'Sentence pairs' presentation slideshows

Evolving Word-Aligners via Genetic Programming

Evolving Word-Aligners via Genetic Programming. Ben Heilers CS 294-5 December 10, 2004. Goal. To evolve word aligners through genetic programming. In other words, instead of building a word aligner, building a system which may possibly find a better word aligner than I myself could.

405 views • 27 slides

Stochastic Inversion Transduction Grammars Dekai Wu

Stochastic Inversion Transduction Grammars Dekai Wu. 11-734 Advanced Machine Translation Seminar Presented by: Sanjika Hewavitharana 04/13/2006. Overview. Simple Transduction Grammars Inversion Transduction Grammars (ITGs) Stochastic ITGs Parsing with SITGs Applications of SITGs

254 views • 25 slides

467 views • 24 slides

Acquiring entailment pairs across languages and domains: A data analysis

355 views • 23 slides

Warm-Up: Creating Complex Sentences

508 views • 21 slides

GT Drills Qt 3 2010-2011

276 views • 18 slides

Pre-processing of Bilingual Corpora for Mandarin-English EBMT

324 views • 17 slides

How Could You, Should You and Would You Teach Modals?

How Could You, Should You and Would You Teach Modals?. Prepared by: Stacey Larson-Everson. What are modals?. Auxiliary verbs Can Could Had better May Might Must Ought to Shall Should Will Would. How could I teach modals? Should I teach them?. Why do we use modals?.

435 views • 14 slides

Duluth Word Alignment System

Duluth Word Alignment System. Bridget Thomson McInnes Ted Pedersen University of Minnesota Duluth Computer Science Department. 31 May 2003. Duluth Word Alignment System. Perl implementation of IBM Model 2 Learns a probabilistic model from sentence aligned parallel corpora

285 views • 12 slides

Background

. Constructing a Chinese-Japanese Parallel Corpus from Wikipedia Chenhui Chu, Toshiaki Nakazawa , Sadao Kurohashi (Graduate School of Informatics, Kyoto University). Common Chinese characters. Common Chinese characters. Background. Features. Baseline features

144 views • 1 slides