Paper Info
Title
An efficient and user-friendly tool for machine translation quality estimation.
Abstract
We present a new version of QUEST - an open source framework for machine translation quality estimation - which brings a number of improvements: (i) it provides a Web interface and functionalities such that non-expert users, e.g. translators or lay-users of machine translations, can get quality predictions (or internal features of the framework) for translations without having to install the toolkit, obtain resources or build prediction models; (ii) it significantly improves over the previous runtime performance by keeping resources (such as language models) in memory; (iii) it provides an option for users to submit the source text only and automatically obtain translations from Bing Translator; (iv) it provides a ranking of multiple translations submitted by users for each source text according to their estimated quality. We exemplify the use of this new version through some experiments with the framework.
Year
Venue
Keywords
2014
LREC 2014 - NINTH INTERNATIONAL CONFERENCE ON LANGUAGE RESOURCES AND EVALUATION
Machine Translation,Translation Evaluation,Translation Quality Estimation
Field
DocType
Citations 
Ranking,Computer science,Machine translation,Artificial intelligence,Natural language processing,User Friendly,Source text,User interface,Language model
Conference
4
PageRank 
References 
Authors
0.45
12
3
Name
Order
Citations
PageRank
Kashif Shah110311.69
Marco Turchi256057.79
lucia specia31217122.84