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Bag-of-visual-words models for adult image classification and filtering

Bag-of-visual-words models for adult image classification an...

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作者： Deselaers, Thomas Pimenidis, Lexi Ney, Hermann Computer Science Department Human Language Technology and Pattern Recognition RWTH Aachen University Aachen Germany Security and Privacy Research RWTH Aachen University Aachen Germany

ISBN: (纸本)9781424421756

We present a method to classify images into different categories of pornographic content to create a system for filtering pornographic images from network traffic. Although different systems for this application were presented in the past, most of these systems are based on simple skin colour features and have rather poor performance. Recent advances in the image recognition field in particular for the classification of objects have shown that bag-of-visual-words-approaches are a good method for many image classification problems. The system we present here, is based on this approach, uses a task-specific visual vocabulary and is trained and evaluated on an image database of 8500 images from different categories. It is shown that it clearly outperforms earlier systems on this dataset and further evaluation on two novel web-traffic collections shows the good performance of the proposed system. © 2008 IEEE.

关键词： Image classification

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Improvements in Dynamic Programming Beam Search for Phrase-based Statistical Machine Translation 5

Improvements in Dynamic Programming Beam Search for Phrase-b...

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5th International Workshop on Spoken language Translation, IWSLT 2008

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 Google Inc. 1600 Am-phitheatre Parkway Mountain ViewCA94043 United States

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 state-of-the-art, in particular we perform a comparison with cube pruning as well as with Moses. © 2008 International Workshop on Spoken language Translation, IWSLT 2008. All rights reserved.

关键词： Dynamic programming

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Bag-of-visual-words models for adult image classification and filtering

Bag-of-visual-words models for adult image classification an...

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International Conference on pattern recognition

作者： Thomas Deselaers Lexi Pimenidis Hermann Ney Human Language Technology and Pattern Recognition Security and Privacy Research Computer Science Department RWTH Aachen University Aachen Germany

ISBN: (纸本)9781424421749

关键词： Image classification Filters Vocabulary Filtering Skin Telecommunication traffic Image databases Histograms Feature extraction Iterative algorithms

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Confidence scores for acoustic model adaptation

Confidence scores for acoustic model adaptation

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International Conference on Acoustics, Speech, and Signal Processing (ICASSP)

作者： Christian Gollan Michiel Bacchiani Human Language Technology and Pattern Recognition Computer Science Department 6 RWTH Aachen University Germany Google Inc. New York NY USA

This paper focuses on confidence scores for use in acoustic model adaptation. Frame-based confidence estimates are used in linear transform (CMLLR and MLLR) and MAP adaptation. We show that adaptation approaches with a limited number of free parameters such as linear transform-based approaches are robust in the face of frame labeling errors whereas adaptation approaches with a large number of free parameters such as MAP are sensitive to the quality of the supervision and hence benefit most from use of confidences. Different approaches for using confidence information in adaptation are investigated. This analysis shows that a thresholding approach is effective in that it improves the frame labeling accuracy with little detrimental effect on frame recall. Experimental results show an absolute WER reduction of 2.1% over a CMLLR adapted system on a video transcription task.

关键词： Adaptation model Maximum likelihood linear regression Parameter estimation Speech Robustness Labeling Multimedia systems humans pattern recognition computer science

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Improved Chunk-level Reordering for Statistical Machine Translation 4

Improved Chunk-level Reordering for Statistical Machine Tran...

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4th International Workshop on Spoken language Translation, IWSLT 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 Germany

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 chunk-level reordering approach, the BLEU score improves 1.4% absolutely. The translation results are reported on IWSLT Chinese-English task. © 2007 International Workshop on Spoken language Translation, IWSLT 2007. All rights reserved.

关键词： computer aided language translation

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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 efficient even for very large k. We show that, although we can generate large amounts of distinct translation hypotheses, these numerous candidates are not able to significantly improve overall system performance. We conclude that large n-best lists would benefit from better discriminating models. © 2007 Association for Computational Linguistics.

关键词： Machine translation

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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 for the source phrases. We will show that this representation scales well to large data tasks and that we are able to store hundreds of millions of phrase pairs in the phrase-table. For the large Chinese-English NIST task, the memory requirements of the phrase-table are reduced to less than 20MB using the new representation with no loss in translation quality and speed. Additionally, the new representation is not limited to a specific test set, which is important for online or real-time machine translation. One problem in speech translation is the matching of phrases in the input word graph and the phrase-table. We will describe a novel algorithm that effectively solves this combinatorial problem exploiting the prefix tree data structure of the phrase-table. This algorithm enables the use of significantly larger input word graphs in a more efficient way resulting in improved translation quality. © 2007 Association for Computational Linguistics.

关键词： Machine translation

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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 model. We describe the individual systems and the method that was used for combining the system outputs. Compared to our 2006 system, we newly introduce a hierarchical phrase-based translation model and show improvements in system combination for Machine Translation. RWTH participated in the Italian-to-English and Chinese-to-English translation directions. © 2007 International Workshop on Spoken language Translation, IWSLT 2007. All rights reserved.

关键词： Machine translation

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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-best lists leads to an improvement of translation quality. We report the performance of the MBR decoder on four different tasks: the TC-STAR EPPS Spanish-English task 2006, the NIST Chinese-English task 2005 and the GALE Arabic-English and Chinese-English task 2006. The absolute improvement of the BLEU score is between 0.2% for the TC-STAR task and 1.1% for the GALE Chinese-English task. ©2007 Association for Computational Linguistics

关键词： Stars

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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 automatically learned from source-side chunks and word alignments. During translation, the rules are used to generate a reordering lattice for each sentence. Experimental results are reported for a Chinese-to-English task, showing an improvement of 0.5%-1.8% BLEU score absolute on various test sets and better computational efficiency than reordering during decoding. The experiments also show that the reordering at the chunk-level performs better than at the POS-level. © 2007 Association for Computational Linguistics

关键词： Computational efficiency

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