This paper describes the statistical machine translation (SMT) systems developed at RWTH Aachen University for the translation task of the NAACL 2012 Seventh Workshop on Statistical Machine Translation (WMT 2012). We ...
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Embedding and projection matrices are commonly used in neural language models (NLM) as well as in other sequence processing networks that operate on large vocabularies. We examine such matrices in fine-tuned language ...
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We investigate insertion and deletion models for hierarchical phrase-based statistical machine translation. Insertion and deletion models are designed as a means to avoid the omission of content words in the hypothese...
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This paper describes the statistical machine translation system developed at RWTH Aachen University for the English?German and German?English translation tasks of the EMNLP 2017 Second Conference on Machine Translatio...
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This paper describes the submission of RWTH Aachen University for the De→En parallel corpus filtering task of the EMNLP 2018 Third Conference on Machine Translation (WMT 2018). We use several rule-based, heuristic me...
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This work investigates the alignment problem in state-of-the-art multi-head attention models based on the transformer architecture. We demonstrate that alignment extraction in transformer models can be improved by aug...
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During the last few years, the statistical approach has found widespread use in machine translation, in particular for spoken language. In many comparative evaluations of automatic speech translation, the statistical ...
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During the last few years, the statistical approach has found widespread use in machine translation, in particular for spoken language. In many comparative evaluations of automatic speech translation, the statistical approach was found to be significantly superior to the existing conventional approaches. The paper will present the main components of a statistical machine translation system (such as alignment and lexicon models, training procedure, generation of the target sentence) and summarize the progress made so far. We will conclude with a roadmap for future research on spoken language translation.
Regardless of different word embedding and hidden layer structures of the neural architectures that are used in named entity recognition, a conditional random field layer is commonly used for the output. This work pro...
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Document-level context for neural machine translation (NMT) is crucial to improve the translation consistency and cohesion, the translation of ambiguous inputs, as well as several other linguistic phenomena. Many work...
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This work explores extending attention-based neural models to include alignment information as input. We modify the attention component to have dependence on the current source position. The attention model is then us...
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