Results 91 to 100 of about 594,786 (216)

Neural Network Machine Translation Method Based on Unsupervised Domain Adaptation

Complexity, 2020
Relying on large-scale parallel corpora, neural machine translation has achieved great success in certain language pairs. However, the acquisition of high-quality parallel corpus is one of the main difficulties in machine translation research.
Rui Wang
doaj   +1 more source

Combining data-driven MT systems for improved sign language translation [PDF]

, 2007
In this paper, we investigate the feasibility of combining two data-driven machine translation (MT) systems for the translation of sign languages (SLs).
Bungeroth, Jan, Morrissey, Sara, Ney, Hermann, Stein, Daniel, Way, Andy   +4 more
core  

Statistical Machine Translation Features with Multitask Tensor Networks

, 2015
We present a three-pronged approach to improving Statistical Machine Translation (SMT), building on recent success in the application of neural networks to SMT.
Devlin, Jacob, Huang, Zhongqiang, Lamar, Thomas, Makhoul, John, Schwartz, Richard, Setiawan, Hendra, Zbib, Rabih   +6 more
core   +1 more source

Promoting Flexible Translations in Statistical Machine Translation

, 2013
While SMT systems can learn to translate multiword expressions (MWEs) from parallel text, they typically have no notion of non-compositionality, and thus overgeneralise translations that are only used in certain contexts. This paper describes a novel approach to measure the flexibility of a phrase pair, i.e.
openaire   +2 more sources

Controlled beam search for neural machine translation using subword units leveraging phrase-based statistical machine translation outputs

Discover Computing
The decoding phase is a crucial component in machine translation systems, alongside the creation of the model. Beam search is the most commonly used algorithm for decoding in these systems.
Emre Satir, Hasan Bulut
doaj   +1 more source

Comparison of SYSTRAN and Google Translate for English→Portuguese

Revista Tradumàtica, 2011
Two machine translation (MT) systems, a statistical MT (SMT) system and a hybrid system (rule-based and SMT) were tested in order to compare various MT performances. The source language was English (EN) and the target language Portuguese (PT).
Rodrigo Gomes de Oliveira, Dimitra Anastasiou   +1 more
doaj   +1 more source

Using Cross-Lingual Explicit Semantic Analysis for Improving Ontology Translation [PDF]

, 2012
Semantic Web aims to allow machines to make inferences using the explicit conceptualisations contained in ontologies. By pointing to ontologies, Semantic Web-based applications are able to inter-operate and share common information easily.
Aggarwal, Nitish, Asooja, Kartik, Gracia, Jorge, Gómez-Pérez, A.   +3 more
core   +2 more sources

Pushdown Automata in Statistical Machine Translation

Computational Linguistics, 2023
Cyril Allauzen, Bill Byrne, Adrià de Gispert, Gonzalo Iglesias, Michael Riley   +4 more
doaj   +1 more source

Application of translation technology based on AI in translation teaching

Systems and Soft Computing
Nowadays, translation technology based on artificial intelligence (AI) has gradually matured. Traditional translation teaching methods have many limitations, such as time and space limitations, increased labor costs, etc.
Yu Yuxiu
doaj   +1 more source

Why Translation Is Difficult: A Corpus-Based Study of Non-Literality in Post-Editing and From-Scratch Translation

Hermes, 2017
The paper develops a definition of translation literality that is based on the syntactic and semantic similarity of the source and the target texts. We provide theoretical and empirical evidence that absolute literal translations are easy to produce ...
Michael Carl, Moritz Jonas Schaeffer
doaj   +1 more source