PPT-Neural Machine Translation

by Jointly Learning to Align and Translate Bahdanau et al ICLR 2015 Presented by İhsan Utlu Outline Neural Machine Translation overview Relevant . Minh Tang . Luon. (Stanford University). Iiya. . Sutskever. (Google). Quoc. . V.Le. (Google). Orial. . Vinyals. (Google). Wojciech. . Zaremba. (New York . Univerity. ). Abstract. Neural Machine Translation (NMT) is a new approach to machine translation that has shown promising results that are comparable to traditional approaches. By: Henry Zaremba. Origins of Translator Technology. 1954- IBM gives a demo of a translation program called the “Georgetown-IBM experiment”. 250 words in Russian; 6 grammatical rules. The database was a 16” disk. Machine . Translation. . for Spoken Language Domains. Thang . Luong. IWSLT 2015. (Joint work with Chris Manning). Neural Machine Translation (NMT). End-to-end. neural approach to MT:. Simple and coherent.. Introduction to MT. Machine Translation. Fully automatic. Helping human translators. Enter Source Text:. Translation from Stanford’s . Phrasal. :.  这 不过 是 一 个 时间 的 问题 . .. This is only a matter of time.. (it’s all about the readers). Mikel L. . Forcada. Universitat. . d’Alacant. (Spain). Prompsit. Language Engineering (. Elx. , Spain). European Association for Machine Translation. All translation is communication. a . Panel Discussion. Organized. . by. . Alan K. . Melby. . PANELLISTS. : . Joanna . Drugan. Mikel . Forcada. Dieter Rummel. . David Wood. Moderator :. . . Olaf-Michael Stefanov. Professional Translation In a Pre-singularity World. Omid Kashefi. omid.Kashefi@pitt.edu. Visual Languages Seminar. November, 2016. Outline. Machine Translation. Deep Learning. Neural Machine Translation. Machine Translation. Machine Translation. Use of software in translating from one language into another. Gap. . between . Human and Machine Translation. Wu. . et. al., . arXiv. - . sept. 2016. Presenter. : Lütfi Kerem Şenel. Outline. . Introduction. . and. . Related. . w. orks. . Model Architecture . Translation. Unit 1. 1.1 Basic Definitions. To realize what the translator does in the process of translation, we must clarify a number of terms that will be used throughout the course: . Text: . Any stretch of speech or writing assumed to make a coherent whole. . SYNTAX BASED MACHINE TRANSLATION UNDER GUIDANCE OF PROF PUSHPAK BHATTACHARYYA PRESENTED BY ROUVEN R Ӧ HRIG (10V05101) ERANKI KIRAN (10438004) SRIHARSA MOHAPATRA (10405004) ARJUN ATREYA (09405011) 9/4/2011 . Thang . Luong. ACL 2015. Joint work with. : . Ilya Sutskever. , . Quoc . Le. , . Oriol Vinyals. , . & . Wojciech. . Zaremba. .. Standard Machine Translation (MT). T. ranslate . locally phrases by phrases: . i. n Cross-lingual Question Answering. Kyoshiro Sugiyama. , Masahiro Mizukami, Graham Neubig, . Koichiro. Yoshino, Sakriani Sakti, Tomoki Toda, Satoshi Nakamura. NAIST, Japan. Question answering (QA). What is the equation of the blue curve?. Lost in translation?. The blue curve on the right is a translation. of the red curve. What is the equation of. the blue curve?. Notes and Solution. The blue curve is a translation of the red. May.  4. , 20. 21. Junjie Hu. Materials largely borrowed from Austin Matthews. One naturally wonders if the problem of translation could conceivably be treated as a problem in cryptography. When I look at an article in Russian, I say: .