[PDF] Top 20 Generalized Data Augmentation for Low Resource Translation
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Generalized Data Augmentation for Low Resource Translation
... training data, as the LRL data will be ...augmented data the rare word is not in the lowest 10 th frequency percentile ...corresponding translation BLEU score is shown in Figure ...our ... See full document
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Naive Regularizers for Low-Resource Neural Machine Translation
... training data are not avail- able, neural machine translation has come with diminishing returns (Koehn and Knowles, ...of translation models depart- ing heavily from simple characteristics of the ... See full document
10
METIS-II: Machine Translation for Low Resource Languages
... While industrial technologies are mainly rule-based, cur- rent research is mainly on data-driven methods (like SMT and EBMT). Both SMT and EBMT systems rely on par- allel corpora, and the development of a RBMT ... See full document
6
Transfer Learning for Low Resource Neural Machine Translation
... machine translation (NMT) has been shown effective in large data scenarios, but is much less effective for low-resource ...of low-resource ...the low-resource pair ... See full document
8
Meta Learning for Low Resource Neural Machine Translation
... performance. Low Resource Translation NMT is known to easily over-fit and result in an inferior performance when the training data is limited (Koehn and Knowles, ...of low ... See full document
10
Handling Syntactic Divergence in Low resource Machine Translation
... While neural machine translation (NMT; Bah- danau et al. (2015); Vaswani et al. (2017)) now represents the state of the art in the majority of large-scale MT benchmarks (Bojar et al., 2017), it is highly dependent ... See full document
7
The IIIT H Gujarati English Machine Translation System for WMT19
... Machine Translation for low resource ...the data scarcity ...Machine Translation are two important areas of research that tackles this ...a low resource language ... See full document
5
Improving Low Resource Neural Machine Translation with Filtered Pseudo Parallel Corpus
... the translation model (Wang et ...better translation performance and reduce time- complexity with a small high-quality ...filters data by calculating similarity be- tween source and target ... See full document
9
Japanese Russian TMU Neural Machine Translation System using Multilingual Model for WAT 2019
... Asian Translation (Nakazawa et ...news translation. It is a very challenging task considering: (a) extremely low resource setting, the size of parallel data is only 12k parallel ... See full document
6
Training Data Augmentation for Context Sensitive Neural Lemmatizer Using Inflection Tables and Raw Text
... in low resource ...baseline data augmentation approach (AE Aug Baseline) inspired by Bergma- nis et ...in low-resource ... See full document
10
Statistical Machine Translation with a Factorized Grammar
... Factorized grammars not only relieve the burden on space and search, but also alleviate the sparse data problem, especially for low-resource language translation with few training data. ... See full document
10
Revisiting Low Resource Neural Machine Translation: A Case Study
... machine translation (NMT) drops starkly in low-resource conditions, underperforming phrase-based statistical machine translation (PBSMT) and requiring large amounts of aux- iliary data ... See full document
11
Trivial Transfer Learning for Low Resource Neural Machine Translation
... The baselines are either models trained purely on the child parallel data or only on the parent data. The second baseline only indicates the relat- edness of languages because it is only tested but never ... See full document
9
Unsupervised Source Hierarchies for Low Resource Neural Machine Translation
... training data with an external parser, and such parsers may be unavailable for low-resource lan- ...improve low-resource NMT, but we would need a way of doing so without an external ... See full document
7
Neural Machine Translation of Low Resource and Similar Languages with Backtranslation
... Additionally, the organizers provided monolingual datasets for Spanish, Portuguese, Czech and Polish. They all largely came from the same sources including the Europarl, JRC-Acquis, New Crawl, and News Commentary ... See full document
12
Combining Bilingual and Comparable Corpora for Low Resource Machine Translation
... comparable data (Ravi and Knight, 2011; Dou and Knight, 2012; Nuhn et ...high resource language do- main adaptation for a machine translation ... See full document
9
Exploiting Linguistic Knowledge for Low-Resource Neural Machine Translation
... the low-resource NMT to explicitly utilize the source-side linguistic knowledge, which models the word sequence in parallel to the linguistic features by using two separate encoders with parameter ...the ... See full document
9
Understanding Data Augmentation in Neural Machine Translation: Two Perspectives towards Generalization
... Many Data Augmentation (DA) methods have been proposed for neural machine translation. Existing works measure the superiority of DA methods in terms of their performance on a specific test set, but ... See full document
7
Supervised neural machine translation based on data augmentation and improved training & inference process
... training data, we tried four kinds of combinations shown in Table ...For data augmentation and back translation is mutual exclusion, we trained different models and did ensemble to combine all ... See full document
5
Statistical Machine Translation in Low Resource Settings
... Recently, Klementiev et al. (2012b) induced dis- tributed representations for the crosslingual setting. There, the induced embedding is learned jointly over multiple languages so that the representations of se- ... See full document
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