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| 41 |
Linguistic Mathematical Relationships Saved or Lost in Translating Texts: Extension of the Statistical Theory of Translation and Its Application to the New Testament
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In: Information; Volume 13; Issue 1; Pages: 20 (2022)
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| 42 |
Sign Language Avatars: A Question of Representation
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In: Information; Volume 13; Issue 4; Pages: 206 (2022)
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| 43 |
Identifying Source-Language Dialects in Translation
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In: Mathematics; Volume 10; Issue 9; Pages: 1431 (2022)
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| 44 |
Leveraging Frozen Pretrained Written Language Models for Neural Sign Language Translation
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In: Information; Volume 13; Issue 5; Pages: 220 (2022)
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| 45 |
X-Transformer: A Machine Translation Model Enhanced by the Self-Attention Mechanism
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In: Applied Sciences; Volume 12; Issue 9; Pages: 4502 (2022)
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| 46 |
Retrieval-Based Transformer Pseudocode Generation
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In: Mathematics; Volume 10; Issue 4; Pages: 604 (2022)
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| 47 |
Evaluating the Impact of Integrating Similar Translations into Neural Machine Translation
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In: Information; Volume 13; Issue 1; Pages: 19 (2022)
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| 48 |
Hebrew Transformed: Machine Translation of Hebrew Using the Transformer Architecture
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Abstract:
This thesis presents the first known end-to-end application to Hebrew language of Google’s state-of-the-art Transformer architecture for natural language processing (NLP). The state of the art in machine translation (MT) of Hebrew remains poor. Scholarly work in MT, deep learning (DL), and other areas of NLP for Hebrew began to develop much later and remains much less mature than for other languages. The problem is difficult because of the nature of Hebrew as a morphologically-rich language (MRL), the small size of the total corpus of electronic Hebrew documents available as training material, and the small size of the Hebrew-literate computing community worldwide. Nonetheless, significant advances in Hebrew NLP tools, data, methods, and scholarly infrastructure over the last 15 years, combined with recent advances in general NLP and MT over the last few years, especially the rise of neural networks and deep learning, create an enticing opportunity to attempt to advance the current state of Hebrew MT. More specifically, Google’s Transformer neural network and associated technologies such as bidirectional encoder representations from Transformers (BERT) have revolutionized general MT and hold great promise for improving automatic Hebrew translation. This thesis demonstrates that, as measured by METEOR scores, a basic Hebrew Transformer trained in a few hours on a single GPU (graphics processing unit) exceeds the current performance of Google Translate on in-genre Hebrew translation tasks and is not far behind Google Translate on Hebrew translation tasks in general.
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Keyword:
Artificial intelligence; bidirectional encoder representations from transformers (BERT); computational linguistics; Computer science; hebrew; Linguistics; machine translation; natural language processing (NLP); transformer
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URL: https://nrs.harvard.edu/URN-3:HUL.INSTREPOS:37370749
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| 49 |
Technology in audiovisual translation practices and training ; Las tecnologías en la formación y las prácticas de traducción audiovisual
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In: CLINA Revista Interdisciplinaria de Traducción Interpretación y Comunicación Intercultural; Vol. 7 Núm. 1 (2021); 17-24 ; CLINA Revista Interdisciplinaria de Traducción Interpretación y Comunicación Intercultural; Vol. 7 No. 1 (2021); 17-24 ; 2444-1961 ; 10.14201/clina202171 (2022)
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| 50 |
Training in machine translation post-editing for foreign language students
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Zhang, Hong; Torres-Hostench, Olga. - : University of Hawaii National Foreign Language Resource Center, 2022. : Center for Language & Technology, 2022. : (co-sponsored by Center for Open Educational Resources and Language Learning, University of Texas at Austin), 2022
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| 51 |
Pushing the right buttons: adversarial evaluation of quality estimation
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In: Proceedings of the Sixth Conference on Machine Translation ; 625 ; 638 (2022)
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| 52 |
Some Contributions to Interactive Machine Translation and to the Applications of Machine Translation for Historical Documents
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| 53 |
Neural-based Knowledge Transfer in Natural Language Processing
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| 54 |
Machine Translation of polysemic words: current technology in light of Cognitive Linguistics ; Tradução automática de palavras polissêmicas: tecnologias atuais à luz da Linguística Cognitiva
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In: Entrepalavras; v. 11, n. 3 (11): Linguagem e Tecnologia; 52-74 (2022)
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| 55 |
The role of machine translation in translation education: A thematic analysis of translator educators’ beliefs
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In: Translation and Interpreting : the International Journal of Translation and Interpreting Research, Vol 14, Iss 1, Pp 177-197 (2022) (2022)
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| 56 |
Predicting and Critiquing Machine Virtuosity: Mawwal Accompaniment as Case Study
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In: International Computer Music Conference ; https://hal.archives-ouvertes.fr/hal-03044066 ; International Computer Music Conference, Jul 2021, Santiago, Chile (2021)
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| 57 |
Investigating alignment interpretability for low-resource NMT
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In: ISSN: 0922-6567 ; EISSN: 1573-0573 ; Machine Translation ; https://hal.archives-ouvertes.fr/hal-03139744 ; Machine Translation, Springer Verlag, 2021, ⟨10.1007/s10590-020-09254-w⟩ (2021)
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| 58 |
Parallel Corpora Preparation for English-Amharic Machine Translation
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In: IWANN 2021 - International Work on Artificial Neural Networks, Conference Springer LNCS proceedings ; https://hal.inria.fr/hal-03272258 ; IWANN 2021 - International Work on Artificial Neural Networks, Conference Springer LNCS proceedings, Jun 2021, Online, Spain (2021)
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| 59 |
DESIGNING TO SUPPORT SENSEMAKING IN CROSS-LINGUAL COMPUTER-MEDIATED COMMUNICATION USING NLP TECHNIQUES
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| 60 |
DELA Corpus - A Document-Level Corpus Annotated with Context-Related Issues
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In: Castilho, Sheila orcid:0000-0002-8416-6555 , Cavalheiro Camargo, João Lucas orcid:0000-0003-3746-1225 , Menezes, Miguel and Way, Andy orcid:0000-0001-5736-5930 (2021) DELA Corpus - A Document-Level Corpus Annotated with Context-Related Issues. In: Sixth Conference on Machine Translation (WMT21), 10-11 Nov 2021, Punta Cana, Dominican Republic (Online). ISBN 978-1-954085-94-7 (2021)
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