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检索条件"机构=Human Language Technology and Pattern Recognition Computer Science"
230 条 记 录,以下是11-20 订阅
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Transformer-based direct hidden Markov model for machine translation  59
Transformer-based direct hidden Markov model for machine tra...
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2021 Student Research Workshop, SRW 2021 at the 59th Annual Meeting of the Association for Computational Linguistics and the 11th International Joint Conference on Natural language Processing, ACL-IJCNLP 2021
作者: Wang, Weiyue Yang, Zijian Gao, Yingbo Ney, Hermann Human Language Technology and Pattern Recognition Group Computer Science Department RWTH Aachen University Germany
The neural hidden Markov model has been proposed as an alternative to attention mechanism in machine translation with recurrent neural networks. However, since the introduction of the transformer models, its performan... 详细信息
来源: 评论
Advancements in reordering models for statistical machine translation
Advancements in reordering models for statistical machine tr...
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51st Annual Meeting of the Association for Computational Linguistics, ACL 2013
作者: Feng, Minwei Peter, Jan-Thorsten Ney, Hermann Human Language Technology and Pattern Recognition Computer Science Department RWTH Aachen University Aachen Germany
In this paper, we propose a novel reordering model based on sequence labeling techniques. Our model converts the reordering problem into a sequence labeling problem, i.e. a tagging task. Results on five Chinese-Englis... 详细信息
来源: 评论
The RWTH Aachen Machine Translation system for IWSLT 2010  7
The RWTH Aachen Machine Translation system for IWSLT 2010
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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 ... 详细信息
来源: 评论
Decipherment complexity in 1:1 substitution ciphers
Decipherment complexity in 1:1 substitution ciphers
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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
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 ... 详细信息
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Spoken language Translation Using Automatically Transcribed Text in Training  9
Spoken Language Translation Using Automatically Transcribed ...
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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 ... 详细信息
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Unsupervised adaptation for statistical machine translation  9
Unsupervised adaptation for statistical machine translation
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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
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 ... 详细信息
来源: 评论
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
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 trainin... 详细信息
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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
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 trainin... 详细信息
来源: 评论
Using morpheme and syllable based sub-words for polish LVCSR
Using morpheme and syllable based sub-words for polish LVCSR
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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
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 ch... 详细信息
来源: 评论
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-... 详细信息
来源: 评论