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 . Llorens. You know one of my bugbears (or perhaps hobby horses) is the Content Tsunami. It is the main pillar of the flimsy business case for Low Quality Translation.. The main question . archeologists. 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. 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.. and parallel corpus generation. Ekansh. Gupta. Rohit. Gupta. Advantages of Neural Machine Translation Models. Require . only a fraction of the memory needed by traditional statistical machine translation (SMT) . 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. 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 . Machine . Translation. . by. . Jointly. Learning . to. . Align. . and. . Translate. Bahdanau. et. al., ICLR 2015. Presented. . by. İhsan Utlu. Outline. . Neural. Machine . Translation. . in . SP2013. Vesa Juvonen. Principal Consultant. Microsoft. Provides built-in . machine translation capabilities on the SharePoint platform. Cloud-based translation services. Based on . Word Automation Service . 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: . 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.. 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: .