Minimum Bayes Risk Decoding

This paper describes the techniques we explored to improve the translation of news text in the German-English and Hungarian-English tracks of the WMT09 shared translation task. Beginning with a convention …...

A novel and robust approach to improv- ing statistical machine translation fluency is developed within a minimum Bayes- risk decoding framework. By segment- ing translation lattices according to con- fidence …...

This paper describes the system we devel- oped to improve German-English transla- tion of News text for the shared task of the Fifth Workshop on Statistical Machine Translation. Working within …...

Efficient computation of n-gram posterior probabilities from lattices has applications in lattice-based minimum Bayes-risk de- coding in statistical machine translation and the estimation of expected document frequencies from spoken corpora. …...

We introduce two first-order graph-based de- pendency parsers achieving a new state of the art. The first is a consensus parser built from an ensemble of independently trained greedy LSTM …...

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 …...

AbstractThis paper describes CMU’s submissions to the IWSLT 2022 dialect speech translation (ST) shared task for translating Tunisian-Arabic speech to English text. We use additional paired Modern Standard Arabic data …...

AbstractDespite the progress in machine translation quality estimation and evaluation in the last years, decoding in neural machine translation (NMT) is mostly oblivious to this and centers around finding the …...