Philipp Koehn
Philipp Koehn
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Machine Translation - Lecture 22: Computer Aided Translation
Computer Aided Translation lecture of the Johns Hopkins University class on "Machine Translation".
Course web site with slides and additional material:
mt-class.org/jhu/
Textbooks:
Statistical Machine Translation www.statmt.org/book/
Neural Machine Translation www.statmt.org/nmt-book/
Переглядів: 804

Відео

Machine Translation - Lecture 21: Corpus Acquisition from the Internet
Переглядів 7063 роки тому
Corpus Acquisition from the Internet lecture of the Johns Hopkins University class on "Machine Translation". Course web site with slides and additional material: mt-class.org/jhu/ Textbooks: Statistical Machine Translation www.statmt.org/book/ Neural Machine Translation www.statmt.org/nmt-book/
Machine Translation - Lecture 20: Analysis and Visualization
Переглядів 5143 роки тому
Analysis and Visualization lecture of the Johns Hopkins University class on "Machine Translation". Course web site with slides and additional material: mt-class.org/jhu/ Textbooks: Statistical Machine Translation www.statmt.org/book/ Neural Machine Translation www.statmt.org/nmt-book/
Machine Translation - Lecture 18: Syntax and Semantics
Переглядів 6473 роки тому
Syntax and Semantics lecture of the Johns Hopkins University class on "Machine Translation". Course web site with slides and additional material: mt-class.org/jhu/ Textbooks: Statistical Machine Translation www.statmt.org/book/ Neural Machine Translation www.statmt.org/nmt-book/
Machine Translation - Lecture 19: Challenges
Переглядів 5863 роки тому
Challenges lecture of the Johns Hopkins University class on "Machine Translation". Course web site with slides and additional material: mt-class.org/jhu/ Textbooks: Statistical Machine Translation www.statmt.org/book/ Neural Machine Translation www.statmt.org/nmt-book/
Machine Translation - Lecture 17: Beyond Parallel Data
Переглядів 6483 роки тому
Beyond Parallel Corpora lecture of the Johns Hopkins University class on "Machine Translation". Course web site with slides and additional material: mt-class.org/jhu/ Textbooks: Statistical Machine Translation www.statmt.org/book/ Neural Machine Translation www.statmt.org/nmt-book/
Machine Translation - Lecture 16: Adaptation
Переглядів 5163 роки тому
Adaptation lecture of the Johns Hopkins University class on "Machine Translation". Course web site with slides and additional material: mt-class.org/jhu/ Textbooks: Statistical Machine Translation www.statmt.org/book/ Neural Machine Translation www.statmt.org/nmt-book/
Machine Translation - Lecture 15: Words and Morphology
Переглядів 5603 роки тому
Words and Morphology lecture of the Johns Hopkins University class on "Machine Translation". Course web site with slides and additional material: mt-class.org/jhu/ Textbooks: Statistical Machine Translation www.statmt.org/book/ Neural Machine Translation www.statmt.org/nmt-book/
Machine Translation - Lecture 14: Alternative Architectures
Переглядів 5123 роки тому
Alternative Architectures lecture of the Johns Hopkins University class on "Machine Translation". Course web site with slides and additional material: mt-class.org/jhu/ Textbooks: Statistical Machine Translation www.statmt.org/book/ Neural Machine Translation www.statmt.org/nmt-book/
Machine Translation - Lecture 13: Machine Learning Tricks
Переглядів 5593 роки тому
Machine Learning Tricks lecture of the Johns Hopkins University class on "Machine Translation". Course web site with slides and additional material: mt-class.org/jhu/ Textbooks: Statistical Machine Translation www.statmt.org/book/ Neural Machine Translation www.statmt.org/nmt-book/
Machine Translation - Lecture 12: Neural Translation Model Decoding
Переглядів 7793 роки тому
Neural Translation Model Decoding lecture of the Johns Hopkins University class on "Machine Translation". Course web site with slides and additional material: mt-class.org/jhu/ Textbooks: Statistical Machine Translation www.statmt.org/book/ Neural Machine Translation www.statmt.org/nmt-book/
Machine Translation - Lecture 11: Neural Translation Models
Переглядів 1,3 тис.3 роки тому
Neural Translation Model lecture of the Johns Hopkins University class on "Machine Translation". Course web site with slides and additional material: mt-class.org/jhu/ Textbooks: Statistical Machine Translation www.statmt.org/book/ Neural Machine Translation www.statmt.org/nmt-book/
Machine Translation - Lecture 10: Neural Language Models
Переглядів 1,5 тис.3 роки тому
Neural Language Model lecture of the Johns Hopkins University class on "Machine Translation". Course web site with slides and additional material: mt-class.org/jhu/ Textbooks: Statistical Machine Translation www.statmt.org/book/ Neural Machine Translation www.statmt.org/nmt-book/
Machine Translation - Lecture 9: Computation Graphs
Переглядів 6143 роки тому
Computation Graphs lecture of the Johns Hopkins University class on "Machine Translation". Course web site with slides and additional material: mt-class.org/jhu/ Textbooks: Statistical Machine Translation www.statmt.org/book/ Neural Machine Translation www.statmt.org/nmt-book/
Machine Translation - Lecture 8: Introduction to Neural Networks
Переглядів 1,4 тис.4 роки тому
Introduction to Neural Networks lecture of the Johns Hopkins University class on "Machine Translation". Course web site with slides and additional material: mt-class.org/jhu/ Textbooks: Statistical Machine Translation www.statmt.org/book/ Neural Machine Translation www.statmt.org/nmt-book/
Machine Translation - Lecture 7: Evaluation
Переглядів 2,6 тис.4 роки тому
Machine Translation - Lecture 7: Evaluation
Machine Translation - Lecture 6: Decoding
Переглядів 1,8 тис.4 роки тому
Machine Translation - Lecture 6: Decoding
Machine Translation - Lecture 5: Phrase Based Models
Переглядів 3 тис.4 роки тому
Machine Translation - Lecture 5: Phrase Based Models
Machine Translation - Lecture 4: IBM Model 1 and the EM Algorithm
Переглядів 8 тис.4 роки тому
Machine Translation - Lecture 4: IBM Model 1 and the EM Algorithm
Machine Translation - Lecture 3: Language Models
Переглядів 2,8 тис.4 роки тому
Machine Translation - Lecture 3: Language Models
Machine Translation - Lecture 2: Basics in Language and Probability
Переглядів 3,5 тис.4 роки тому
Machine Translation - Lecture 2: Basics in Language and Probability
Machine Translation - Lecture 1: Introduction
Переглядів 15 тис.4 роки тому
Machine Translation - Lecture 1: Introduction

КОМЕНТАРІ

  • @jenniferkychu6109
    @jenniferkychu6109 3 місяці тому

    Thank you for sharing the course on UA-cam.

  • @bishwaranjandas221
    @bishwaranjandas221 4 місяці тому

    very nice lecture, thank you so much

  • @hebozhe
    @hebozhe 5 місяців тому

    Very informative! Much obliged.

  • @nxsounds853
    @nxsounds853 6 місяців тому

    fucking terrible

  • @translationtechnologies-ne5347
    @translationtechnologies-ne5347 6 місяців тому

    Hi! Thank you for the very informative lecture. What is the name of the annotation tool or where to find it? Thanks in advance.

    • @phkoehn
      @phkoehn 6 місяців тому

      The code for the tool shown in the slides is not available. There is an open source tool called Appraise - github.com/cfedermann/Appraise - that you find valuable.

    • @translationtechnologies-ne5347
      @translationtechnologies-ne5347 6 місяців тому

      @@phkoehnThank you!

  • @23232323rdurian
    @23232323rdurian Рік тому

    and the best trick is the data structure used holding the language stats, that apparently gets keyed by current context, a vector of word embeddings????

  • @23232323rdurian
    @23232323rdurian Рік тому

    I guess the RNN state has to also keep a whole English/German dictionary as well as a gigantic English language data structure that remembers all the occurrence/context statistics for every Ngram and every context Q-deep.....also for German.....and I doubt the RNN state is carrying around all that info from one step to the next..... so....how? maybe it'll get cleared up in future lectures...I hope so... RNN doesnt just <know> that it otta be <Haus> in German when it's <house> in English.....RNN is relying on a huge exhaustive statistical compilation that took place BEFORE we ever tried to translate anything....involving multi-BILLIONs of words of parallel text, then also English and also German text....musta needed MONTHs to acquire and weeks to execute...

  • @Liiiiiiina_22
    @Liiiiiiina_22 Рік тому

    Thank you so much i was looking for explanation about this topic glad i found whole series about it

  • @ajitkumar15
    @ajitkumar15 2 роки тому

    I simply became fan of your videos on MT.. Thank you so much !!!

  • @deepwavv
    @deepwavv 2 роки тому

    Thank you so much for making this high-quality course available for everyone! This is like a treasure for those who want to learn more about MT :)

  • @ritamsarkar7753
    @ritamsarkar7753 2 роки тому

    it should be 5^3 not 4^3

  • @pss_crs
    @pss_crs 2 роки тому

    In my thoughts outbof this lectur beside the technical issues face TM is language based on the research (English), there's no fixed mathematical rules the languages so we need a language helps us the challenge. I'm not linguist but after my mom language Somali English and Arabic are secondary and my thoughts are around it. English is more flexible language and well documented on the other hand not good when it comes Grammarly and using cases also it lacking on vocabulary, speakers put alot of effort on portability to other languages and it worked but still near full percent at last whiting is too poor we all know pronunciation is base of learning the language. where as Arabic have rigid language structuring and grammar understanding, vocabulary is rich enough as far My understanding portability to other language is to easy if you can speak, and write Arabic every language is be easy to learn other languages what language family it is, if learn how to read Arabic you can't miss pronounce. Somali is where between them,

  • @BizarreKisse
    @BizarreKisse 3 роки тому

    This is exactly what i was looking for but the audio quality is making it really difficult to follow the explanation. Volume is maxed out but still inaudible at many places.

  • @shailpandey2219
    @shailpandey2219 3 роки тому

    Good

  • @dewinmoonl
    @dewinmoonl 3 роки тому

    35:51 literally crickets in the background lol appreciate the late night recording bro

  • @amberkhan8779
    @amberkhan8779 3 роки тому

    useless lecture dont waste your time here

  • @andrasaponyi343
    @andrasaponyi343 4 роки тому

    Thank you for making this publicly available!

  • @sheikhakbar2067
    @sheikhakbar2067 4 роки тому

    Thanks, professor Philipp, very useful lectures. Could you recommend a book/resource on probability/maths that's necessary to follow the lectures for those who's been out of college for a long time?

  • @sheikhakbar2067
    @sheikhakbar2067 4 роки тому

    Thanks.

  • @akbarghurbal
    @akbarghurbal 4 роки тому

    Looking forward for the rest of the series. Thanks.