This paper presents the results of the WMT14 shared tasks, which included a standard news
translation task, a separate medical translation task, a task for run-time estimation of …

This paper presents QUEST++, an open source tool for quality estimation which can predict
quality for texts at word, sentence and document level. It also provides pipelined processing …

Many applications within natural language processing involve performing text-to-text
transformations, ie, given a text in natural language as input, systems are required to …

Human rating of predicted post-editing effort is a common activity and has been used to train
confidence estimation models. However, the correlation between human ratings and actual …

We introduce FDA5 for efficient parameterization, optimization, and implementation of
feature decay algorithms (FDA), a class of instance selection algorithms that use feature …

Quality estimation (QE) task aims to predict the machine translation (MT) quality well by
referring to the source sentence and its MT output. The various applicability of QE proves the …

We use referential translation machines (RTMs) for predicting the semantic similarity of text.
RTMs are a computational model for identifying the translation acts between any two data …

We use referential translation machines (RTMs) for predicting translation performance.
RTMs pioneer a language independent approach to all similarity tasks and remove the need …

Referential translation machines (RTMs) are a computational model effective at judging
monolingual and bilingual similarity while identifying translation acts between any two data …

This paper explores the use of external sources of bilingual information available on-line for
word-level machine translation quality estimation (MTQE). These sources of bilingual …