1 août 2021 Word alignment which aims to align transla- tionally equivalent words between source and target sentences
Although unnecessary for training neu- ral MT models word alignment still plays an important role in interactive applications of neural machine translation
1 août 2021 a novel neural semi-Markov CRF alignment model which unifies word and phrase align- ments through variable-length spans. We also.
25 sept. 2020 Word alignments can also be viewed as a form of possible explanation of the often opaque behavior of a Neural Machine Translation. (Stahlberg et ...
28 juil. 2019 Prior researches suggest that neural machine translation (NMT) captures word alignment through its attention mechanism however
Word alignments identify translational correspondences between words in a parallel sentence pair and is used for instance
22 mai 2022 alignment graph joining all bilingual word alignment pairs in one graph. Next
One simple solution is NAIVE-ATT which induces word alignments from the attention weights be- tween the encoder and decoder. The next target word is aligned
We introduce a novel discriminative word alignment model which we integrate into a. Transformer-based machine translation model. In experiments based on a
Word alignments can also be viewed as a form of possible explanation of the often opaque behavior of a Neural Machine Translation. (Stahlberg et al. 2018).
Word alignment is an important task of ?nding the correspondence between words in a sentence pair (Brown et al 1993) and used to be a key component of statistical machine translation (SMT) (Koehn et al 2003;Dyer et al 2013) Although word alignment is no longer explicitly modeled in neural machine translation (NMT) (Bahdanau et al
Word alignment is usually inferred by GIZA++ (Och and Ney2003) or FastAlign (Dyer et al 2013) which are based on the statistical IBM word alignment models (Brown et al 1993) Recently neural methods are applied for inferring the word alignment They use NMT-based framework to in-duce alignments through using attention weights or
Word alignment is one of the basic tasks in multilingual Natural Language Processing (NLP) and is used to learn bilingual dictionaries to train statistical machine translation (SMT) sys- tems (Koehn 2010) to ?lter out noise from translation memories (Pham et al 2018) or in quality estimation applications (Specia et al 2017)