检索结果-内蒙古大学图书馆

您好，读者！请登录

内蒙古大学图书馆

首页
概况
党建
资源
服务
科研支持
- 论文收录引用证明
- 科技查新
知识产权
档案馆
帮助

咨询与建议

建议与咨询留下您的常用邮箱和电话号码，以便我们向您反馈解决方案和替代方法

您的常用邮箱：*

您的手机号码：*

问题描述：

当前已输入0个字，您还可以输入200个字

全部搜索
期刊论文
图书
学位论文
标准
纸本馆藏
外文资源发现
数据库导航
超星发现

高级检索

时间限定

出版年份：

文献类型

图书期刊文献学位论文多媒体

馆藏选择

电子馆藏纸本馆藏

核心期刊

全部期刊 SCI 收录期刊 SSCI 收录期刊 EI 收录期刊 CSCD 收录期刊 CSSCI 收录期刊

语言

中文英文

文献类型

期刊文献图书学位论文标准纸本馆藏

帮助

文字说明：

T=题名（书名、题名），A=作者（责任者），K=主题词，P=出版物名称，PU=出版社名称，O=机构（作者单位、学位授予单位、专利申请人），L=中图分类号，C=学科分类号，U=全部字段，Y=年（出版发行年、学位年度、标准发布年）

检索规则说明：

AND代表“并且”；OR代表“或者”；NOT代表“不包含”；(注意必须大写,运算符两边需空一格)

检索范例：

范例一：(K=图书馆学 OR K=情报学) AND A=范并思 AND Y=1982-2016
范例二：P=计算机应用与软件 AND (U=C++ OR U=Basic) NOT K=Visual AND Y=2011-2016

分类表

所选分类

>> <<

限定检索结果

文献类型

291 篇 会议
110 篇 期刊文献

馆藏范围

401 篇 电子文献
0 种 纸本馆藏

日期分布

学科分类号

275 篇 工学
- 204 篇 计算机科学与技术...
- 187 篇 软件工程
- 72 篇 信息与通信工程
- 23 篇 生物工程
- 20 篇 机械工程
- 17 篇 控制科学与工程
- 14 篇 电气工程
- 14 篇 电子科学与技术（可...
- 12 篇 光学工程
- 9 篇 化学工程与技术
- 7 篇 生物医学工程（可授...
- 5 篇 仪器科学与技术
- 3 篇 动力工程及工程热...
- 2 篇 材料科学与工程（可...
- 2 篇 土木工程
174 篇 理学
- 118 篇 物理学
- 72 篇 数学
- 42 篇 统计学（可授理学、...
- 27 篇 生物学
- 20 篇 系统科学
- 10 篇 化学
- 1 篇 地球物理学
38 篇 管理学
- 27 篇 图书情报与档案管...
- 11 篇 管理科学与工程(可...
- 5 篇 工商管理
6 篇 法学
- 5 篇 社会学
- 1 篇 法学
2 篇 经济学
- 2 篇 应用经济学
2 篇 文学
- 2 篇 外国语言文学
- 1 篇 中国语言文学
1 篇 农学
1 篇 医学
1 篇 艺术学

主题

70 篇 speech recogniti...
42 篇 hidden markov mo...
41 篇 training
29 篇 neural machine t...
25 篇 machine translat...
21 篇 decoding
20 篇 handwriting reco...
18 篇 computer aided l...
17 篇 recurrent neural...
16 篇 feature extracti...
15 篇 vocabulary
15 篇 transducers
13 篇 databases
13 篇 error analysis
11 篇 speech
11 篇 pattern recognit...
11 篇 humans
9 篇 training data
9 篇 modelling langua...
9 篇 optimization

机构

52 篇 human language t...
40 篇 human language t...
38 篇 apptek gmbh aach...
32 篇 human language t...
31 篇 human language t...
23 篇 apptek gmbh aach...
21 篇 human language t...
16 篇 human language t...
13 篇 human language t...
12 篇 pattern recognit...
10 篇 human language t...
9 篇 spoken language ...
9 篇 human language t...
8 篇 computer science...
8 篇 human language t...
7 篇 pattern recognit...
6 篇 pattern recognit...
6 篇 human language t...
6 篇 human language t...
6 篇 human language t...

作者

212 篇 ney hermann
81 篇 hermann ney
61 篇 schlüter ralf
23 篇 ralf schluter
21 篇 ralf schlüter
20 篇 casacuberta fran...
20 篇 wuebker joern
18 篇 zeyer albert
18 篇 zhou wei
16 篇 gao yingbo
14 篇 kim yunsu
14 篇 herold christian
13 篇 mansour saab
13 篇 zeineldeen moham...
13 篇 patrick doetsch
13 篇 peitz stephan
13 篇 huck matthias
12 篇 peris álvaro
12 篇 peter jan-thorst...
12 篇 michel wilfried

语言

398 篇 英文
1 篇 西班牙文
1 篇 其他
1 篇 中文

检索条件"机构=Pattern Recognition and Human Language"

共 401 条记录，以下是211-220 订阅

全选清除本页清除全部题录导出标记到"检索档案"

详细简洁

排序：

Advances in Arabic broadcast news transcription at RWTH

Advances in Arabic broadcast news transcription at RWTH

引用

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

来源：评论

学校读者我要写书评

暂无评论

Offline Features for Classifying Handwritten Math Symbols with Recurrent Neural Networks

Offline Features for Classifying Handwritten Math Symbols wi...

引用

International Conference on pattern recognition

作者： Francisco Álvaro Joan-Andreu Sánchez José-Miguel Benedí Pattern Recognition and Human Language Technologies Universitat Politècnica de València Spain

In mathematical expression recognition, symbol classification is a crucial step. Numerous approaches for recognizing handwritten math symbols have been published, but most of them are either an online approach or a hybrid approach. There is an absence of a study focused on offline features for handwritten math symbol recognition. Furthermore, many papers provide results difficult to compare. In this paper we assess the performance of several well-known offline features for this task. We also test a novel set of features based on polar histograms and the vertical repositioning method for feature extraction. Finally, we report and analyze the results of several experiments using recurrent neural networks on a large public database of online handwritten math expressions. The combination of online and offline features significantly improved the recognition rate.

关键词： Feature extraction Text recognition Vectors Handwriting recognition Hidden Markov models Databases Training

来源：评论

学校读者我要写书评

暂无评论

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

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

引用

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

来源：评论

学校读者我要写书评

暂无评论

Morpheme-based feature-rich language models using Deep Neural Networks for LVCSR of Egyptian Arabic

Morpheme-based feature-rich language models using Deep Neura...

引用

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

来源：评论

学校读者我要写书评

暂无评论

Development of the 2007 RWTH Mandarin LVCSR system

Development of the 2007 RWTH Mandarin LVCSR system

引用

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

来源：评论

学校读者我要写书评

暂无评论

A random forest approach for authorship profiling 16

A random forest approach for authorship profiling

引用

16th Conference and Labs of the Evaluation Forum, CLEF 2015

作者： Palomino-Garibay, Alonso Camacho-González, Adolfo T. Fierro-Villaneda, Ricardo A. Hernández-Farias, Irazú Buscaldi, Davide Meza-Ruiz, Ivan V. Ciudad de Mexico Mexico Ciudad de Mexico Mexico Pattern Recognition and Human Language Technology Universitat Politécnica de Valencia Valencia Spain Universite Paris 13 Sorbonne Paris Cité Villetaneuse France

In this paper we present our approach to extract profile information from anonymized tweets for the author profiling task at PAN 2015 [10]. Particularly we explore the versatility of random forest classifiers for the genre and age groups information and random forest regressions to score important aspects of the personality of a user. Furthermore we propose a set of features tailored for this task based on characteristics of the twitters. In particular, our approach relies on previous proposed features for sentiment analysis tasks.

关键词： Decision trees

来源：评论

学校读者我要写书评

暂无评论

Improvement of Context Dependent Modeling for Arabic Handwriting recognition

Improvement of Context Dependent Modeling for Arabic Handwri...

引用

International Workshop on Frontiers in Handwriting recognition

作者： Mahdi Hamdani Patrick Doetsch Hermann Ney Human Language Technology and Pattern Recognition Computer Science Department RWTH Aachen University Aachen Germany

This paper proposes the improvement of context dependent modeling for Arabic handwriting recognition. Since the number of parameters in context dependent models is huge, CART trees are used for state tying. This work is based on a new set of questions for the CART tree construction based on a "lossy mapping" categorization of the Arabic shapes. The used system is a combination of Hidden Markov Models and Recurrent Neural Networks using the hybrid approach. A comparison between a Neural network trained using the baseline labels and another one based on the CART tree labels is done. The experimental results show that the use of the CART labels for the Neural Network training beneficial. The lossy mapping based CART tree performed better than the baseline system. An absolute improvement of 2.9% in terms of Word Error Rate is performed on the test set of the Open Hart database.

关键词： Hidden Markov models Context Handwriting recognition Context modeling Training Shape Speech recognition

来源：评论

学校读者我要写书评

暂无评论

A comparative analysis of dynamic network decoding

A comparative analysis of dynamic network decoding

引用

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

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

ISBN: (纸本)9781457705380

The use of statically compiled search networks for ASR systems using huge vocabularies and complex language models often becomes challenging in terms of memory requirements. Dynamic network decoders introduce additional computations in favor of significantly lower memory consumption. In this paper we investigate the properties of two well-known search strategies for dynamic network decoding, namely history conditioned tree search and WFST-based search using dynamic transducer composition. We analyze the impact of the differences in search graph representation, search space structure, and language model look-ahead techniques. Experiments on an LVCSR task illustrate the influence of the compared properties.

关键词： Decoding Transducers Hidden Markov models History Speech recognition Context Vocabulary

来源：评论

学校读者我要写书评

暂无评论

Powerful extensions to CRFS for grapheme to phoneme conversion

Powerful extensions to CRFS for grapheme to phoneme conversi...

引用

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

作者： Stefan Hahn Patrick Lehnen Hermann Ney Human Language Technology and Pattern Recognition Computer Science Department RWTH Aachen University Aachen Germany

ISBN: (纸本)9781457705380

Conditional Random Fields (CRFs) have proven to per form well on natural language processing tasks like name transliteration, concept tagging or grapheme-to-phoneme (g2p) conversion. The aim of this paper is to propose some extension to the state-of-the-art CRF systems for these tasks. Since the number of features can grow rapidly, a method for features selection is very helpful to boost performance. A combination of L1 and L2 regularization (elastic net) has been adopted and implemented within the Rprop optimization algorithm. Usually, dependencies on the target side are limited to bigram dependencies since the computational complexity grows exponentially with the history length. We present a modified CRF decoding where a conventional language model on target side is integrated into the CRF search process. Thus, larger contexts can be taken into account. Besides these two main parts, the already published margin-extension to the CRF training criterion has been adopted.

关键词： Training Context Context modeling Optimization Natural language processing Software algorithms Interpolation

来源：评论

学校读者我要写书评

暂无评论

Comparison and combination of different CRBE based MLP features for LVCSR

Comparison and combination of different CRBE based MLP featu...

引用

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

作者： Zoltán Tüske Ralf Schlüter Hermann Ney Human Language Technology and Pattern Recognition Computer Science Department RWTH Aachen University Aachen Germany

Multi Layer Perceptron (MLP) features extracted from different types of critical band energies (CRBE) - derived from MFCC, GT, and PLP pipeline - are compared on French broadcast news and conversational speech recognition task. Though the MLP structure is kept fixed, ROVER combination of different CRBE based systems leads to 4% relative improvement. Furthermore, aiming at the combination of state-of-the-art features based on various signal analysis methods into one single stream, posterior feature space based combination technique is proposed. The speaker normalized features originated from different CRBEs are merged after additional MLP training by Dempster-Shafer rule. The performance of these posterior features unifying the different CRBE based features is superior to the best single CRBE based posterior features by 6% relative. Further results reveal that the concatenated cepstral and unified posterior features perform nearly as well as the ROVER combination of the different CRBE based systems.

关键词： Feature extraction Mel frequency cepstral coefficient Speech Training Hidden Markov models

来源：评论

学校读者我要写书评

暂无评论

没有更多数据了...

全选清除本页清除全部题录导出标记到“检索档案”

共41页 << < 18 19 20 21 22 23 24 25 26 27 > >>

检索报告对象比较合并检索0

隐藏清空

合并搜索

回到顶部

执行限定条件

内容：

评分：

请选择保存的检索档案：

请选择收藏分类：

订阅名称：

通借通还

温馨提示：

图书名称：

借书校区：

取书校区：

手机号码：

邮箱地址：

一卡通帐号：

电话和邮箱必须正确填写，我们会与您联系确认。

联系人：

所在院系：

联系邮箱：

联系电话：

内蒙古自治区呼和浩特市赛罕区大学西街235号邮编: 010021

建议与咨询 留下您的常用邮箱和电话号码，以便我们向您反馈解决方案和替代方法

时间限定

文献类型

馆藏选择

核心期刊

语言

文献类型

帮助

文字说明：

检索规则说明：

检索范例：

分类表

所选分类

限定检索结果

文献类型

馆藏范围

日期分布

学科分类号

主题

机构

作者

语言

请选择保存的检索档案： 新增检索档案 确定 取消

请选择收藏分类： 新增自定义分类 确定 取消

通借通还

建议与咨询留下您的常用邮箱和电话号码，以便我们向您反馈解决方案和替代方法

请选择保存的检索档案：

请选择收藏分类：