Humanist Discussion Group

Humanist Archives: June 17, 2021, 6:32 a.m. Humanist 35.89 - events: machine translation (17 June)

				
              Humanist Discussion Group, Vol. 35, No. 89.
        Department of Digital Humanities, University of Cologne
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        Date: 2021-06-16 11:16:33+00:00
        From: Omniscien Technologies <sales@omniscien.com>
        Subject: Applying New Advances in AI-based Machine Translation to Real World Use Cases

Free Webinar:
Applying New Advances in AI-based Machine Translation to Real World Use Cases  

Thursday 17 June 2021
08:00 PST (UTC -7) San Francisco
11:00 EST (UTC -4) New York
16:00 BST  (UTC +1) London
17:00 CET (UTC +2) France 
22:00 ICT (UTC +7) Thailand

Join Omniscien's Chief Scientist Professor Philipp Koehn, a leading researcher
in the field of AI and MT, along with Dion Wiggins, Omniscien’s CTO, for an hour
of information sharing and insights on what the rest of 2021 and beyond will
likely bring. We will look at trends in Neural Machine Translation, Natural
Language Processing, Artificial Intelligence, Machine Learning, Data Mining,
Text Analytics, and more.

This is a 2-part, 90-minute presentation.

Part 1: Exciting Advances and Breakthroughs in AI and MT.

In the last 3 years, there have been many significant advances in language-
related Artificial Intelligence (AI) and Machine Translation (MT). MT and more
broadly natural language processing have become essential parts of the global
technological leadership race in AI. Research in this area has skyrocketed, and
many ground-breaking achievements continue to be made. We will present a concise
overview of the latest updates and advances in this rapidly advancing field.

Part 2: Putting Advances to Real World Use

This fast-evolving technology field is changing the way people work, play, and
understand data. Language Studio V6.0 ships in July 2021, just weeks from now.
We will look at many of the exciting new features and show how many of the
technological advances discussed in Part 1 are being used in the real world. We
will look at runtime translation features, with a number of great product
feature reveals, and look at real-world examples of custom MT advances that take
engines to as much as 25 BLEU points above Google, Microsoft, and DeepL
offerings.


REPLAYS WILL BE AVAILABLE
[ Register Now: ( https://2ky15.r.ag.d.sendibm3.com/mk/cl/f/LUKsCDRflU
jxMFdhINQqRqlPbsHz5QfiGRNeoprkEBV6MrFviEtj852cPlNbsFv6y3YrZQ6ApBYoNFXldofWDzNBI-
aBRGJIZr3crL03L5QwaIW1al5pjnWBuuMlLJh9WlIT47EKwhDUEZB0hmAKexwEkKvVDSt78gKKC-
bbjqvO4THSVxwG_AEP1YLJJIq3geH797WY8mQ1SQIYpzup2CL6lb864po )      

Professor Philipp Koehn
Chief Scientist,
Omniscien Technologies

Dion Wiggins
CTO, Co-Founder,
Omniscien Technologies    

Did you miss our previous Webinars? 

Anatomy of a Great Custom Machine Translation Engine

Anyone can create a custom MT engine by simply uploading data and training.
However, much like in a kitchen, just throwing ingredients in a pot does not
make a great meal. A good recipe, a skilled chief, and the right tools will give
a much better result. Similarly, a great translation engine that consistently
delivers substantially higher quality translations that generic machine
translation engines such as Google, requires expertise and experience.

With over 14 years of experience creating tens-of-thousands of custom machine
translation engines, the Omniscien team has refined a methodology and set of
tools that provide unmatched translation quality. Many of the tools and
processes are unique to Omniscien and are designed to make it fast and easy to
create your own custom machine translation engines.

This webinar will go through each of the core processes that we follow and the
tools that we use when we build a Professional Guided custom machine translation
engine. They include data cleaning, data gathering, data synthesis, document
alignment, sentence matching, quality measurement, and much more.

You will learn:
When a custom machine translation is needed. How much data is needed for a
custom machine translation engine (spoiler: millions of domain-specific
sentences) and how to create that data when you do not have enough. What tools
are used to gather and process data. How to control writing style and embed
multiple styles and domains into a single machine translation engine. How to
automatically create thousands of in-domain bilingual glossary terms. How to
synthesize millions of bilingual sentences.        [ Watch the Replay Now ]( htt
ps://2ky15.r.ag.d.sendibm3.com/mk/cl/f/r6j5-GKzX3Y39qdJUaSe4OTetv9RgglooiFFBrm2y
gHJSvT0CP9jBChzaS721GzyDmN-CzkCBZWqHg1_vOASvAoRmMDYT-97qURg_3LmMxQWTL16WdtuB9TIY
xBvb-4WDmpkL7jMcOLrLz91msGa09tzlfESkQouqxE00X49jNp_hL-b3thFjdzeXztl20E3FwHE9Nohy
DCFrgQQ8YMV0uS0wtLYpEMddBdH0QR4sdL-0sn2sNap5C7QnxJswLBfGNNi3dCfTwg_5EzgIg )


Omniscien Technologies
www.omniscien.com
sales@omniscien.com



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