Richard Zens


2018

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Content Explorer: Recommending Novel Entities for a Document Writer
Michal Lukasik | Richard Zens
Proceedings of the 2018 Conference on Empirical Methods in Natural Language Processing

Background research is an essential part of document writing. Search engines are great for retrieving information once we know what to look for. However, the bigger challenge is often identifying topics for further research. Automated tools could help significantly in this discovery process and increase the productivity of the writer. In this paper, we formulate the problem of recommending topics to a writer. We consider this as a supervised learning problem and run a user study to validate this approach. We propose an evaluation metric and perform an empirical comparison of state-of-the-art models for extreme multi-label classification on a large data set. We demonstrate how a simple modification of the cross-entropy loss function leads to improved results of the deep learning models.

2012

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Fast and Scalable Decoding with Language Model Look-Ahead for Phrase-based Statistical Machine Translation
Joern Wuebker | Hermann Ney | Richard Zens
Proceedings of the 50th Annual Meeting of the Association for Computational Linguistics (Volume 2: Short Papers)

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A Systematic Comparison of Phrase Table Pruning Techniques
Richard Zens | Daisy Stanton | Peng Xu
Proceedings of the 2012 Joint Conference on Empirical Methods in Natural Language Processing and Computational Natural Language Learning

2008

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Improvements in dynamic programming beam search for phrase-based statistical machine translation.
Richard Zens | Hermann Ney
Proceedings of the 5th International Workshop on Spoken Language Translation: Papers

Search is a central component of any statistical machine translation system. We describe the search for phrase-based SMT in detail and show its importance for achieving good translation quality. We introduce an explicit distinction between reordering and lexical hypotheses and organize the pruning accordingly. We show that for the large Chinese-English NIST task already a small number of lexical alternatives is sufficient, whereas a large number of reordering hypotheses is required to achieve good translation quality. The resulting system compares favorably with the current stateof-the-art, in particular we perform a comparison with cube pruning as well as with Moses.

2007

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Minimum Bayes Risk Decoding for BLEU
Nicola Ehling | Richard Zens | Hermann Ney
Proceedings of the 45th Annual Meeting of the Association for Computational Linguistics Companion Volume Proceedings of the Demo and Poster Sessions

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Moses: Open Source Toolkit for Statistical Machine Translation
Philipp Koehn | Hieu Hoang | Alexandra Birch | Chris Callison-Burch | Marcello Federico | Nicola Bertoldi | Brooke Cowan | Wade Shen | Christine Moran | Richard Zens | Chris Dyer | Ondřej Bojar | Alexandra Constantin | Evan Herbst
Proceedings of the 45th Annual Meeting of the Association for Computational Linguistics Companion Volume Proceedings of the Demo and Poster Sessions

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Efficient Phrase-Table Representation for Machine Translation with Applications to Online MT and Speech Translation
Richard Zens | Hermann Ney
Human Language Technologies 2007: The Conference of the North American Chapter of the Association for Computational Linguistics; Proceedings of the Main Conference

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Are Very Large N-Best Lists Useful for SMT?
Saša Hasan | Richard Zens | Hermann Ney
Human Language Technologies 2007: The Conference of the North American Chapter of the Association for Computational Linguistics; Companion Volume, Short Papers

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A Systematic Comparison of Training Criteria for Statistical Machine Translation
Richard Zens | Saša Hasan | Hermann Ney
Proceedings of the 2007 Joint Conference on Empirical Methods in Natural Language Processing and Computational Natural Language Learning (EMNLP-CoNLL)

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Chunk-Level Reordering of Source Language Sentences with Automatically Learned Rules for Statistical Machine Translation
Yuqi Zhang | Richard Zens | Hermann Ney
Proceedings of SSST, NAACL-HLT 2007 / AMTA Workshop on Syntax and Structure in Statistical Translation

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Improved chunk-level reordering for statistical machine translation
Yuqi Zhang | Richard Zens | Hermann Ney
Proceedings of the Fourth International Workshop on Spoken Language Translation

Inspired by previous chunk-level reordering approaches to statistical machine translation, this paper presents two methods to improve the reordering at the chunk level. By introducing a new lattice weighting factor and by reordering the training source data, an improvement is reported on TER and BLEU. Compared to the previous chunklevel reordering approach, the BLEU score improves 1.4% absolutely. The translation results are reported on IWSLT Chinese-English task.

2006

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The JHU workshop 2006 IWSLT system
Wade Shen | Richard Zens | Nicola Bertoldi | Marcello Federico
Proceedings of the Third International Workshop on Spoken Language Translation: Evaluation Campaign

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The RWTH statistical machine translation system for the IWSLT 2006 evaluation
Arne Mauser | Richard Zens | Evgeny Matusov | Sasa Hasan | Hermann Ney
Proceedings of the Third International Workshop on Spoken Language Translation: Evaluation Campaign

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A Flexible Architecture for CAT Applications
Saša Hasan | Shahram Khadivi | Richard Zens | Hermann Ney
Proceedings of the 11th Annual conference of the European Association for Machine Translation

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Integration of Speech to Computer-Assisted Translation Using Finite-State Automata
Shahram Khadivi | Richard Zens | Hermann Ney
Proceedings of the COLING/ACL 2006 Main Conference Poster Sessions

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Discriminative Reordering Models for Statistical Machine Translation
Richard Zens | Hermann Ney
Proceedings on the Workshop on Statistical Machine Translation

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N-Gram Posterior Probabilities for Statistical Machine Translation
Richard Zens | Hermann Ney
Proceedings on the Workshop on Statistical Machine Translation

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Partitioning Parallel Documents Using Binary Segmentation
Jia Xu | Richard Zens | Hermann Ney
Proceedings on the Workshop on Statistical Machine Translation

2005

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Statistical Machine Translation of European Parliamentary Speeches
David Vilar | Evgeny Matusov | Sasa Hasan | Richard Zens | Hermann Ney
Proceedings of Machine Translation Summit X: Papers

In this paper we present the ongoing work at RWTH Aachen University for building a speech-to-speech translation system within the TC-Star project. The corpus we work on consists of parliamentary speeches held in the European Plenary Sessions. To our knowledge, this is the first project that focuses on speech-to-speech translation applied to a real-life task. We describe the statistical approach used in the development of our system and analyze its performance under different conditions: dealing with syntactically correct input, dealing with the exact transcription of speech and dealing with the (noisy) output of an automatic speech recognition system. Experimental results show that our system is able to perform adequately in each of these conditions.

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Integrated Chinese Word Segmentation in Statistical Machine Translation
Jia Xu | Evgeny Matusov | Richard Zens | Hermann Ney
Proceedings of the Second International Workshop on Spoken Language Translation

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The RWTH Phrase-based Statistical Machine Translation System
Richard Zens | Oliver Bender | Sasa Hasan | Shahram Khadivi | Evgeny Matusov | Jia Xu | Yuqi Zhang | Hermann Ney
Proceedings of the Second International Workshop on Spoken Language Translation

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Comparison of generation strategies for interactive machine translation
Oliver Bender | Saša Hasan | David Vilar | Richard Zens | Hermann Ney
Proceedings of the 10th EAMT Conference: Practical applications of machine translation

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Sentence segmentation using IBM word alignment model 1
Jia Xu | Richard Zens | Hermann Ney
Proceedings of the 10th EAMT Conference: Practical applications of machine translation

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Novel Reordering Approaches in Phrase-Based Statistical Machine Translation
Stephan Kanthak | David Vilar | Evgeny Matusov | Richard Zens | Hermann Ney
Proceedings of the ACL Workshop on Building and Using Parallel Texts

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Word Graphs for Statistical Machine Translation
Richard Zens | Hermann Ney
Proceedings of the ACL Workshop on Building and Using Parallel Texts

2004

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Do We Need Chinese Word Segmentation for Statistical Machine Translation?
Jia Xu | Richard Zens | Hermann Ney
Proceedings of the Third SIGHAN Workshop on Chinese Language Processing

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Alignment templates: the RWTH SMT system
Oliver Bender | Richard Zens | Evgeny Matusov | Hermann Ney
Proceedings of the First International Workshop on Spoken Language Translation: Evaluation Campaign

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Statistical machine translation of spontaneous speech with scarce resources
Evgeny Matusov | Maja Popovic | Richard Zens | Hermann Ney
Proceedings of the First International Workshop on Spoken Language Translation: Papers

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Improved Word Alignment Using a Symmetric Lexicon Model
Richard Zens | Evgeny Matusov | Hermann Ney
COLING 2004: Proceedings of the 20th International Conference on Computational Linguistics

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Reordering Constraints for Phrase-Based Statistical Machine Translation
Richard Zens | Hermann Ney | Taro Watanabe | Eiichiro Sumita
COLING 2004: Proceedings of the 20th International Conference on Computational Linguistics

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Symmetric Word Alignments for Statistical Machine Translation
Evgeny Matusov | Richard Zens | Hermann Ney
COLING 2004: Proceedings of the 20th International Conference on Computational Linguistics

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Improvements in Phrase-Based Statistical Machine Translation
Richard Zens | Hermann Ney
Proceedings of the Human Language Technology Conference of the North American Chapter of the Association for Computational Linguistics: HLT-NAACL 2004

2003

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Efficient Search for Interactive Statistical Machine Translation
Franz Josef Och | Richard Zens | Hermann Ney
10th Conference of the European Chapter of the Association for Computational Linguistics

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A Comparative Study on Reordering Constraints in Statistical Machine Translation
Richard Zens | Hermann Ney
Proceedings of the 41st Annual Meeting of the Association for Computational Linguistics