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Philipp Koehn (Part 1) - How Neural Networks Have Transformed Machine Translation
Manage episode 297999658 series 2954151
Damien Deighan and Philipp Diesinger, Damien Deighan, and Philipp Diesinger에서 제공하는 콘텐츠입니다. 에피소드, 그래픽, 팟캐스트 설명을 포함한 모든 팟캐스트 콘텐츠는 Damien Deighan and Philipp Diesinger, Damien Deighan, and Philipp Diesinger 또는 해당 팟캐스트 플랫폼 파트너가 직접 업로드하고 제공합니다. 누군가가 귀하의 허락 없이 귀하의 저작물을 사용하고 있다고 생각되는 경우 여기에 설명된 절차를 따르실 수 있습니다 https://ko.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
26 에피소드
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