Seminaire: Clean Data Machine Translation, Asia Online Webinars, November 2011

Fri Nov 18 21:58:39 UTC 2011

Date: Thu, 17 Nov 2011 09:36:20 +0100
From: Asia Online <info at asiaonline.net>
Message-ID: <6e485356011537c6f8965cb92e8b80a7 at smtp.ymlp36.net>

Free Webinars
November 2011

Asia Online webinars over the last several months have been very popular
and many people have asked us when we will repeat the topics.  We had
many more requests to attend two of our webinars than any other webinars
we have ever delivered before. So, this month Asia Online will be
presenting the following 2 webinars again:

Clean Data Machine Translation: Delivering near-human quality
translations ( https://www1.gotomeeting.com/register/530217161 )

MT & ROI – Scoping, Defining, Measuring and Selecting Suitable Projects
( https://www1.gotomeeting.com/register/214946064 )

Did you attend one of our previous webinars?
Download the slides & videos.

Clean Data Machine Translation: Delivering near-human quality
translations

Presenters :

Dion Wiggins

Chief Executive Officer

dion.wiggins at asiaonline.net

Kirti Vashee

VP Enterprise Translation Sales

kirti.vashee at asiaonline.net

12:00/12AM
Boston, New York

09:00/9AM
Los Angeles, San Diego, San Francisco, Seattle

17:00/5PM
London, Dublin

18:00/6PM
Amsterdam, Prague

19:00/7PM
Bucharest

There are many approaches to Machine Translation (MT). Rules Based
Machine Translation(RBMT) is rapidly being superseded by Statistical
Machine Translation (SMT) approaches. However there are also several
approaches to SMT.

Asia Online takes a unique “Clean Data” approach to SMT that focuses on
the quality of data rather than the quantity. Using the Clean Data
approach, it is possible to build a near-human quality customized
translation engine. This presentation will explore the process of
creating and improving near-human quality custom translation engines
using Language Studio’s clean data tools and processes.

* What is Clean Data SMT and how is it different to other SMT
  approaches.
* Why does clean MT data deliver greater quality?
* Clean Data requirements and preparation.
* Benefits of the Clean Data SMT approach over the Dirty Data MT
  approach.
* The impact of Post Editing on Clean Data SMT.
* Rapid quality improvement – Clean Data analysis.
* Case Study: The impact of Dirty Data examples using multiple data
  sources from TDA.

MT & ROI – Scoping, Defining, Measuring and Selecting Suitable Projects

Presenters :

Dion Wiggins

Chief Executive Officer

dion.wiggins at asiaonline.net

Kirti Vashee

VP Enterprise Translation Sales

kirti.vashee at asiaonline.net

12:00/12AM
Boston, New York

09:00/9AM
Los Angeles, San Diego, San Francisco, Seattle

17:00/5PM
London, Dublin

18:00/6PM
Amsterdam, Prague

19:00/7PM
Bucharest

This webinar will explore the types of project that are suitable for
Machine Translation(MT), and how they can be combined with human effort
to achieve successful results in less time and with higher margins. Not
every project is suitable for MT, and we will explore which projects are
best suited and most likely to succeed, as well as the related Business
Models that can help promote such success.

Return On Investment (ROI) is not well understood for MT projects.
Although it is well known that customization of MT results in
translations that contain fewer errors and therefore require less post
editing, it is not well understood how quickly ROI can be achieved and
what the costs of using MT are on an on-going basis.

We will explore the costs and ROI of various MT projects and how quickly
the costs of customization can be recovered and cost savings
realized. It will also explore the time savings on various projects and
how they should be measured. Finally, we will review several real world
Language Studio™ implementations and the ROI achieved. This includes a
large multimillion word project that delivered 60% cost savings and 77%
time savings and a smaller project with just 25,000 words that
significantly increased profit margins and reduced time to deliver.

* Explore real world ROI examples
* Determining what kinds of projects are best suited to MT
* Determining the best Business Model for MT use
* How long and how many words will it require in order to get ROI
* Best practice

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