Results 101 to 110 of about 4,300,436 (344)

Generalizing Back-Translation in Neural Machine Translation [PDF]

Proceedings of the Fourth Conference on Machine Translation (Volume 1: Research Papers), 2019
Published by Association for Computational Linguistics (ACL), Stroudsburg ...
Graça, Miguel M., Kim, Yunsu, Schamper, Julian, Khadivi, Shahram, Ney, Hermann   +4 more
openaire   +3 more sources

Targeted protein degradation in oncology: novel therapeutic opportunity for solid tumours?

Molecular Oncology, EarlyView.
Current anticancer therapies are limited by the occurrence of resistance and undruggability of most proteins. Targeted protein degraders are novel, promising agents that trigger the selective degradation of previously undruggable proteins through the recruitment of the ubiquitin–proteasome machinery. Their mechanism of action raises exciting challenges,
Noé Herbel, Sophie Postel‐Vinay
wiley   +1 more source

INTEGRATING MACHINE TRANSLATION AND SPEECH SYNTHESIS COMPONENT FOR ENGLISH TO DRAVIDIAN LANGUAGE SPEECH TO SPEECH TRANSLATION SYSTEM [PDF]

Journal of Engineering Science and Technology, 2015
This paper provides an interface between the machine translation and speech synthesis system for converting English speech to Tamil text in English to Tamil speech to speech translation system.
J. SANGEETHA, S. JOTHILAKSHMI
doaj  

Findings of the 2019 Conference on Machine Translation (WMT19) [PDF]

, 2019
This paper presents the results of the premier shared task organized alongside the Conference on Machine Translation (WMT) 2019. Participants were asked to build machine translation systems for any of 18 language pairs, to be evaluated on a test set of ...
Barrault, Loïc, Bojar, Ondřej, Costa-Jussà, Marta R., Federmann, Christian, Fishel, Mark, Graham, Yvette   +5 more
core  

Unsupervised Neural Machine Translation with SMT as Posterior Regularization

, 2019
Without real bilingual corpus available, unsupervised Neural Machine Translation (NMT) typically requires pseudo parallel data generated with the back-translation method for the model training. However, due to weak supervision, the pseudo data inevitably
Liu, Shujie, Ma, Shuai, Ren, Shuo, Zhang, Zhirui, Zhou, Ming   +4 more
core   +1 more source

Circulating tumor DNA monitoring and blood tumor mutational burden in patients with metastatic solid tumors treated with atezolizumab

Molecular Oncology, EarlyView.
In patients treated with atezolizumab as a part of the MyPathway (NCT02091141) trial, pre‐treatment ctDNA tumor fraction at high levels was associated with poor outcomes (radiographic response, progression‐free survival, and overall survival) but better sensitivity for blood tumor mutational burden (bTMB).
Charles Swanton, Russell W. Madison, Candice Francheska B. Tambaoan, Funda Meric‐Bernstam, Christopher J. Sweeney, Razelle Kurzrock, Howard A. Burris III, David R. Spigel, Hanna Tukachinsky, Jason Hughes, Julia Malato, Bongin Yoo, Tania Szado, Cheryl Schwab, Lincoln W. Pasquina, Amaya Gasco, Katja Schulze, Claire F. Friedman   +17 more
wiley   +1 more source

Development and validation of machine translation literacy scale for translation education

Australian Journal of Applied Linguistics
The rise of machine translation demands a fundamental shift in both translators’ roles and educational approaches. However, translation education research and practice have struggled to keep pace with the latest developments.
Junho Lee, Sowon Ahn, Yeong-Houn Yi
doaj   +1 more source

Unsupervised Statistical Machine Translation [PDF]

Proceedings of the 2018 Conference on Empirical Methods in Natural Language Processing, 2018
While modern machine translation has relied on large parallel corpora, a recent line of work has managed to train Neural Machine Translation (NMT) systems from monolingual corpora only (Artetxe et al., 2018c; Lample et al., 2018). Despite the potential of this approach for low-resource settings, existing systems are far behind their supervised ...
Artetxe Zurutuza, Mikel, Labaka Intxauspe, Gorka, Agirre Bengoa, Eneko   +2 more
openaire   +4 more sources

Unraveling LINE‐1 retrotransposition in head and neck squamous cell carcinoma

Molecular Oncology, EarlyView.
The novel RetroTest method allows the detection of L1 activation in clinical samples with low DNA input, providing global L1 activity and the identification of the L1 source element. We applied RetroTest to a real‐world cohort of HNSCC patients where we reported an early L1 activation, with more than 60% of T1 patients showing L1 activity.
Jenifer Brea‐Iglesias, Ana Oitabén, Sonia Zumalave, Bernardo Rodriguez‐Martin, María Gallardo‐Gómez, Martín Santamarina, Ana Pequeño‐Valtierra, Laura Juaneda‐Magdalena, Ramón García‐Escudero, José Luis López‐Cedrún, Máximo Fraga, José M. C. Tubio, Mónica Martínez‐Fernández   +12 more
wiley   +1 more source

Generative Neural Machine Translation [PDF]

, 2018
We introduce Generative Neural Machine Translation (GNMT), a latent variable architecture which is designed to model the semantics of the source and target sentences.
Barber, David, Shah, Harshil
core   +1 more source