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Philipp Koehn (Part 1) - How Neural Networks Have Transformed Machine Translation
Manage episode 297999658 series 2954151
Contenuto fornito da Damien Deighan and Philipp Diesinger, Damien Deighan, and Philipp Diesinger. Tutti i contenuti dei podcast, inclusi episodi, grafica e descrizioni dei podcast, vengono caricati e forniti direttamente da Damien Deighan and Philipp Diesinger, Damien Deighan, and Philipp Diesinger o dal partner della piattaforma podcast. Se ritieni che qualcuno stia utilizzando la tua opera protetta da copyright senza la tua autorizzazione, puoi seguire la procedura descritta qui https://it.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
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