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The RWTH Aachen Machine Translation system for IWSLT 2010 7

The RWTH Aachen Machine Translation system for IWSLT 2010

引用

7th International Workshop on Spoken language Translation, IWSLT 2010

作者： Mansour, Saab Peitz, Stephan Vilar, David Wuebker, Joern Ney, Hermann Human Language Technology and Pattern Recognition Computer Science Department RWTH Aachen University Aachen Germany

In this paper we describe the statistical machine translation system of the RWTH Aachen University developed for the translation task of the IWSLT 2010. This year, we participated in the BTEC translation task for the Arabic to English language direction. We experimented with two state-of-the-art decoders: phrase-based and hierarchical-based decoders. Extensions to the decoders included phrase training (as opposed to heuristic phrase extraction) for the phrase-based decoder, and soft syntactic features for the hierarchical decoder. Additionally, we experimented with various rule-based and statistical-based segmenters for Arabic. Due to the different decoders and the different methodologies that we apply for segmentation, we expect that there will be complimentary variation in the results achieved by each system. The next step would be to exploit these variations and achieve better results by combining the systems. We try different strategies for system combination and report significant improvements over the best single system. © IWSLT 2010. All rights reserved.

关键词： Computational linguistics

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Decipherment complexity in 1:1 substitution ciphers

Decipherment complexity in 1:1 substitution ciphers

引用

51st Annual Meeting of the Association for Computational Linguistics, ACL 2013

作者： Nuhn, Malte Ney, Hermann Human Language Technology and Pattern Recognition Computer Science Department RWTH Aachen University Aachen Germany

ISBN: (纸本)9781937284503

In this paper we show that even for the case of 1:1 substitution ciphers-which encipher plaintext symbols by exchanging them with a unique substitute-finding the optimal decipherment with respect to a bigram language model is NP-hard. We show that in this case the decipherment problem is equivalent to the quadratic assignment problem (QAP). To the best of our knowledge, this connection between the QAP and the decipherment problem has not been known in the literature before. © 2013 Association for Computational Linguistics.

关键词： Combinatorial optimization

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Unsupervised adaptation for statistical machine translation 9

Unsupervised adaptation for statistical machine translation

引用

9th Workshop on Statistical Machine Translation, WMT 2014 at the 52nd Conference of the Associationfor Computational Linguistics, ACL 2014

作者： Mansour, Saab Ney, Hermann Human Language Technology and Pattern Recognition Computer Science Department RWTH Aachen University Aachen Germany

ISBN: (纸本)9781941643174

In this work, we tackle the problem of language and translation models domainadaptation without explicit bilingual indomain training data. In such a scenario, the only information about the domain can be induced from the source-language test corpus. We explore unsupervised adaptation, where the source-language test corpus is combined with the corresponding hypotheses generated by the translation system to perform adaptation. We compare unsupervised adaptation to supervised and pseudo supervised adaptation. Our results show that the choice of the adaptation (target) set is crucial for successful application of adaptation methods. Evaluation is conducted over the German-To-English WMT newswire translation task. The experiments show that the unsupervised adaptation method generates the best translation quality as well as generalizes well to unseen test sets. © Proceedings of the Annual Meeting of the Association for Computational Linguistics 2014.

关键词： Machine translation

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Spoken language Translation Using Automatically Transcribed Text in Training 9

Spoken Language Translation Using Automatically Transcribed ...

引用

9th International Workshop on Spoken language Translation, IWSLT 2012

作者： Peitz, Stephan Wiesler, Simon Nußbaum-Thom, Markus Ney, Hermann Human Language Technology and Pattern Recognition Computer Science Department RWTH Aachen University Aachen Germany

In spoken language translation a machine translation system takes speech as input and translates it into another language. A standard machine translation system is trained on written language data and expects written language as input. In this paper we propose an approach to close the gap between the output of automatic speech recognition and the input of machine translation by training the translation system on automatically transcribed speech. In our experiments we show improvements of up to 0.9 BLEU points on the IWSLT 2012 English-to-French speech translation task. © IWSLT 2012. All rights reserved.

关键词： Speech recognition

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Phrase training based adaptation for statistical machine translation

Phrase training based adaptation for statistical machine tra...

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2013 Conference of the North American Chapter of the Association for Computational Linguistics: human language Technologies, NAACL HLT 2013

作者： Mansour, Saab Ney, Hermann Human Language Technology and Pattern Recognition Computer Science Department RWTH Aachen University Aachen Germany

ISBN: (纸本)9781937284473

We present a novel approach for translation model (TM) adaptation using phrase training. The proposed adaptation procedure is initialized with a standard general-domain TM, which is then used to perform phrase training on a smaller in-domain set. This way, we bias the probabilities of the general TM towards the in-domain distribution. Experimental results on two different lectures translation tasks show significant improvements of the adapted systems over the general ones. Additionally, we compare our results to mixture modeling, where we report gains when using the suggested phrase training adaptation method. © 2013 Association for Computational Linguistics.

关键词： Probability distributions

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Phrase Training Based Adaptation for Statistical Machine Translation 2

Phrase Training Based Adaptation for Statistical Machine Tra...

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2nd Workshop on Computational Linguistics for Literature, CLfL 2013 at the 2013 Conference of the North American Chapter of the Association for Computational Linguistics: human language Technologies, NAACL-HLT 2013

作者： Mansour, Saab Ney, Hermann Human Language Technology and Pattern Recognition Computer Science Department RWTH Aachen University Aachen Germany

ISBN: (纸本)9781937284473

关键词： Probability distributions

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Investigation of mixture splitting concept for training linear bottlenecks of deep neural network acoustic models 40

Investigation of mixture splitting concept for training line...

引用

40th IEEE International Conference on Acoustics, Speech, and Signal Processing, ICASSP 2015

作者： Tahir, Muhammad Ali Wiesler, Simon Schluter, Ralf Ney, Hermann Human Language Technology and Pattern Recognition Computer Science Department RWTH Aachen University Germany Spoken Language Processing Group LIMSI CNRS Paris France

ISBN: (纸本)9781467369978

A Gaussian or log-linear mixture model trained by maximum likelihood may be trained further using discriminative training. It is desirable that the mixture splitting is also done during the discriminative training, to achieve better mixture density distribution. In previous work such a discriminative splitting approach was presented. Similarly, the resolution of a deep neural network may also be increased by splitting. In this paper, discriminative splitting is applied as a way of initializing a linear bottleneck between two layers of a DNN. Experiments for a single hidden layer and six hidden layer cases show the potential of this approach as an alternative method of pre-training for linear bottlenecks for MLP hidden layers. © 2015 IEEE.

关键词： deep neural network linear bottleneck mixture splitting

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Using morpheme and syllable based sub-words for polish LVCSR

Using morpheme and syllable based sub-words for polish LVCSR

引用

36th IEEE International Conference on Acoustics, Speech, and Signal Processing, ICASSP 2011

作者： Shaik, M. Ali Basha El-Desoky Mousa, Amr Schlüter, Ralf Ney, Hermann Human Language Technology and Pattern Recognition - Computer Science Department RWTH Aachen University 52056 Aachen Germany

ISBN: (纸本)9781457705397

Polish is a synthetic language with a high morpheme-per-word ratio. It makes use of a high degree of inflection leading to high out-of-vocabulary (OOV) rates, and high language Model (LM) perplexities. This poses a challenge for Large Vocabulary and Continuous Speech recognition (LVCSR) systems. Here, the use of morpheme and syllable based units is investigated for building sub-lexical LMs. A different type of sub-lexical units is proposed based on combining morphemic or syllabic units with corresponding pronunciations. Thereby, a set of grapheme-phoneme pairs called graphones are used for building LMs. A relative reduction of 3.5% in Word Error Rate (WER) is obtained with respect to a traditional system based on full-words. © 2011 IEEE.

关键词： Continuous speech recognition

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Hierarchical Hybrid language models for Open Vocabulary Continuous Speech recognition using WFST

Hierarchical Hybrid Language models for Open Vocabulary Cont...

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2012 SAPA-SCALE Conference

作者： Shaik, M. Ali Basha Rybach, David Hahn, Stefan Schlüter, Ralf Ney, Hermann Human Language Technology and Pattern Recognition Computer Science Department RWTH Aachen University Aachen52056 Germany

One of the main challenges in automatic speech recognition is recognizing an open, partly unseen vocabulary. To implicitly reduce the out-of-vocabulary (OOV) rate, hybrid vocabularies consisting of full-words and sub-words are used. Nevertheless, when using sub-words, OOV rates are not necessarily zero. In this work, we propose the use of separate character level graphones (orthography and phoneme sequence pair) as sub-words to effectively obtain zero OOV rate. To minimize negative effects on the core vocabulary of the most frequent words, a hierarchical language modeling approach is proposed. We augment the first level hybrid language model with an OOV word class, which is replaced by character level graphone sequences using a second-level graphone based character language and acoustic model during search. This approach is realized on-the-fly using weighted finite state transducers. We recognize a significant fraction of OOVs on the Wall Street Journal corpus, compared to the full-word and former hybrid language model based approaches. © SAPA-SCALE 2012. All rights reserved.

关键词： Modeling languages

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Towards a Better Evaluation of Metrics for Machine Translation 5

Towards a Better Evaluation of Metrics for Machine Translati...

引用

5th Conference on Machine Translation, WMT 2020

作者： Stanchev, Peter Wang, Weiyue Ney, Hermann Human Language Technology and Pattern Recognition Computer Science Department RWTH Aachen University Aachen52056 Germany

ISBN: (纸本)9781948087810

An important aspect of machine translation is its evaluation, which can be achieved through the use of a variety of metrics. To compare these metrics, the workshop on statistical machine translation annually evaluates metrics based on their correlation with human judgement. Over the years, methods for measuring correlation with humans have changed, but little research has been performed on what the optimal methods for acquiring human scores are and how human correlation can be measured. In this work, the methods for evaluating metrics at both system- and segment-level are analyzed in detail and their shortcomings are pointed out. © 2020 Association for Computational Linguistics

关键词： Machine translation

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