Машиналық аударма метрикалары

We present two regression models for the prediction of pairwise preference judgments among MT hy- potheses. Both models are based on feature sets that are motivated by textual entailment and …...

We propose to re-examine the hypothesis that automated metrics developed for MT evalu- ation can prove useful for paraphrase iden- tification in light of the significant work on the development …...

AbstractThere are several MT metrics used to evaluate translation into Spanish, although most of them use partial or little linguistic information. In this paper we present the multilingual capability of …...

AbstractCopying mechanism has been commonly used in neural paraphrasing networks and other text generation tasks, in which some important words in the input sequence are preserved in the output sequence. …...

AbstractNeural Machine Translation (NMT) currently exhibits biases such as producing translations that are too short and overgenerating frequent words, and shows poor robustness to copy noise in training data or …...

AbstractTrainable evaluation metrics for machine translation (MT) exhibit strong correlation with human judgements, but they are often hard to interpret and might produce unreliable scores under noisy or out-of-domain data. …...

AbstractAutomatic translations with critical errors may lead to misinterpretations and pose several risks for the user. As such, it is important that Machine Translation (MT) Evaluation systems are robust to …...

AbstractAutomatic machine translation (MT) metrics are widely used to distinguish the quality of machine translation systems across relatively large test sets (system-level evaluation). However, it is unclear if automatic metrics …...