IR book by Bruce Croft

Title: Search Engines Information Retrieval in Practice by Prof. Bruce Croft
Link: http://ciir.cs.umass.edu/irbook/

Intro: This book provides an overview of the important issues in information retrieval, and how those issues affect the design and implementation of search engines. Not every topic is covered at the same level of detail. The focus is on some of the most important alternatives to implementing search engine components and the information retrieval models underlying them. The target audience for the book is advanced undergraduates in computer science, although it is also a useful introduction for graduate students. (from the link)

 

NAACL 2015 papers

Link: http://naacl.org/naacl-hlt-2015/papers.html

Here is my subjective list of remarkable papers relating to MT research:

 

*** Neural Machine Translation

 

Paul Baltescu and Phil Blunsom. "Pragmatic Neural Language Modelling in Machine Translation"

 

Adrià de Gispert, Gonzalo Iglesias, Bill Byrne. "Fast and Accurate Preordering for SMT using Neural Networks"

 

*** Continuous Models for Statistical Machine Translation

 

Frédéric Blain, Fethi Bougares, Amir Hazem, Loïc Barrault, Holger Schwenk. "Continuous Adaptation to User Feedback for Statistical Machine Translation"

 

Kai Zhao, Hany Hassan, Michael Auli. "Learning Translation Models from Monolingual Continuous Representations"

 

*** Multi-language Translation 

 

Raj Dabre, Fabien Cromieres, Sadao Kurohashi, Pushpak Bhattacharyya. "Leveraging Small Multilingual Corpora for SMT Using Many Pivot Languages"

 

*** Video to Text Translation 

 

Subhashini Venugopalan, Huijuan Xu, Jeff Donahue, Marcus Rohrbach, Raymond Mooney, Kate Saenko. "Translating Videos to Natural Language Using Deep Recurrent Neural Networks" 

 

*** Others

 

Jonathan H. Clark, Chris Dyer, Alon Lavie. "Locally Non-Linear Learning for Statistical Machine Translation via Discretization and Structured Regularization"

 

Graham Neubig, Philip Arthur, Kevin Duh. "Multi-Target Machine Translation with Multi-Synchronous Context-free Grammars"

 

Aurelien Waite and Bill Byrne. "The Geometry of Statistical Machine Translation"

Other papers are also worth reading:

*** News Processing

Areej Alhothali and Jesse Hoey. "Good News or Bad News: Using Affect Control Theory to Analyze Readers' Reaction Towards News Articles"

 

 

Python wrapper for online translators

If you want to use Google Translate and Microsoft Bing Translate for free, you may consider the following Python-based wrappers:

+ Code: Google Translate; Bing Translate

+ Samples:

# Google Translate
import googletrans
gs = googletrans.Googletrans()

languages = gs.get_languages()
print(languages['en'])

print(gs.translate('hello', 'de'))
print(gs.translate('hello', 'zh'))
print(gs.translate('hello', 'vi'))

print(gs.detect('some English words'))

 

#Bing Translate

from mstranslator import Translator

translator =
Translator('cdvhoang', 'HlUUMftdkETWa8E9/jzD4l1CzC8sOhRSJxH+kk0MDBg=')

print(translator.translate('hello', lang_from='en', lang_to='vi')) 

 *** Please note that I don't encourage to use the wrapper for Google Translate because you should respect and pay for using its service (simply it's now commercialized ^_^).