Machine Translation Master Class

The Machine Translation Master Class provides an independent perspective on MT implementation and its impact on other aspects of existing localization processes for both vendors and clients. It focuses on the continuous adaptation to the change that MT implementation brings about.

Machine Translation Master Class
Machine Translation Master Class

Master Class Details

Dates
April 22, 2024 - May 13, 2024

Format
4 classes, 2 hour each

Instructor:
Dr. Peng Wang

Fee
$750

Language
English

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Cancellation Policy

Machine Translation Master Class

Managing the Dynamics of NMT Implementation and Exploring New Alternatives in AGI

Session #1: Monday, April 22 – 6pm – 8pm CEST / 12pm – 2pm EDT
Session #2: Monday, April 29 – 6pm – 8pm CEST / 12pm – 2pm EDT
Session #3: Monday, May 6 – 6pm – 8pm CEST / 12pm – 2pm EDT
Session #4: Monday, May 13 – 6pm – 8pm CEST / 12pm – 2pm EDT

 

The rise of Neural Machine Translation lies not only in the success of the engine itself, but also in its revolutionary power within the whole human-machine interaction system. When NMT works optimally, it makes great strides in simulating human intelligence and thus has the power to shake up the whole industry by being applied to many more scenarios that used to be human-dominant. But NMT is driven by machine learning and is less constrained by humans. It contains risks to the accelerated localization process because of dynamic instability that the power of AI can bring about.
The new edition of MT Master Class from the Localization Institute takes a closer look under the hood of NMT technology as well as MT-related NLP tasks. Having worked in both academia and industry, Dr. Peng Wang recognizes key insights and trends spanning both worlds. This course helps you further explore NMT use cases, pioneers risk control measures and highlights the value added by humans within and beyond the localization process.

The Localization Institute is pleased to offer an instructor-led online master class on Machine Translation with Dr. Wang. In four 2-hour sessions, she shares her independent perspective on MT with both vendors and clients.

This Master Class is for:

  • Project Managers tasked with implementing an MT solution
  • Vendors who want to leverage MT to meet their clients’ needs
  • Buyers who want to implement MT
  • Decision-makers who have to understand MT but don’t want to become technical experts
  • IT professionals involved in MT implementation
  • Content Managers responsible for global content
Please note: recording or republishing any of the class sessions is prohibited. We do this in order for students to be able to speak and share experiences freely with the instructor and their fellow classmates in a comfortable and safe environment without fear that something they say might later be made public.

 

Curriculum

Weekly Modules

Session 1 – Orientation and Introduction: A Holistic Approach to MT

Monday, April 22 – 6pm – 8pm CEST / 12pm – 2pm EDT

from CAT to MT – the evolution of language technology

Session 2 – Deconstructing the Skills: The Dynamics of NMT implementation

Monday, April 29 – 6pm – 8pm CEST / 12pm – 2pm EDT

a look under the hood at the most relevant parts

Session 3 – Imagining The Opposite: Anticipate and Identify The Potential Risks

Monday, May 6 – 6pm – 8pm CEST / 12pm – 2pm EDT

automatic quality evaluation, estimation and editing strategies

Session 4 – Integrating AI into the Localization Ecosystem: Managing The Risks

Monday, May 13 – 6pm – 8pm CEST / 12pm – 2pm EDT

mind and machine, the key to AI integration

Each session consists of one 45 minute class, a 10 minute break, and then another 45 minutes of class followed by 20 minutes of Q&A.

To allow for a high level of interactivity, the class is limited to 20 attendees. To protect privacy and confidentiality, sessions will not be recorded.

10% discount for 3 or more students from the same company – please contact jill@localizationinstitute.com for more information.

This course will provide you with:

  • An understanding of the most relevant cutting-edge translation technologies related to MT implementation
  • A perception of how these technologies are related to human cognition
  • Knowledge and appreciation of the diversity of the world and how it is related to MT

All students who complete the Machine Translation Master Class will receive an Industry Certificate of Completion from The Localization Institute, Inc.

Machine Translation Master Class

About Your Instructor

Dr. Peng Wang

Dr. Peng Wang has taught, researched and practiced translation and localization on three continents. She is the convener for EDUinLOC, the chair of the automation/AI track for LocWorld conferences and a part-time professor at the University of Ottawa. Previously, she was the CAT Tools Coordinator at the University of Maryland.

Dr. Wang has rich research experience on NLP AI, having worked as a linguistic researcher at the Corpus Research Lab at Northern Arizona University, a domain expert for data mining projects at the University of Maryland and an honorary research fellow on automatic discourse analysis tools at the University of Liverpool. Her current research and practice focus on human learning vs. machine learning, machine translation, terminology and multilingual corpus analysis.

Dr. Wang has published about 30 articles and two books. She is an expert in approaching technology in the context of culture and humanities. She embraces linguistic and cultural diversity in her classrooms, with students aged from 18 to over 70, in over 10 language combinations, coming from UAE, China, Italy, Spain, Germany, Morocco, Colombia, Mexico, and Haiti, to name just a few.

Testimonials

Dr. Peng Wang’s Latest Book

Machine Learning in Translation

On March 22, 2023, Dr. Wang and co-author David B. Sawyer will publish Machine Learning in Translation. For more information about the book and to reserve your copy, please click here to visit the publisher’s website.

Machine Translation Master Class

Overview

Preview Webinar Recording

Interview with Dr. Peng Wang