Search Results for author:
Found 15 papers, 1 papers with code
deepQuest: A Framework for Neural-based Quality Estimation
Our approach is significantly faster and yields performance improvements for a range of document-level quality estimation tasks.
Findings of the WMT 2018 Shared Task on Quality Estimation
We report the results of the WMT18 shared task on Quality Estimation, i. e. the task of predicting the quality of the output of machine translation systems at various granularity levels: word, phrase, sentence and document.
Sheffield Submissions for the WMT18 Quality Estimation Shared Task
In this paper we present the University of Sheffield submissions for the WMT18 Quality Estimation shared task.
Automatic Translation of Scientific Documents in the HAL Archive
This paper describes the development of a statistical machine translation system between French and English for scientific papers.
Phrase Level Segmentation and Labelling of Machine Translation Errors
This paper presents our work towards a novel approach for Quality Estimation (QE) of machine translation based on sequences of adjacent words, the so-called phrases.
Multimodal Quality Estimation for Machine Translation
We propose approaches to Quality Estimation (QE) for Machine Translation that explore both text and visual modalities for Multimodal QE.
An Exploratory Study on Multilingual Quality Estimation
Predicting the quality of machine translation has traditionally been addressed with language-specific models, under the assumption that the quality label distribution or linguistic features exhibit traits that are not shared across languages.
