[PDF] Top 20 Addressing the Rare Word Problem in Neural Machine Translation
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Addressing the Rare Word Problem in Neural Machine Translation
... one word at a ...of neural networks to generalize implies that NMT systems will also generalize to novel word phrases and sen- tences that do not occur in the training ... See full document
9
Handling Rare Word Problem using Synthetic Training Data for Sinhala and Tamil Neural Machine Translation
... the rare word problem in Neural Machine Translation (NMT) systems, particularly for under- resourced ...the rare word ...Sinhala translation systems, ... See full document
5
Overcoming the Rare Word Problem for low resource language pairs in Neural Machine Translation
... of neural machine translation (NMT) coined by (Koehn and Knowles, 2017), rare-word problem is consid- ered the most severe one, especially in trans- lation of low-resource ...the ... See full document
8
Addressing word order Divergence in Multilingual Neural Machine Translation for extremely Low Resource Languages
... of word order di- vergence and its mitigation has not been ...(SVO word order) and some Indian (SOV word order) languages, but very little parallel corpora between Indian ... See full document
6
Inducing Embeddings for Rare and Unseen Words by Leveraging Lexical Resources
... for rare words on the basis of the knowl- edge extracted from external lexical ...in addressing the rare word problem for morphologically complex words in the general domain as well as ... See full document
6
Incorporating Word Reordering Knowledge into Attention based Neural Machine Translation
... content-based addressing fashion (Graves et ...current translation status. Lack of ex- plicit models to exploit the word reordering knowledge may lead to attention faults and generate fluent but ... See full document
11
Word Representation Models for Morphologically Rich Languages in Neural Machine Translation
... The rare word problem is exacerbated when translating from morphologically rich languages, where the several morphological variants of words result in a huge vocabulary with a heavy ...70 word ... See full document
6
On the Importance of Word Boundaries in Character level Neural Machine Translation
... The translation problem is then modeled as a mapping between sequences of subword units in the source and target languages (Sennrich et ...One problem related to the subword-based NMT approach is ... See full document
7
Word Transduction for Addressing the OOV Problem in Machine Translation for Similar Resource Scarce Languages
... as machine readable dictionaries, WordNet and any standard parallel corpus, which makes the devel- opment of machine translation (MT) systems very ...chine Translation is not feasible as it ... See full document
8
Neural Machine Translation of Rare Words with Subword Units
... Neural machine translation (NMT) mod- els typically operate with a fixed vocabu- lary, but translation is an open-vocabulary ...the translation of out-of-vocabulary words by backing off ... See full document
11
What Makes Word level Neural Machine Translation Hard: A Case Study on English German Translation
... that rare words are often composed of frequent words, Sennrich et ...OOV problem is not an issue anymore, it is more difficult and time-consuming to train such models (Ling et ... See full document
10
Towards Understanding Neural Machine Translation with Word Importance
... scoring word importance (Section ...of word importance estimation methods under dif- ferent synthetic ...shifting problem, in this exper- iment, we investigate three types of perturbations to avoid ... See full document
10
Greedy Search with Probabilistic N gram Matching for Neural Machine Translation
... Neural machine translation (NMT) models are usually trained with the word-level loss using the teacher forcing algorithm, which not only evaluates the translation improperly but also ... See full document
7
ReWE: Regressing Word Embeddings for Regularization of Neural Machine Translation Systems
... A substantial literature has been devoted to im- proving the generalization of NMT systems. Fadaee et al. (2017) have proposed a data augmen- tation approach for low-resource settings that gen- erates synthetic sentence ... See full document
7
Incorporating Word and Subword Units in Unsupervised Machine Translation Using Language Model Rescoring
... unsupervised machine translation track of the WMT’19 news shared task from German to ...tistical machine translation (PBSMT) model and a pre-trained language model to combine word-level ... See full document
8
Unsupervised Bilingual Word Embedding Agreement for Unsupervised Neural Machine Translation
... as machine translation (Bahdanau et ...large word- pair dictionary poses a major practical problem for many language ...any word dictionary via fully unsupervised ... See full document
11
Target side Word Segmentation Strategies for Neural Machine Translation
... art neural machine translation (NMT) re- quires the vocabulary to be restricted to a limited-size set of several thousand sym- ...investigate word segmen- tation strategies that incorporate ... See full document
12
Syntax Enhanced Neural Machine Translation with Syntax Aware Word Representations
... In this work, we present an implicit syntax en- coding method for NMT, enhancing NMT models by syntax-aware word representations (SAWRs). Figure 1 illustrates the basic idea, where trees are modeled indirectly by ... See full document
11
Neural Machine Translation with Word Predictions
... the problem of training an NMT system with lots of parame- ...of neural networks, which are not specifically targeting the model- ing of the translation process like ... See full document
10
Differentiable Sampling with Flexible Reference Word Order for Neural Machine Translation
... for machine translation: they assume that words in the refer- ence translations and in sampled sequences are aligned at each time step, which results in weak and sometimes misleading training ... See full document
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