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Inferring translation candidates for multilingual dictionary generation with multi-way neural machine translation
2019
Preserved Fulltext
additionally with a relatively small human-validated dictionary to infer new translation candidates. ...
Since multilingual dictionary creation and curation is a time-consuming task, we explored the use of multi-way neural machine translation trained on corpora of languages from the same family and trained ...
Conclusion In this work, we have shown that we can enrich an existing dictionary with multilingual knowledge by using multi-way neural machine translation trained on data that does not include parallel ...
doi:10.13025/s89k9j
fatcat:5jkpafk2eng63p6htnqa2ey5sa
TIAD 2019 Shared Task: Leveraging Knowledge Graphs with Neural Machine Translation for Automatic Multilingual Dictionary Generation
2019
Zenodo
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We present three methods based on graph analysis and neural machine translation and show that we can generate translations without parallel data. ...
This paper describes the different proposed approaches to the TIAD 2019 Shared Task, which consisted in the automatic discovery and generation of dictionaries leveraging multilingual knowledge bases. ...
; a path-based graph approach which retrieves the translation candidates based on translation inference using the language paths of the Apertium dictionaries; a multi-way neural machine translation (NMT ...
doi:10.5281/zenodo.3266899
fatcat:2wcdo7v67vbf5kdbzwtvqvgabu
Inferring translation candidates for multilingual dictionary generation
2019
Zenodo
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additionally with a relatively small human-validated dictionary to infer new translation candidates. ...
Since multilingual dictionary creation and curation is a time-consuming task, we explored the use of multi-way neural machine translation trained on corpora of languages from the same family and trained ...
Conclusion In this work, we have shown that we can enrich an existing dictionary with multilingual knowledge by using multi-way neural machine translation trained on data that does not include parallel ...
doi:10.5281/zenodo.3266898
fatcat:5lw46c2ihjd5lik4qknnmhaoii
Neural Label Search for Zero-Shot Multi-Lingual Extractive Summarization
[article]
2022
arXiv
pre-print
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In this way, it is possible to translate the English dataset to other languages and obtain different sets of labels again using heuristics. ...
Given English gold summaries and documents, sentence-level labels for extractive summarization are usually generated using heuristics. ...
Note that we do use both the word replacement and machine translation methods to generate multilingual labels (see the next section). ...
arXiv:2204.13512v2
fatcat:42toqnprsjad3avowq2qayuyym
Results of the Translation Inference Across Dictionaries 2019 Shared Task
2019
Zenodo
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The objective of the Translation Inference Across Dictionaries (TIAD) shared task is to explore and compare methods and techniques that infer translations indirectly between language pairs, based on other ...
bilingual/multilingual lexicographic resources. ...
Acknowledgements We would like to thank Michael Ruppert (University of Erlangen-Nuremberg) for his assistance with the Word2Vec baseline. ...
doi:10.5281/zenodo.3555154
fatcat:2yhcyak7lbh3vpp43cmw2n2pii
Constraint Translation Candidates: A Bridge between Neural Query Translation and Cross-lingual Information Retrieval
[article]
2020
arXiv
pre-print
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With the help of deep learning, neural machine translation (NMT) has shown promising results on various tasks. ...
The constraint translation candidates are employed at both of training and inference time, thus guiding the translation model to learn and generate well performing target queries. ...
Sarwar [16] proposes a multi-task learning approach to train a neural translation model with a Relevance-based Auxiliary Task (RAT) for search query translation. ...
arXiv:2010.13658v1
fatcat:voprjm6qnnhgxme2s5bs2xkfje
Translation Inference through Multi-lingual Word Embedding Similarity
2019
Zenodo
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This paper describes our contribution to the Shared Task on Translation Inference across Dictionaries (TIAD-2019). ...
We use the similarity of the word embeddings to predict candidate translations. ...
Ready-to-use Multilingual Linked Language Data for Knowledge Services across Sectors" funded in the European Union's Horizon 2020 research and innovation programme under grant agreement No 825182. ...
doi:10.5281/zenodo.3555183
fatcat:ky5avcys7vd4lglkyuqw3fpvfi
Code-Mixing on Sesame Street: Dawn of the Adversarial Polyglots
[article]
2021
arXiv
pre-print
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2021 pre-print arXiv:2103.09593v2 fatcat:n4e6vspuyjeezj4mola7fyn26uOther Versions
The former uses bilingual dictionaries to propose perturbations and translations of the clean example for sense disambiguation. ...
In multilingual communities, it is common for polyglots to code-mix when conversing with each other. ...
XNLI is a multilingual dataset for natural language
inference (NLI) with parallel translations for each
example in fifteen languages. ...
arXiv:2103.09593v3
fatcat:epgdk4dr3zg7bn5jjqpaediwzy
Machine translation for everyone: Empowering users in the age of artificial intelligence
[article]
2022
Zenodo
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It presents a rationale for learning about MT, and provides both a basic introduction to contemporary machine-learning based MT, and a more advanced discussion of neural MT. ...
Language learning and translation have always been complementary pillars of multilingualism in the European Union. ...
Thanks also to Reinhard Rapp and Felix Kopecky for their thorough review of this chapter. Any remaining errors are mine alone. ...
doi:10.5281/zenodo.6653405
fatcat:fqpka6rnvrcqbpmchjt4u7wiwq
Neural Natural Language Generation: A Survey on Multilinguality, Multimodality, Controllability and Learning
2022
The Journal of Artificial Intelligence Research
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These methods combine generative language learning techniques with neural-networks based frameworks. ...
This report also focuses on the seminal applications of these NNLG models such as machine translation, description generation, automatic speech recognition, abstractive summarization, text simplification ...
Acknowledgments This work has been partially supported by the European Commission ICT COST Action "Multi-task, Multilingual, Multi-modal Language Generation" (CA18231). ...
doi:10.1613/jair.1.12918
fatcat:xfnul3j5azchfe6pvgvwy3z6em
Meemi: A Simple Method for Post-processing and Integrating Cross-lingual Word Embeddings
[article]
2020
arXiv
pre-print
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The resulting (monolingual and multilingual) spaces show consistent gains over the current state-of-the-art in standard intrinsic tasks, namely dictionary induction and word similarity, as well as in extrinsic ...
tasks such as cross-lingual hypernym discovery and cross-lingual natural language inference. ...
Acknowledgments Yerai Doval has been supported by the Spanish Ministry of Economy, Industry and Competitiveness (MINECO) through the ANSWER-ASAP project (TIN2017-85160-C2-2-R); by the Spanish State Secretariat for ...
arXiv:1910.07221v4
fatcat:ezeepywtkfdqbalfdpa6vpqqdy
A Deep Neural Network Approach To Parallel Sentence Extraction
[article]
2017
arXiv
pre-print
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quality of the extracted parallel sentences and the translation performance of statistical machine translation systems. ...
We propose an end-to-end deep neural network approach to detect translational equivalence between sentences in two different languages. ...
The translations with a probability score above 10% from the estimated translation tables are used to infer bilingual dictionaries that are used in the word-overlap filter for candidate sentence pair selection ...
arXiv:1709.09783v1
fatcat:2xkr7bbnzrcmfipn7eaxgzj4na
Neural Machine Translation for Low-Resource Languages: A Survey
[article]
2021
arXiv
pre-print
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Neural Machine Translation (NMT) has seen a tremendous spurt of growth in less than ten years, and has already entered a mature phase. ...
While considered as the most widely used solution for Machine Translation, its performance on low-resource language pairs still remains sub-optimal compared to the high-resource counterparts, due to the ...
Methodology We queried Google Scholar with the query "neural machine translation" + "language" (e.g. "neural machine translation" + "Hindi"). ...
arXiv:2106.15115v1
fatcat:4w3jtdd4q5fnjbfznrqq7glxdu
Pre-training Multilingual Neural Machine Translation by Leveraging Alignment Information
[article]
2021
arXiv
pre-print
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2020 pre-print arXiv:2010.03142v2 fatcat:o77pr2c5wzb7npd3swlrz3lvkqOther Versions
We propose mRASP, an approach to pre-train a universal multilingual neural machine translation model. ...
We investigate the following question for machine translation (MT): can we develop a single universal MT model to serve as the common seed and obtain derivative and improved models on arbitrary language ...
We would also like to thank Liwei Wu, Huadong Chen, Qianqian Dong, Zewei Sun, and Weiying Ma for their useful suggestion and help with experiments. ...
arXiv:2010.03142v3
fatcat:v5zcixzrurecnnmlaewkmxzg6u
Low-resource Languages: A Review of Past Work and Future Challenges
[article]
2020
arXiv
pre-print
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Machine translation A Neural Machine Translation model, known as NMT model, aims to translate a sentence from a source language to a target language. ...
NEL Cross-lingual NEL (XEL) generally consists in two steps: candidate generation and candidate ranking. ...
Yoda system for wmt16 shared task: Bilingual document alignment. In Proceedings of the First Conference on Machine Translation: Volume 2, Shared Task Papers, pages 679-684. ...
arXiv:2006.07264v1
fatcat:mx2vyj6j3vhxplezy2fclffud4
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