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2013 38th IEEE International Conference on Acoustics, Speech, and Signal Processing, ICASSP 2013

作者： El-Desoky Mousa, Amr Kuo, Hong-Kwang Jeff Mangu, Lidia Soltau, Hagen Human Language Technology and Pattern Recognition Computer Science Department RWTH Aachen University 52056 Aachen Germany IBM T. J. Watson Research Center Yorktown Heights NY 10598 United States

ISBN: (纸本)9781479903566

Egyptian Arabic (EA) is a colloquial version of Arabic. It is a low-resource morphologically rich language that causes problems in Large Vocabulary Continuous Speech recognition (LVCSR). Building LMs on morpheme level is considered a better choice to achieve higher lexical coverage and better LM probabilities. Another approach is to utilize information from additional features such as morphological tags. On the other hand, LMs based on Neural Networks (NNs) with a single hidden layer have shown superiority over the conventional n-gram LMs. Recently, Deep Neural Networks (DNNs) with multiple hidden layers have achieved better performance in various tasks. In this paper, we explore the use of feature-rich DNN-LMs, where the inputs to the network are a mixture of words and morphemes along with their features. Significant Word Error Rate (WER) reductions are achieved compared to the traditional word-based LMs. © 2013 IEEE.

关键词： Deep neural networks

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MORPHEME-BASED FEATURE-RICH language MODELS USING DEEP NEURAL NETWORKS FOR LVCSR OF EGYPTIAN ARABIC

MORPHEME-BASED FEATURE-RICH LANGUAGE MODELS USING DEEP NEURA...

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IEEE International Conference on Acoustics, Speech, and Signal Processing

作者： Amr El-Desoky Mousa Hong-Kwang Jeff Kuo Lidia Mangu Hagen Soltau Human Language Technology and Pattern Recognition - Computer Science Department RWTH Aachen University IBM T. J. Watson Research Center

ISBN: (纸本)9781479903573

关键词： language model Morpheme Feature-rich Deep neural network Egyptian Arabic modelling languages Neural network Arabic language additional features Word Religious Missions Continuous speech recognition

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An open science resource for establishing reliability and reproducibility in functional connectomics

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Scientific data 2014年第1期1卷 140049页

作者： Xi-Nian Zuo Jeffrey S Anderson Pierre Bellec Rasmus M Birn Bharat B Biswal Janusch Blautzik John C S Breitner Randy L Buckner Vince D Calhoun F Xavier Castellanos Antao Chen Bing Chen Jiangtao Chen Xu Chen Stanley J Colcombe William Courtney R Cameron Craddock Adriana Di Martino Hao-Ming Dong Xiaolan Fu Qiyong Gong Krzysztof J Gorgolewski Ying Han Ye He Yong He Erica Ho Avram Holmes Xiao-Hui Hou Jeremy Huckins Tianzi Jiang Yi Jiang William Kelley Clare Kelly Margaret King Stephen M LaConte Janet E Lainhart Xu Lei Hui-Jie Li Kaiming Li Kuncheng Li Qixiang Lin Dongqiang Liu Jia Liu Xun Liu Yijun Liu Guangming Lu Jie Lu Beatriz Luna Jing Luo Daniel Lurie Ying Mao Daniel S Margulies Andrew R Mayer Thomas Meindl Mary E Meyerand Weizhi Nan Jared A Nielsen David O'Connor David Paulsen Vivek Prabhakaran Zhigang Qi Jiang Qiu Chunhong Shao Zarrar Shehzad Weijun Tang Arno Villringer Huiling Wang Kai Wang Dongtao Wei Gao-Xia Wei Xu-Chu Weng Xuehai Wu Ting Xu Ning Yang Zhi Yang Yu-Feng Zang Lei Zhang Qinglin Zhang Zhe Zhang Zhiqiang Zhang Ke Zhao Zonglei Zhen Yuan Zhou Xing-Ting Zhu Michael P Milham Key Laboratory of Behavioral Science and Magnetic Resonance Imaging Research Center Institute of Psychology Chinese Academy of Sciences Chaoyang Beijing 100101 China Faculty of Psychology Southwest University Beibei Chongqing 400715 China. Division of Neuroradiology University of Utah Salt Lake City Utah 84132 USA. Unité de neuroimagerie fonctionnelle Centre de recherche de l'institut universitaire de gériatrie de Montréal Université de Montréal Montreal Quebec Canada H3W 1W5. Department of Psychiatry University of Wisconsin-Madison Madison Wisconsin 53719 USA. Department of Biomedical Engineering New Jersey Institute of Technology Newark New Jersey 07102 USA. Institute of Clinical Radiology Ludwig-Maximilians-University 80336 Munich Germany. Centre for Studies on Prevention of Alzheimer's Disease Department of Psychiatry Douglas Institute McGill University Faculty of Medicine Montreal Quebec Canada H4H 1R3. Department of Psychology Harvard University Cambridge Massachussetts 02138 USA. Mind Research Network Albuquerque New Mexico 87106 USA. Nathan S. Kline Institute for Psychiatric Research Orangeburg New York 10962 USA Phyllis Green and Randolph Cōwen Institute for Pediatric Neuroscience the Child Study Center at NYU Langone Medical Center New York New York 10016 USA. Center for Cognition and Brain Disorders Hangzhou Normal University Gongshu Hangzhou Zhejiang 311121 China. Nathan S. Kline Institute for Psychiatric Research Orangeburg New York 10962 USA. Center for the Developing Brain Child Mind Institute New York New York 10022 USA. University of Chinese Academy of Sciences Shijingshan Beijing 100049 China. State Key Laboratory of Brain and Cognitive Science Institute of Psychology Chinese Academy of Sciences Chaoyang Beijing 100101 China. Huaxi MR Research Center (HMRRC) Department of Radiology West China Hospital of Sichuan University Wuhou Chengdu Sichuan 610041 China. Max Planck Research Group for Neuroanatomy & C

Efforts to identify meaningful functional imaging-based biomarkers are limited by the ability to reliably characterize inter-individual differences in human brain function. Although a growing number of connectomics-based measures are reported to have moderate to high test-retest reliability, the variability in data acquisition, experimental designs, and analytic methods precludes the ability to generalize results. The Consortium for Reliability and Reproducibility (CoRR) is working to address this challenge and establish test-retest reliability as a minimum standard for methods development in functional connectomics. Specifically, CoRR has aggregated 1,629 typical individuals' resting state fMRI (rfMRI) data (5,093 rfMRI scans) from 18 international sites, and is openly sharing them via the International Data-sharing Neuroimaging Initiative (INDI). To allow researchers to generate various estimates of reliability and reproducibility, a variety of data acquisition procedures and experimental designs are included. Similarly, to enable users to assess the impact of commonly encountered artifacts (for example, motion) on characterizations of inter-individual variation, datasets of varying quality are included.

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A comparative large scale study of MLP features for mandarin ASR

A comparative large scale study of MLP features for mandarin...

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作者： Valente, Fabio Doss, Mathew Magimai Plahl, Christian Ravuri, Suman Wang, Wen IDIAP Research Institute CH-1920 Martigny Switzerland Human Language Technology and Pattern Recognition RWTH Aachen University Germany International Computer Science Institute 1947 Center Street Berkeley CA 94704 United States Speech Technology and Research Laboratory SRI International Menlo Park CA United States

MLP based front-ends have shown significant complementary properties to conventional spectral features. As part of the DARPA GALE program, different MLP features were developed for Mandarin ASR. In this paper, all the proposed frontends are compared in systematic manner and we extensively investigate the scalability of these features in terms of the amount of training data (from 100 hours to 1600 hours) and system complexity (maximum likelihood training, SAT, lattice level combination, and discriminative training). Results on 5 hours of evaluation data from the GALE project reveal that the MLP features consistently produce relative improvements in the range of 15% - 23% at the different steps of a multipass system when compared to the conventional short-term spectral based features like MFCC and PLP. The largest improvement is obtained using a hierarchical MLP approach. © 2010 ISCA.

关键词： Maximum likelihood

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Demonstration of Joshua: An open source toolkit for parsing-based machine translation

Demonstration of Joshua: An open source toolkit for parsing-...

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Joint Conference of the 47th Annual Meeting of the Association for Computational Linguistics and 4th International Joint Conference on Natural language Processing of the AFNLP, ACL-IJCNLP 2009

作者： Li, Zhifei Callison-Burch, Chris Dyer, Chris Ganitkevitch, Juri Khudanpur, Sanjeev Schwartz, Lane Thornton, Wren N.G. Weese, Jonathan Zaidan, Omar F. Center for Language and Speech Processing Johns Hopkins University United States Computational Linguistics and Information Processing Lab. University of Maryland United States Human Language Technology and Pattern Recognition Group RWTH Aachen University Germany Natural Language Processing Lab. University of Minnesota United States

ISBN: (纸本)9781617382581

We describe Joshua (Li et al., 2009a)1, an open source toolkit for statistical machine translation. Joshua implements all of the algorithms required for translation via synchronous context free grammars (SCFGs): chart-parsing, n-gram language model integration, beam- and cubepruning, and k-best extraction. The toolkit also implements suffix-array grammar extraction and minimum error rate training. It uses parallel and distributed computing techniques for scalability. We also provide a demonstration outline for illustrating the toolkit's features to potential users, whether they be newcomers to the field or power users interested in extending the toolkit. © 2009 ACL and AFNLP.

关键词： Distributed computer systems

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Joshua: An Open Source Toolkit for Parsing-based Machine Translation 4

Joshua: An Open Source Toolkit for Parsing-based Machine Tra...

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4th Workshop on Statistical Machine Translation, WMT 2009, immediately preceding the 12th Conference of the European Chapter of the Association for Computational Linguistics, EACL 2009

作者： Li, Zhifei Callison-Burch, Chris Dyer, Chris Ganitkevitch, Juri Khudanpur, Sanjeev Schwartz, Lane Thornton, Wren N. G. Weese, Jonathan Zaidan, Omar F. Center For Language And Speech Processing Johns Hopkins University BaltimoreMD United States Computational Linguistics And Information Processing Lab University of Maryland College ParkMD United States Human Language Technology And Pattern Recognition Group RWTH Aachen University Germany Natural Language Processing Lab University of Minnesota MinneapolisMN United States

We describe Joshua, an open source toolkit for statistical machine translation. Joshua implements all of the algorithms required for synchronous context free grammars (SCFGs): chart-parsing, ngram language model integration, beamand cube-pruning, and k-best extraction. The toolkit also implements suffix-array grammar extraction and minimum error rate training. It uses parallel and distributed computing techniques for scalability. We demonstrate that the toolkit achieves state of the art translation performance on the WMT09 French-English translation task. ©2009 Association for Computational Linguistics.

关键词： Distributed computer systems

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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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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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Incorporating On-demand Stereo for Real Time recognition

Incorporating On-demand Stereo for Real Time Recognition

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Conference on Computer Vision and pattern recognition (CVPR)

作者： T. Deselaers A. Criminisi J. Winn A. Agarwal Microsoft Research Limited Cambridge UK Human Language Technology and Pattern Recognition RWTH Aachen University of Technology Germany

A new method for localising and recognising hand poses and objects in real-time is presented. This problem is important in vision-driven applications where it is natural for a user to combine hand gestures and real objects when interacting with a machine. Examples include using a real eraser to remove words from a document displayed on an electronic surface. In this paper the task of simultaneously recognising object classes, hand gestures and detecting touch events is cast as a single classification problem. A random forest algorithm is employed which adaptively selects and combines a minimal set of appearance, shape and stereo features to achieve maximum class discrimination for a given image. This minimal set leads to both efficiency at run time and good generalisation. Unlike previous stereo works which explicitly construct disparity maps, here the stereo matching costs are used directly as visual cue and only computed on-demand, i.e. only for pixels where they are necessary for recognition. This leads to improved efficiency. The proposed method is assessed on a database of a variety of objects and hand poses selected for interacting on a flat surface in an office environment.

关键词： Object detection pattern recognition Shape Cameras humans Event detection Costs Visual databases Hardware Object recognition

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