internationalization standards and open source software and has advised several non-profits. He is an advisor to Translation Commons where he is architecting their Language Digitization Initiative, bringing the languages of Indigenous communities to digital systems. Most recently, Tex has been developing keyboards and related standards for Indigenous languages.

Tex is a popular speaker at conferences around the world. Tex is the owner/author of the popular instructional I18nGuy.com site.

Hosts:

Many thanks to Craig Cornelius and Google for hosting this talk!

 

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March 27, 2024, 6:30-8:30 PM
(Attendee chat/networking 6:30-7:00 PM)

The Evolution of Translation Efficiency
Hosted by Adobe in San Jose, CA

Video: https://youtu.be/ZISYtTVoa_Y new page

Levels of efficiency for human-quality translation workflows

Screen shotWhat's the next level of translation efficiency? Why is post-editing machine translation not that much faster, and what is? What are the prerequisites for using more AI successfully? And what about quality?

We'll walk through the levels of efficiency for human-quality translation workflows, from fully manual, to the "hybrid" workflows used to translate tens or hundreds of millions of words, whether inside ecom platforms and enterprise L10n buyer teams, like Microsoft, Citrix and VMWare, or LSPs with tech startup DNA, like Unbabel.

We'll answer practical questions about savings, maintaining quality, adoption, prerequisites, availability in translation management systems (TMSes) and costs.

“The future is already here. It's just not evenly distributed.”

Starting in 2013, leading players researched and launched AI beyond MT - like adaptive translation, quality prediction or automatic post-editing.

But for L10n teams, getting AI beyond MT wasn't in reach without in-house machine learning research team, and wasn't accessible in TMSes anyway.

So by 2020, much of the industry - even L10n teams inside Bay Area tech companies - was still stuck post-editing generic machine translation, or not even post-editing at all.

Now that has changed, thanks to providers of AI for adaptive translation and quality prediction - integrated by the top TMSes - as well as tools like ChatGPT, that let anybody play with an LLM for many more tasks.

About the speaker:

Adam Bittlingmayer is the CEO and co-founder of ModelFront, the leading provider of machine translation quality prediction.

To translate their content more efficiently - at the same human quality - high-volume translation buyers use segment-level quality scores to control which segments get sent to human editing, and which don't - because they won't be edited anyway.

Adam previously worked at Google Translate as a software engineer, as well as on products like Android Market (Google Play) and Adobe Creative Suite.

He also founded the non-profit Machine Translate foundation to make machine translation more accessible to more people, with open information and community. machinetranslate.org now covers 75 APIs, 251 TMS integrations and 225 languages.

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