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Philipp Koehn (Part 1) - How Neural Networks Have Transformed Machine Translation

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Manage episode 297999658 series 2954151
Content provided by Damien Deighan and Philipp Diesinger, Damien Deighan, and Philipp Diesinger. All podcast content including episodes, graphics, and podcast descriptions are uploaded and provided directly by Damien Deighan and Philipp Diesinger, Damien Deighan, and Philipp Diesinger or their podcast platform partner. If you believe someone is using your copyrighted work without your permission, you can follow the process outlined here https://player.fm/legal.

Professor Philipp Koehn of Johns Hopkins University discusses the evolution of machine translation and the fundamentals for using Neural Networks to deliver Machine translation.

Episode Summary:

  • Philipp Koehn Bio
  • What is Machine Translation?
  • Adequacy & Fluency
  • How to Quantify the performance of Machine Translation models
  • The Transition from Statistical approaches to using Neural Networks for translation
  • Validating Outputs of models
  • What can go wrong with Machine Translation?

Resources:

Philipp Koehn latest book - Neural Machine Translation - Amazon link:

https://www.amazon.com/Neural-Machine-Translation-Philipp-Koehn/dp/1108497322

  continue reading

24 episodes

Artwork
iconShare
 
Manage episode 297999658 series 2954151
Content provided by Damien Deighan and Philipp Diesinger, Damien Deighan, and Philipp Diesinger. All podcast content including episodes, graphics, and podcast descriptions are uploaded and provided directly by Damien Deighan and Philipp Diesinger, Damien Deighan, and Philipp Diesinger or their podcast platform partner. If you believe someone is using your copyrighted work without your permission, you can follow the process outlined here https://player.fm/legal.

Professor Philipp Koehn of Johns Hopkins University discusses the evolution of machine translation and the fundamentals for using Neural Networks to deliver Machine translation.

Episode Summary:

  • Philipp Koehn Bio
  • What is Machine Translation?
  • Adequacy & Fluency
  • How to Quantify the performance of Machine Translation models
  • The Transition from Statistical approaches to using Neural Networks for translation
  • Validating Outputs of models
  • What can go wrong with Machine Translation?

Resources:

Philipp Koehn latest book - Neural Machine Translation - Amazon link:

https://www.amazon.com/Neural-Machine-Translation-Philipp-Koehn/dp/1108497322

  continue reading

24 episodes

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