PPT-Neural Machine Translation

Omid Kashefi omidKashefipittedu 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. 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. Cost function. Machine Learning. Neural Network (Classification). Binary classification. . . 1 output unit. Layer 1. Layer 2. Layer 3. Layer 4. Multi-class classification . (K classes). K output units. 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) . Conference on Empirical Methods in Natural Language . Processing 2007. 報告者：郝柏翰. 2013/06/04. Thorsten . Brants. , Ashok . C. . Popat. , . Peng. . Xu. , Franz . J. . Och. , Jeffrey Dean. Chong Ho Yu. What is data mining?. Data mining (DM) is a cluster of techniques, including decision trees, artificial neural networks, and clustering, which has been employed in the field Business Intelligence (BI) for years.. 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.. 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. Gap. . between . Human and Machine Translation. Wu. . et. al., . arXiv. - . sept. 2016. Presenter. : Lütfi Kerem Şenel. Outline. . Introduction. . and. . Related. . w. orks. . Model Architecture . 13. . The Deutsch-Schiffman Smalltalk-80 Implementation. Main references. [Kras83] Glenn Krasner (Ed.). Smalltalk-80: Bits of History, Words of Advice. Addison-Wesley Longman Publishing Co., Inc., Boston, MA, USA.1983.. Analogy of Energy Loss . The transfer of energy in any machine necessarily involves energy loss. This is not a theoretical anomaly, but simply a practical problem. To confront this issue, engineers strive to design more efficient machines wherein energy loss is reduced. . 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 . 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. . A good legal translation service is supposed to give you a bit more than mere transformations of words. 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: .