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检索条件"机构=Human Language Technology and Pattern Recognition Group Computer Science Department"
237 条 记 录,以下是81-90 订阅
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Efficient phrase-table representation for machine translation with applications to online MT and speech translation
Efficient phrase-table representation for machine translatio...
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human language Technologies 2007: The Conference of the North American Chapter of the Association for Computational Linguistics, NAACL HLT 2007
作者: Zens, Richard Ney, Hermann Human Language Technology and Pattern Recognition Lehrstuhl für Informatik 6 - Computer Science Department RWTH Aachen University D-52056 Aachen Germany
In phrase-based statistical machine translation, the phrase-table requires a large amount of memory. We will present an efficient representation with two key properties: on-demand loading and a prefix tree structure f... 详细信息
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Minimum bayes risk decoding for BLEU  45
Minimum bayes risk decoding for BLEU
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45th Annual Meeting of the Association for Computational Linguistics, ACL 2007
作者: Ehling, Nicola Zens, Richard Ney, Hermann Human Language Technology and Pattern Recognition Lehrstuhl für Informatik 6 Computer Science Department RWTH Aachen University AachenD-52056 Germany
We present a Minimum Bayes Risk (MBR) decoder for statistical machine translation. The approach aims to minimize the expected loss of translation errors with regard to the BLEU score. We show that MBR decoding on N-be... 详细信息
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The RWTH Machine Translation System for IWSLT 2007  4
The RWTH Machine Translation System for IWSLT 2007
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4th International Workshop on Spoken language Translation, IWSLT 2007
作者: Mauser, Arne Vilar, David Leusch, Gregor Zhang, Yuqi Ney, Hermann Human Language Technology and Pattern Recognition Lehrstuhl für Informatik 6 Computer Science Department RWTH Aachen University AachenD-52056 Germany
The RWTH system for the IWSLT 2007 evaluation is a combination of several statistical machine translation systems. The combination includes Phrase-Based models, a n-gram translation model and a hierarchical phrase mod... 详细信息
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Discriminative reordering models for statistical machine translation
Discriminative reordering models for statistical machine tra...
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2006 Workshop on Statistical Machine Translation, WMT 2006, collocated with the HLT-NAACL 2006
作者: Zens, Richard Ney, Hermann Human Language Technology and Pattern Recognition Lehrstuhl für Informatik 6 Computer Science Department RWTH Aachen University AachenD-52056 Germany
We present discriminative reordering models for phrase-based statistical machine translation. The models are trained using the maximum entropy principle. We use several types of features: based on words, based on word... 详细信息
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Are unaligned words important for machine translation?
Are unaligned words important for machine translation?
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13th Annual Conference of the European Association for Machine Translation, EAMT 2009
作者: Zhang, Yuqi Matusov, Evgeny Ney, Hermann Human Language Technology and Pattern Recognition Lehrstuhl für Informatik 6 - Computer Science Department RWTH Aachen University D-52056 Aachen Germany
In this paper, we deal with the problem of a large number of unaligned words in automatically learned word alignments for machine translation (MT). These unaligned words are the reason for ambiguous phrase pairs extra... 详细信息
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Robust Knowledge Distillation from RNN-T Models with Noisy Training Labels Using Full-Sum Loss  48
Robust Knowledge Distillation from RNN-T Models with Noisy T...
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48th IEEE International Conference on Acoustics, Speech and Signal Processing, ICASSP 2023
作者: Zeineldeen, Mohammad Audhkhasi, Kartik Baskar, Murali Karthick Ramabhadran, Bhuvana Rwth Aachen University Human Language Technology and Pattern Recognition Computer Science Department Aachen52074 Germany Google Llc New York United States
This work studies knowledge distillation (KD) and addresses its constraints for recurrent neural network transducer (RNN-T) models. In hard distillation, a teacher model transcribes large amounts of unlabelled speech ... 详细信息
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Unsupervised adaptation of a denoising autoencoder by Bayesian Feature Enhancement for reverberant asr under mismatch conditions  40
Unsupervised adaptation of a denoising autoencoder by Bayesi...
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40th IEEE International Conference on Acoustics, Speech, and Signal Processing, ICASSP 2015
作者: Heymann, Jahn Haeb-Umbach, Reinhold Golik, Pavel Schluter, Ralf University of Paderborn Department of Communications Engineering Paderborn Germany RWTH Aachen University Human Language Technology and Pattern Recognition Computer Science Department Aachen Aachen Germany
The parametric Bayesian Feature Enhancement (BFE) and a datadriven Denoising Autoencoder (DA) both bring performance gains in severe single-channel speech recognition conditions. The first can be adjusted to different... 详细信息
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The RWTH Phrase-based Statistical Machine Translation System  2
The RWTH Phrase-based Statistical Machine Translation System
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2nd International Workshop on Spoken language Translation, IWSLT 2005
作者: Zens, Richard Bender, Oliver Hasan, Saša Khadivi, Shahram Matusov, Evgeny Xu, Jia Zhang, Yuqi Ney, Hermann Human Language Technology and Pattern Recognition Lehrstuhl für Informatik VI Computer Science Department RWTH Aachen University AachenD-52056 Germany
We give an overview of the RWTH phrase-based statistical machine translation system that was used in the evaluation campaign of the International Workshop on Spoken language Translation 2005. We use a two pass approac... 详细信息
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Are very large N-best lists useful for SMT?
Are very large N-best lists useful for SMT?
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2007 human language technology Conference of the North American Chapter of the Association of Computational Linguistics, NAACL-HLT 2007
作者: Hasan, Saša Zens, Richard Ney, Hermann Human Language Technology and Pattern Recognition Lehrstuhl für Informatik 6 Computer Science Department RWTH Aachen University AachenD-52056 Germany
This paper describes an efficient method to extract large n-best lists from a word graph produced by a statistical machine translation system. The extraction is based on the k shortest paths algorithm which is efficie... 详细信息
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Chunk-level reordering of source language sentences with automatically learned rules for statistical machine translation
Chunk-level reordering of source language sentences with aut...
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2007 AMTA Workshop on Syntax and Structure in Statistical Translation, SSST 2007 at the 2007 Conference of the North American Chapter of the Association for Computational Linguistics: human language Technologies, NAACL-HLT 2007
作者: Zhang, Yuqi Zens, Richard Ney, Hermann Human Language Technology and Pattern Recognition Lehrstuhl für Informatik 6 Computer Science Department RWTH Aachen University AachenD-52056 Germany
In this paper, we describe a source-side reordering method based on syntactic chunks for phrase-based statistical machine translation. First, we shallow parse the source language sentences. Then, reordering rules are ... 详细信息
来源: 评论