33.725, Summer Schools: Introducing Neural Machine Translation (NMT) to Translators / Online

Thu Feb 24 23:30:45 UTC 2022

LINGUIST List: Vol-33-725. Thu Feb 24 2022. ISSN: 1069 - 4875.

Subject: 33.725, Summer Schools:  Introducing Neural Machine Translation (NMT) to Translators / Online

Moderator: Malgorzata E. Cavar (linguist at linguistlist.org)
Student Moderator: Billy Dickson
Managing Editor: Lauren Perkins
Team: Helen Aristar-Dry, Everett Green, Sarah Goldfinch, Nils Hjortnaes,
      Joshua Sims, Billy Dickson, Amalia Robinson, Matthew Fort
Jobs: jobs at linguistlist.org | Conferences: callconf at linguistlist.org | Pubs: pubs at linguistlist.org

Homepage: http://linguistlist.org

Please support the LL editors and operation with a donation at:
           https://funddrive.linguistlist.org/donate/

Editor for this issue: Sarah Goldfinch <sgoldfinch at linguistlist.org>
================================================================

Date: Thu, 24 Feb 2022 18:30:37
From: Leonardo Zilio [ziliotradutor at gmail.com]
Subject: Introducing Neural Machine Translation (NMT) to Translators / Online

Introducing Neural Machine Translation (NMT) to Translators

Host Institution: 
Website: https://www.surrey.ac.uk/events/20220304-introducing-neural-machine-translation-nmt-translators

Dates: 04-Mar-2022 - 04-Mar-2022
Location: Online, Zoom, United Kingdom

Focus: Neural Machine Translation
Minimum Education Level: No Minimum

Description:
Should translators understand the power of the technology behind Google
Translate and other providers of machine translation? We think so, and that is
why we prepared this webinar as the first step in helping translators make
informed decisions when working with this technology.

The volume and quality of machine translation produced today baffles anyone
who has been working or wants to start working with translation. Neural
machine translation (NMT) is a set of the most advanced machine learning
technologies that has been yielding surprising volumes of high-quality machine
translation output.

NMT uses neural network-based models to learn probabilistic models of
languages, in such a way that they can be used to estimate very likely good
translations of new source sentences. One of the key benefits of these
approaches is to simplify the process of training MT systems. Unlike previous
statistical translation systems, which consisted of many small sub-components
that were tuned separately, NMT attempts to build and train a single, large
neural network which will then be able to read a source sentence and output a
translation for it.

In this webinar, we will explain the use of widely available programming
libraries to create a customised translation engine or model using NMT. The
webinar will consist of a step-by-step demonstration of the different stages
of training a NMT model, with simple explanations of the terms that are used
by researchers that train these systems.

The webinar will include introductory answers to questions like: What is a
neural network? What are word embeddings? What does training and learning
mean? How many stages are there in an NMT training process? What methods are
there to improve the quality of the MT output? Why is the translation stage
called decoding? There will be time for the participants to ask questions, but
they are not expected to perform any hands-on work. As a follow-up to the
webinar, we are preparing a short course with hands-on exercises for
participants to train their own initial models.

Registration: 23-Feb-2022 to 01-Mar-2022

Contact Person: Leonardo Zilio
                Email: cts_inquiries at surrey.ac.uk

Registration Instructions:

------------------------------------------------------------------------------

***************************    LINGUIST List Support    ***************************
 The 2020 Fund Drive is under way! Please visit https://funddrive.linguistlist.org
  to find out how to donate and check how your university, country or discipline
     ranks in the fund drive challenges. Or go directly to the donation site:
                   https://crowdfunding.iu.edu/the-linguist-list

                        Let's make this a short fund drive!
                Please feel free to share the link to our campaign:
                    https://funddrive.linguistlist.org/donate/

----------------------------------------------------------
LINGUIST List: Vol-33-725	
----------------------------------------------------------