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Inferring translation candidates for multilingual dictionary generation with multi-way neural machine translation

Arcan, Mihael, ; Torregrosa, Daniel Ahmadi, ; Sina McCrae, John P.,
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

Daniel Torregrosa, Mihael Arcan, Sina Ahmadi, John P. McCrae
2019 Zenodo  
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

Mihael Arcan, Daniel Torregrosa, Sina Ahmadi, John P. McCrae
2019 Zenodo  
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]

Ruipeng Jia, Xingxing Zhang, Yanan Cao, Shi Wang, Zheng Lin, Furu Wei
2022 arXiv   pre-print
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

Jorge Gracia, Besim Kabashi, Ilan Kernerman, Marta Lanau-Coronas, Dorielle Lonke
2019 Zenodo  
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]

Tianchi Bi and Liang Yao and Baosong Yang and Haibo Zhang and Weihua Luo and Boxing Chen
2020 arXiv   pre-print
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

Kathrin Donandt, Christian Chiarcos
2019 Zenodo  
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]

Samson Tan, Shafiq Joty
2021 arXiv   pre-print
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]

Dorothy Kenny
2022 Zenodo  
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

Erkut Erdem, Menekse Kuyu, Semih Yagcioglu, Anette Frank, Letitia Parcalabescu, Barbara Plank, Andrii Babii, Oleksii Turuta, Aykut Erdem, Iacer Calixto, Elena Lloret, Elena-Simona Apostol (+6 others)
2022 The Journal of Artificial Intelligence Research  
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]

Yerai Doval, Jose Camacho-Collados, Luis Espinosa-Anke, Steven Schockaert
2020 arXiv   pre-print
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]

Francis Grégoire, Philippe Langlais
2017 arXiv   pre-print
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]

Surangika Ranathunga, En-Shiun Annie Lee, Marjana Prifti Skenduli, Ravi Shekhar, Mehreen Alam, Rishemjit Kaur
2021 arXiv   pre-print
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]

Zehui Lin, Xiao Pan, Mingxuan Wang, Xipeng Qiu, Jiangtao Feng, Hao Zhou, Lei Li
2021 arXiv   pre-print
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]

Alexandre Magueresse, Vincent Carles, Evan Heetderks
2020 arXiv   pre-print
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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