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

284 篇 会议
101 篇 期刊文献

馆藏范围

385 篇 电子文献
0 种 纸本馆藏

日期分布

学科分类号

261 篇 工学
- 192 篇 计算机科学与技术...
- 176 篇 软件工程
- 66 篇 信息与通信工程
- 21 篇 机械工程
- 19 篇 生物工程
- 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...
- 10 篇 光学工程
- 9 篇 化学工程与技术
- 7 篇 生物医学工程（可授...
- 3 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
163 篇 理学
- 109 篇 物理学
- 66 篇 数学
- 36 篇 统计学（可授理学、...
- 23 篇 生物学
- 20 篇 系统科学
- 10 篇 化学
- 1 篇 地球物理学
36 篇 管理学
- 26 篇 图书情报与档案管...
- 9 篇 管理科学与工程(可...
- 4 篇 工商管理
6 篇 法学
- 5 篇 社会学
- 1 篇 法学
2 篇 文学
- 2 篇 外国语言文学
- 1 篇 中国语言文学
1 篇 经济学
- 1 篇 应用经济学
1 篇 农学
1 篇 医学
1 篇 艺术学

主题

66 篇 speech recogniti...
41 篇 training
39 篇 hidden markov mo...
29 篇 neural machine t...
23 篇 machine translat...
20 篇 decoding
19 篇 handwriting reco...
18 篇 computer aided l...
16 篇 recurrent neural...
15 篇 feature extracti...
15 篇 transducers
14 篇 vocabulary
12 篇 databases
12 篇 error analysis
11 篇 speech
10 篇 pattern recognit...
10 篇 humans
9 篇 training data
9 篇 optimization
9 篇 context

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...
6 篇 pattern recognit...
6 篇 human language t...
6 篇 human language t...
6 篇 human language t...
5 篇 a2ia sa

作者

213 篇 ney hermann
82 篇 hermann ney
61 篇 schlüter ralf
22 篇 ralf schluter
21 篇 ralf schlüter
20 篇 wuebker joern
18 篇 casacuberta fran...
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

383 篇 英文
1 篇 西班牙文
1 篇 中文

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

共 385 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：

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...

引用

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

ISBN: (纸本)9781467369978

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 conditions by an appropriate parameter setting, while the latter needs to be trained on conditions similar to the ones expected at decoding time, making it vulnerable to a mismatch between training and test conditions. We use a DNN backend and study reverberant ASR under three types of mismatch conditions: different room reverberation times, different speaker to microphone distances and the difference between artificially reverberated data and the recordings in a reverberant environment. We show that for these mismatch conditions BFE can provide the targets for a DA. This unsupervised adaptation provides a performance gain over the direct use of BFE and even enables to compensate for the mismatch of real and simulated reverberant data. © 2015 IEEE.

关键词： deep neuronal networks denoising autoencoder feature enhancement robust speech recognition

来源：评论

学校读者我要写书评

暂无评论

Speeding up 2D-warping for pose-invariant face recognition

Speeding up 2D-warping for pose-invariant face recognition

引用

International Conference on Automatic Face and Gesture Recognition

作者： Harald Hanselmann Hermann Ney Human Language Technology and Pattern Recognition Group RWTH Aachen University Germany

Recently, state-of-the-art recognition accuracies for pose-invariant face recognition have been achieved by using 2D-Warping methods in a nearest-neighbor framework. However, the main drawback of these methods is the high computational complexity. In this paper we address this issue. We use a simple and fast method to get a rough estimate of a 2D-Warping. This estimate can then be used to apply an image dependent warprange on the 2D-Warping algorithm, limit the possible poses or preselect the most likely classes. By this method we are able significantly reduce the runtime of a recently proposed 2D-Warping algorithm without sacrificing recognition accuracy.

关键词： Face recognition Accuracy Runtime Databases Complexity theory Manuals Face

来源：评论

学校读者我要写书评

暂无评论

Speaker adaptive joint training of Gaussian mixture models and bottleneck features

Speaker adaptive joint training of Gaussian mixture models a...

引用

IEEE Workshop on Automatic Speech Recognition and Understanding

作者： Zoltán Tüske Pavel Golik Ralf Schlüter Hermann Ney Human Language Technology and Pattern Recognition RWTH Aachen University Aachen Germany

In the tandem approach, the output of a neural network (NN) serves as input features to a Gaussian mixture model (GMM) aiming to improve the emission probability estimates. As has been shown in our previous work, GMM with pooled covariance matrix can be integrated into a neural network framework as a softmax layer with hidden variables, which allows for joint estimation of both neural network and Gaussian mixture parameters. Here, this approach is extended to include speaker adaptive training (SAT) by introducing a speaker dependent neural network layer. Error backpropagation beyond this speaker dependent layer realizes the adaptive training of the Gaussian parameters as well as the optimization of the bottleneck (BN) tandem features of the underlying acoustic model, simultaneously. In this study, after the initialization by constrained maximum likelihood linear regression (CMLLR) the speaker dependent layer itself is kept constant during the joint training. Experiments show that the deeper backpropagation through the speaker dependent layer is necessary for improved recognition performance. The speaker adaptively and jointly trained BN-GMM results in 5% relative improvement over very strong speaker-independent hybrid baseline on the Quaero English broadcast news and conversations task, and on the 300-hour Switchboard task.

关键词： Adaptation models Training Acoustics Hidden Markov models Robustness Artificial neural networks

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

Bagging by design for continuous Handwriting Recognition using multi-objective particle swarm optimization

Bagging by design for continuous Handwriting Recognition usi...

引用

International Conference on Document Analysis and Recognition

作者： Mahdi Hamdani Patrick Doetsch Hermann Ney Human Language Technology and Pattern Recognition Group - RWTH Aachen University Germany Spoken Language Processing Group LIMSI CNRS Paris France

Multiple classifier systems are used to improve baseline results using different strategies. Bagging by design improves standard bagging by the minimization of intersection between the different ensembles. This work proposes the use of design bagging for continuous handwriting recognition. The design is performed using a multi-objective particle swarm optimizer. Hidden Markov Models and Long-Short Term Memory Recurrent Neural Networks are used to validate the proposed design. Experiments on English and French Handwriting Recognition with different setups show significant improvements.

关键词： Lattices Optimization Optical character recognition software

来源：评论

学校读者我要写书评

暂无评论

Combining handwriting and speech recognition for transcribing historical handwritten documents

Combining handwriting and speech recognition for transcribin...

引用

International Conference on Document Analysis and Recognition

作者： Emilio Granell Carlos-D. Martínez-Hinarejos Pattern Recognition and Human Language Technology Research Center Universitat Politècnica de València Valencia Spain

Transcription of historical documents is an interesting task for libraries in order to make available their funds. In the lasts years, the use of Handwritten Text Recognition allowed paleographs to speed up the manual transcription process, since they are able to correct on a draft transcription. Another alternative is obtaining the draft transcription by dictating the contents to an Automatic Speech Recognition system. When both sources (image and speech) are available, a multimodal combination is possible, and an iterative process can be used in order to refine the final hypothesis. In this work, a multimodal combination based on confusion networks is presented. Results on two different sets of data, with different difficulty level, show that the proposed technique provides similar or better draft transcriptions than a previously proposed approach, allowing for a faster transcription process.

关键词： Iterative decoding Acoustics Proposals Laplace equations Integrated optics Optical imaging

来源：评论

学校读者我要写书评

暂无评论

Influence of text line segmentation in Handwritten Text Recognition 13

Influence of text line segmentation in Handwritten Text Reco...

引用

13th International Conference on Document Analysis and Recognition, ICDAR 2015

作者： Romero, Veronica Sanchez, Joan Andreu Bosch, Vicente Depuydt, Katrien De Does, Jesse Pattern Recognition and Human Language Technology Universitat Politècnica de València Camí de Vera S/n València Spain Instituut voor Nederlandse Lexicologie 2300RA Matthias de Vrieshof 2-3 Leiden2311 BZ Netherlands

ISBN: (纸本)9781479918058

Text line segmentation is the process by which text lines in a document image are localized and extracted. It is an important step in off-line Handwritten Text Recognition (HTR) given that the input of these systems is the line image of the text to be transcribed. A myriad of solutions to the text line segmentation problem have been proposed in the literature. Although these solutions may differ greatly on what is actually applied to perform the segmentation, they can be classified by the level of precision and detail in the final extracted lines. In this paper we study the influence and real needs of different levels of precision and detail in the segmentation solutions in a real HTR task. We test three technics of text line segmentation whose output range from a simple rectangle for each line to a perfect fitted polygon surrounding the detected lines. Experiments have been carried out with a historical collection and results show that good HTR accuracy can be obtained with simple extraction algorithms. © 2015 IEEE.

关键词： Image segmentation

来源：评论

学校读者我要写书评

暂无评论

Deep Learning of Mouth Shapes for Sign language

Deep Learning of Mouth Shapes for Sign Language

引用

International Conference on Computer Vision Workshops (ICCV Workshops)

作者： Oscar Koller Hermann Ney Richard Bowden Human Language Technology & Pattern Recog. RWTH Aachen University Germany Centre for Vision Speech & Signal Processing University of Surrey UK

This paper deals with robust modelling of mouth shapes in the context of sign language recognition using deep convolutional neural networks. Sign language mouth shapes are difficult to annotate and thus hardly any publicly available annotations exist. As such, this work exploits related information sources as weak supervision. humans mainly look at the face during sign language communication, where mouth shapes play an important role and constitute natural patterns with large variability. However, most scientific research on sign language recognition still disregards the face. Hardly any works explicitly focus on mouth shapes. This paper presents our advances in the field of sign language recognition. We contribute in following areas: We present a scheme to learn a convolutional neural network in a weakly supervised fashion without explicit frame labels. We propose a way to incorporate neural network classifier outputs into a HMM approach. Finally, we achieve a significant improvement in classification performance of mouth shapes over the current state of the art.

关键词： Mouth Shape Hidden Markov models Assistive technology Gesture recognition Training Neural networks

来源：评论

学校读者我要写书评

暂无评论

Extensions of the Sign language Recognition and Translation Corpus RWTH-PHOENIX-Weather 9

Extensions of the Sign Language Recognition and Translation ...

引用

9th International Conference on language Resources and Evaluation (LREC)

作者： Forster, Jens Schmidt, Christoph Koller, Oscar Bellgardt, Martin Ney, Hermann Human Language Technology and Pattern Recognition RWTH Aachen University Germany

ISBN: (纸本)9782951740884

This paper introduces the RWTH-PHOENIX-Weather 2014, a video-based, large vocabulary, German sign language corpus which has been extended over the last two years, tripling the size of the original corpus. The corpus contains weather forecasts simultaneously interpreted into sign language which were recorded from German public TV and manually annotated using glosses on the sentence level and semi-automatically transcribed spoken German extracted from the videos using the open-source speech recognition system RASR. Spatial annotations of the signers' hands as well as shape and orientation annotations of the dominant hand have been added for more than 40k respectively 10k video frames creating one of the largest corpora allowing for quantitative evaluation of object tracking algorithms. Further, over 2k signs have been annotated using the SignWriting annotation system, focusing on the shape, orientation, movement as well as spatial contacts of both hands. Finally, extended recognition and translation setups are defined, and baseline results are presented.

关键词： Sign language Corpus Automatic Recognition and Translation

来源：评论

学校读者我要写书评

暂无评论

Investigation of Segmental Conditional Random Fields for large vocabulary handwriting recognition

Investigation of Segmental Conditional Random Fields for lar...

引用

International Conference on Document Analysis and Recognition

作者： Mahdi Hamdani M. Ali Basha Shaik Patrick Doetsch Hermann Ney Human Language Technology and Pattern Recognition Group RWTH Aachen University Germany Rheinisch-Westfalische Technische Hochschule Aachen Aachen Nordrhein-Westfalen DE Spoken Language Processing Group LIMSI CNRS Paris France

Multiple types of models are used in handwriting recognition and can be broadly categorized into generative and discriminative models. Gaussian Hidden Markov Models are used successfully in most of the systems. Discriminative training can be applied to these models to improve them further. Alternatively, Segmental Conditional Random Fields have the advantage of being discriminative as well as segmental. The novelty of this work is the investigation of Segmental Conditional Random Fields for handwriting recognition. In addition, Multi-Layer Perceptrons and Long Short Term Memory Recurrent Neural Networks are compared for the observations generation in this framework. Various types of features are investigated in the segmental models for handwriting recognition. Furthermore, class-based language model features are proposed to extend this model. Visual features based on moments are extracted at a word level to make the model more robust. Experimental results on English handwriting show a relative reduction of 13.7% in terms of word error rate w.r.t. the baseline system. The proposed system also outperforms the Gaussian Hidden Markov Models trained discriminatively using the minimum phone error criterion by a relative reduction of 6.9% in terms of word error rate.

关键词： Hidden Markov models Adaptation models Handwriting recognition Computer architecture Speech recognition Computational modeling Markov processes

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39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：