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International Conference on Current Research in computer science and Information Technology (ICCIT)

作者： Aram Mahmood Ahmed Sarkar Hasan Ahmed Omed Hassan Ahmed Department of Information Computer Science Institute University of Human Development Scientific Research

ISBN: (纸本)9781538629567

Play Fairal gorithm has been enhanced in various ways. One of the methods is to increase the confusion rates by transforming the algorithm into 3D-playfair which has four tables of 4×4 and accepts trigraph rather than digraph. This paper further enhances the 3D-playfair algorithm by extending its tables and hereby increasing the security level as well as supporting the characters of all the world's living languages. This is achieved by using four matrices of 128×128 to store all the possible characters which are 65536. As a result, the proposed algorithm has more resistanceto brute force andfrequency analysis attacks.

关键词： Floors Ciphers Encryption Algorithm design and analysis Force

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Investigations on byte-level convolutional neural networks for language modeling in low resource speech recognition

Investigations on byte-level convolutional neural networks f...

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IEEE International Conference on Acoustics, Speech and Signal Processing

作者： Kazuki Irie Pavel Golik Ralf Schluter Hermann Ney Human Language Technology and Pattern Recognition Computer Science Department RWTH Aachen University Germany

ISBN: (纸本)9781509041183

In this paper, we present an investigation on technical details of the byte-level convolutional layer which replaces the conventional linear word projection layer in the neural language model. In particular, we discuss and compare the effective filter configurations, pooling types and the use of bytes instead of characters. We carry out experiments on language packs released by the IARPA Babel project and measure the performance in terms of perplexity and word error rate. Introducing a convolutional layer consistently improves the results on all languages. Also, there is no degradation from using raw bytes instead of proper Unicode characters, even on syllabic alphabets like Amharic. In addition, we report improvements in word error rate from rescoring lattices and evaluate keyword search performance on several languages.

关键词： language modeling convolutional neural networks speech recognition keyword search modelling languages Speech recognition Key Search Error analysis language Amharic Byte Word

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Audio segmentation for speech recognition using segment features

Audio segmentation for speech recognition using segment feat...

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

作者： David Rybach Christian Gollan Ralf Schluter Hermann Ney Human Language Technology and Pattern Recognition Computer Science Department RWTH Aachen University Germany

Audio segmentation is an essential preprocessing step in several audio processing applications with a significant impact e.g. on speech recognition performance. We introduce a novel framework which combines the advantages of different well known segmentation methods. An automatically estimated log-linear segment model is used to determine the segmentation of an audio stream in a holistic way by a maximum a posteriori decoding strategy, instead of classifying change points locally. A comparison to other segmentation techniques in terms of speech recognition performance is presented, showing a promising segmentation quality of our approach.

关键词： Speech recognition Streaming media Decoding Broadcasting Loudspeakers Automatic speech recognition Bayesian methods humans Natural languages Pattern recognition

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A Novel Detection System for human Retina Based on Fuzzification Neural Network 1st

A Novel Detection System for Human Retina Based on Fuzzifica...

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1st International Conference on Applied Computing Research to Support Industry: Innovation and Technology, ACRIT 2019

作者： Alheeti, Khattab M. Ali Abdulbaqi, Azmi Shawkat Saleh, Hadeel M. Al-Ani, Muzhir Shaban Department of Computer Networking System College of Computer Sciences and Information Technology University of Anbar PO Box 55 Ramadi Iraq Department of Computer Sciences College of Computer Sciences and Information Technology University of Anbar Ramadi Iraq College of Education for Women University of Anbar Ramadi Iraq College of Science and Technology Department of Information Technology University of Human Development Sulaymaniyah Iraq

ISBN: (纸本)9783030387518

Automated methods are based on human biometrics for the purpose of verifying a person’s identity based on the physiological or behavioural features of humans. Biometrics traits include facial, iris, retina, fingerprint, and tongue. Preserving biometrics is very important because it is one of the means of preserving the information of others. One of the most important biometrics, most accurate, and powerful methods of identity verification is human retina. The unique retina features per person can be displayed as a compact binary form. For the purpose of confirming an individual’s identity, the unique retinal features of the individual can be easily compared with the reference template. In this paper, a novel detection system is proposed for retinal images utilising the fuzzification model that integrated with deep learning neural networks. In addition, identification system based on human retina is considered the most protect scheme of modern applications. The novelty in this paper is integrated between fuzzy set and deep learning neural networks. Practically, this is first time to integrate between fuzzification model and artificial neural network. The obtained experimental results of the proposed identification system demonstrate that the suggested approach possess outstanding detection rate with decline error rate as well as reducing the number of false alarms. © 2020, Springer Nature Switzerland AG.

关键词： Biometrics

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Advances in Arabic broadcast news transcription at RWTH

Advances in Arabic broadcast news transcription at RWTH

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IEEE Workshop on Automatic Speech Recognition and Understanding

作者： David Rybach Stefan Hahn Christian Gollan Ralf Schluter Hermann Ney Human Language Technology and Pattern Recognition Computer Science Department RWTH Aachen University Germany

ISBN: (纸本)9781424413690;1424413699

This paper describes the RWTH speech recognition system for Arabic. Several design aspects of the system, including cross-adaptation, multiple system design and combination, are analyzed. We summarize the semi-automatic lexicon generation for Arabic using a statistical approach to grapheme-to-phoneme conversion and pronunciation statistics. Furthermore, a novel ASR-based audio segmentation algorithm is presented. Finally, we discuss practical approaches for parallelized acoustic training and memory efficient lattice rescoring. Systematic results are reported on recent GALE evaluation corpora.

关键词： Broadcasting Mel frequency cepstral coefficient Hidden Markov models Neural networks Lattices Cepstral analysis Speech recognition humans Natural languages Loudspeakers

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Inversion transduction grammar coverage of arabic-english word alignment for tree-structured statistical machine translation

Inversion transduction grammar coverage of arabic-english wo...

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IEEE Spoken language Technology Workshop

作者： Dekai Wu Marine Carpuat Yihai Shen HKUST Department of Computer Science and Engineering Human Language Technology Center Hong Kong China

We present the first known direct measurement of word alignment coverage on an Arabic-English parallel corpus using inversion transduction grammar constraints. While direct measurements have been reported for several European and Asian languages, to date no results have been available for Arabic or any Semitic language despite much recent activity on Arabic- English spoken language and text translation. Many recent syntax based statistical MT models operate within the domain of ITG expressiveness, often for efficiency reasons, so it has become important to determine the extent to which the ITG constraint assumption holds. Our results on Arabic provide further evidence that ITG expressiveness appears largely sufficient for core MT models.

关键词： Natural languages Decoding Context modeling Hidden Markov models Error analysis humans Marine technology computer science Oral communication Formal languages

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development of the 2007 RWTH Mandarin LVCSR system

Development of the 2007 RWTH Mandarin LVCSR system

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IEEE Workshop on Automatic Speech Recognition and Understanding

作者： Bjorn Hoffmeister Christian Plahl Peter Fritz Georg Heigold Jonas Loof Ralf Schluter Hermann Ney Human Language and Pattern Recognition Computer Science Department 6 RWTH Aachen University Germany

ISBN: (纸本)9781424413690;1424413699

This paper describes the development of the RWTH Mandarin LVCSR system. Different acoustic front-ends together with multiple system cross-adaptation are used in a two stage decoding framework. We describe the system in detail and present systematic recognition results. Especially, we compare a variety of approaches for cross-adapting to multiple systems. During the development we did a comparative study on different methods for integrating tone and phoneme posterior features. Furthermore, we apply lattice based consensus decoding and system combination methods. In these methods, the effect of minimizing character instead of word errors is compared. The final system obtains a character error rate of 17.7% on the GALE 2006 evaluation data.

关键词： Decoding Error analysis Dictionaries Neural networks Natural languages Lattices Vocabulary humans Pattern recognition computer science

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Formative feedback in interactive learning environments

Formative feedback in interactive learning environments

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16th International Conference on Artificial Intelligence in Education, AIED 2013

作者： Goldin, Ilya M. Martin, Taylor Baker, Ryan Aleven, Vincent Barnes, Tiffany Human-Computer Interaction Institute Carnegie Mellon University Pittsburgh PA United States Department of Instructional Technology and Learning Sciences Utah State University Logan UT United States Department of Human Development Teachers College Columbia University New York City NY United States Department of Computer Science North Carolina State University Raleigh NC United States

ISBN: (纸本)9783642391118

Educators and researchers have long recognized the importance of formative feedback for learning. Formative feedback helps learners understand where they are in a learning process, what the goal is, and how to reach that goal. While experimental and observational research has illuminated many aspects of feedback, modern interactive learning environments provide new tools to understand feedback and its relation to various learning outcomes. © 2013 Springer-Verlag Berlin Heidelberg.

关键词： Learning systems

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Peer Ratings and Social Problem-solving Skills of 6-8 Years Old Children

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Journal of Psychology 2014年第1期5卷 75-78页

作者： Suneeta Paswan Kumar Sanjeev Indu Bansal Department of Human Development Faculty of Home Science Banasthali Vidyapith Department of Stat Maths and Computer Application Rajendra Agricultural University

For the study Faizabad regions of state Uttar Pradesh were selected as locales. Faizabad region included districts namely-Faizabad, Barabanki, Sultanpur, Ambedkar Nagar and Gonda. Four Schools and hundred children from each district were selected. Hence a total of 500 primary school children were assessed for peer acceptance and rejection and interpersonal social problem-solving skills. Result of this study showed the relationship between peer acceptance and rejection and interpersonal social problem-solving skills. Positively rated children suggested more number of relevant strategies and flexibility than their less accepted counter parts. Also positively rated children were more likely to suggest prosocial strategies for obtaining access to an object in another child’s possession, while reverse was seen among negatively rated children.

关键词： Pro-social Strategies Sociometric Measure Object Acquisition Relevancy Correlation

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On constant-weight multi-valued sequences from cyclic difference sets

On constant-weight multi-valued sequences from cyclic differ...

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作者： Kaida, Takayasu Zheng, Junru Department of Information and Computer Sciences Faculty of Humanity-Oriented Science and Engineering Kinki University Iizuka-shi 820-8555 Japan Department of Human Development Faculty of Humanities Kyushu Women's University Kitakyushu-shi 807-8586 Japan

We proposed a method for constructing constant-weight and multi-valued sequences from the cyclic difference sets by generalization of the method in binary case proposed by N. Li, X. Zeng and L. Hu in 2008. In this paper we give some properties about sets of such sequences and it is shown that a set of non-constant-weight sequences over Z4 with length 13 from the (13,4, l)-cyclic difference set, and a set of constant-weight sequences over Z5 with length 21 from the (21,5, l)-cyclic difference set have almost highest linear complexities and good profiles of all sequences' linear complexities. Moreover we investigate the value distribution, the linear complexity and correlation properties of a set of sequences with length 57 over GF(8) from the (57,8, l)-cyclic difference set. It is pointed out that this set also has good value distributions and almost highest linear complexities in similar to previous two sets over Z4 with length 13 and Z5 with length 21. Copyright © 2013 The Institute of Electronics, Information and Communication Engineers.

关键词： Set theory

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