[PDF] Top 20 Neural vs Phrase Based Machine Translation in a Multi Domain Scenario
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Neural vs Phrase Based Machine Translation in a Multi Domain Scenario
... The word segmentation approach proposed in (Sennrich et al., 2016b) has been shown to be very effective in obtaining open vocabulary trans- lation with a fixed vocabulary in NMT. While this holds true for several cases ... See full document
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Multi Domain Neural Machine Translation through Unsupervised Adaptation
... ral Machine Translation (NMT) under the following three conditions posed by real- world application ...without domain in- ...unsupervised multi-domain setting, we explore an ef- ficient ... See full document
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Neural Machine Translation Leveraging Phrase based Models in a Hybrid Search
... For the hybrid approach, we train a phrase-table on the in-domain data and split the source and tar- get phrases with BPE afterwards for compatibility with the NMT vocabulary. With the hybrid ap- proach, ... See full document
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Neural versus Phrase Based Machine Translation Quality: a Case Study
... shared translation task (Bojar et ...best phrase-based models on a couple of lan- guage ...recurrent neural network encoder- decoder model, originally proposed in (Sutskever et ...the ... See full document
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Learning to Generate Word and Phrase Embeddings for Efficient Phrase Based Neural Machine Translation
... Neural machine translation (NMT) often fails in one-to-many translation, ...of multi-word expressions, compounds, and ...the translation of phrases, phrase-based ... See full document
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Domain Control for Neural Machine Translation
... Machine translation systems are very sen- sitive to the domains they were trained ...Several domain adaptation techniques have already been deeply ...for neural ma- chine translation ... See full document
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NICT 2 Translation System for WAT2016: Applying Domain Adaptation to Phrase based Statistical Machine Translation
... as multi-domain data because it includes chemistry, electricity, machine, and physics patents with their domain ID, and thus it is suitable for observing the effects of domain ... See full document
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Towards one shot learning for rare word translation with external experts
... Neural machine translation (NMT) has significantly improved the quality of au- tomatic translation ...the translation of rare ...using phrase-based models to simulate ... See full document
10
Pseudo Word for Phrase Based Machine Translation
... most Phrase-Based Statistical Machine Translation (PB-SMT) systems starts from automatically word aligned parallel cor- ...basic multi-word expression that character- izes minimal ... See full document
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Investigating Phrase-Based and Neural-Based Machine Translation on Low-Resource Settings
... Building An English-Vietnamese Bilingual Cor- pus from Wikipedia As presented in Section 2.3, we used the Wikpedia database dumps to extract par- allel titles, which were updated on 2017-01-20. Af- ter collecting, ... See full document
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Dynamically Integrating Cross Domain Translation Memory into Phrase Based Machine Translation during Decoding
... above scenario, we will thus train our integrated model on the out ...a domain-mismatch problem for this cross-domain ...technical domain, which is suitable for TM application, the ... See full document
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NAVER Machine Translation System for WAT 2015
... Neural machine translation (NMT) is a new ap- proach to machine translation that has shown promising results compared to the existing ap- proaches such as phrase-based ... See full document
5
Phrase Based & Neural Unsupervised Machine Translation
... word-by-word translation with an inferred bilingual ...each domain to infer the structure in the data (underlying continuous curve); it acts as a data-driven prior to denoise/correct sentences (illustrated ... See full document
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Phrase Reordering Model Integrating Syntactic Knowledge for SMT
... For Rule (1) and Rule (2), they strictly comply with the syntactic structures. Given two peer phrases, we have two choices to use one of them. Thus, we use maximum entropy (ME) model algo- rithm to estimate their ... See full document
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Phrase based Unsupervised Machine Translation with Compositional Phrase Embeddings
... to translation is the same for all methods: learn- ing word level embedding spaces for source and target languages and then aligning these ...either neural network models or parts of SMT pipeline is done ... See full document
7
Syntactic Constraints on Phrase Extraction for Phrase Based Machine Translation
... a phrase pair ex- traction procedure is the resulting phrase transla- tion table is very large, especially when a large quantity of parallel data is ...some phrase translation pairs are ... See full document
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A Character level Decoder without Explicit Segmentation for Neural Machine Translation
... proposed neural ma- chine translation system can directly handle trans- lation at the level of characters without any word ...for neural machine translation to translate at the level of ... See full document
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Comparison between NMT and PBSMT Performance for Translating Noisy User Generated Content
... both phrase- based and NMT models to translate ...that phrase-base systems are more robust to noise than NMT systems and we provided several explanations about thisrelatively surprising fact, among ... See full document
13
SampleRank Training for Phrase Based Machine Translation
... Margin-based techniques have the advantage that they do not have to employ expensive and com- plex algorithms to calculate the feature expectations. Typically, either perceptron ((Liang et al., 2006), (Arun and ... See full document
11
Supertagged Phrase Based Statistical Machine Translation
... There are currently two supertagging approaches available: LTAG-based (Bangalore & Joshi, 1999) and CCG-based (Clark & Curran, 2004). Both the LTAG (Chen et al., 2006) and the CCG supertag sets ... See full document
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