Quality estimation aims to measure the quality of translated content without access to a
reference translation. This is crucial for machine translation systems in real-world scenarios …

In computer-aided translation scenarios, quality estimation of machine translation
hypotheses plays a critical role. Existing methods for word-level translation quality …

Abstract Machine translation quality estimation (QE) aims to evaluate the result of translation
without reference. Despite the progress it has made, state-of-the-art QE models are proven …

The translation quality estimation (QE) task, particularly the QE as a Metric task, aims to
evaluate the general quality of a translation based on the translation and the source …

Abstract Machine Translation Quality Estimation (QE) aims to build predictive models to
assess the quality of machine-generated translations in the absence of reference …

Quality estimation (QE) aims to assess the quality of machine translations when reference
translations are unavailable. QE plays a crucial role in many real-world applications of …

Abstract Machine Translation Quality Estimation (QE) is a task of predicting the quality of
machine translations without relying on any reference. Recently, the predictor-estimator …

We present Marmot~―a new toolkit for quality estimation (QE) of machine translation output.
Marmot contains utilities targeted at quality estimation at the word and phrase level …

Quality estimation (QE) of machine translation (MT) aims to evaluate the quality of machine-
translated sentences without references and is important in practical applications of MT …

Machine Translation Quality Estimation (QE) is the task of evaluating translation output in the
absence of human-written references. Due to the scarcity of human-labeled QE data …