Malte Nuhn


2015

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UNRAVELA Decipherment Toolkit
Malte Nuhn | Julian Schamper | Hermann Ney
Proceedings of the 53rd Annual Meeting of the Association for Computational Linguistics and the 7th International Joint Conference on Natural Language Processing (Volume 2: Short Papers)

2014

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Improved Decipherment of Homophonic Ciphers
Malte Nuhn | Julian Schamper | Hermann Ney
Proceedings of the 2014 Conference on Empirical Methods in Natural Language Processing (EMNLP)

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Cipher Type Detection
Malte Nuhn | Kevin Knight
Proceedings of the 2014 Conference on Empirical Methods in Natural Language Processing (EMNLP)

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EM Decipherment for Large Vocabularies
Malte Nuhn | Hermann Ney
Proceedings of the 52nd Annual Meeting of the Association for Computational Linguistics (Volume 2: Short Papers)

2013

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Decipherment Complexity in 1:1 Substitution Ciphers
Malte Nuhn | Hermann Ney
Proceedings of the 51st Annual Meeting of the Association for Computational Linguistics (Volume 1: Long Papers)

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Beam Search for Solving Substitution Ciphers
Malte Nuhn | Julian Schamper | Hermann Ney
Proceedings of the 51st Annual Meeting of the Association for Computational Linguistics (Volume 1: Long Papers)

2012

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The RWTH Aachen speech recognition and machine translation system for IWSLT 2012
Stephan Peitz | Saab Mansour | Markus Freitag | Minwei Feng | Matthias Huck | Joern Wuebker | Malte Nuhn | Markus Nußbaum-Thom | Hermann Ney
Proceedings of the 9th International Workshop on Spoken Language Translation: Evaluation Campaign

In this paper, the automatic speech recognition (ASR) and statistical machine translation (SMT) systems of RWTH Aachen University developed for the evaluation campaign of the International Workshop on Spoken Language Translation (IWSLT) 2012 are presented. We participated in the ASR (English), MT (English-French, Arabic-English, Chinese-English, German-English) and SLT (English-French) tracks. For the MT track both hierarchical and phrase-based SMT decoders are applied. A number of different techniques are evaluated in the MT and SLT tracks, including domain adaptation via data selection, translation model interpolation, phrase training for hierarchical and phrase-based systems, additional reordering model, word class language model, various Arabic and Chinese segmentation methods, postprocessing of speech recognition output with an SMT system, and system combination. By application of these methods we can show considerable improvements over the respective baseline systems.

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Jane 2: Open Source Phrase-based and Hierarchical Statistical Machine Translation
Joern Wuebker | Matthias Huck | Stephan Peitz | Malte Nuhn | Markus Freitag | Jan-Thorsten Peter | Saab Mansour | Hermann Ney
Proceedings of COLING 2012: Demonstration Papers

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The RWTH Aachen Machine Translation System for WMT 2012
Matthias Huck | Stephan Peitz | Markus Freitag | Malte Nuhn | Hermann Ney
Proceedings of the Seventh Workshop on Statistical Machine Translation

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Deciphering Foreign Language by Combining Language Models and Context Vectors
Malte Nuhn | Arne Mauser | Hermann Ney
Proceedings of the 50th Annual Meeting of the Association for Computational Linguistics (Volume 1: Long Papers)