咨询与建议

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"
385 条 记 录,以下是271-280 订阅
排序:
Phrase Model Training for Statistical Machine Translation with Word Lattices of Preprocessing Alternatives  7
Phrase Model Training for Statistical Machine Translation wi...
收藏 引用
7th Workshop on Statistical Machine Translation, WMT 2012, immediately following the Conference of the North-American Chapter of the Association for Computational Linguistics - human language Technologies, NAACL HLT 2012
作者: Wuebker, Joern Ney, Hermann Human Language Technology And Pattern Recognition Group Rwth Aachen University Aachen Germany
In statistical machine translation, word lattices are used to represent the ambiguities in the preprocessing of the source sentence, such as word segmentation for Chinese or morphological analysis for German. Several ... 详细信息
来源: 评论
Tracking benchmark databases for video-based sign language recognition
Tracking benchmark databases for video-based sign language r...
收藏 引用
11th European Conference on Computer Vision, ECCV 2010
作者: Dreuw, Philippe Forster, Jens Ney, Hermann Human Language Technology and Pattern Recognition Group RWTH Aachen University Aachen Germany
A survey of video databases that can be used within a continuous sign language recognition scenario to measure the performance of head and hand tracking algorithms either w.r.t. a tracking error rate or w.r.t. a word ... 详细信息
来源: 评论
A Simple and Effective Weighted Phrase Extraction for Machine Translation Adaptation  9
A Simple and Effective Weighted Phrase Extraction for Machin...
收藏 引用
9th International Workshop on Spoken language Translation, IWSLT 2012
作者: Mansour, Saab Ney, Hermann Human Language Technology and Pattern Recognition Computer Science Department RWTH Aachen University Aachen Germany
The task of domain-adaptation attempts to exploit data mainly drawn from one domain (e.g. news) to maximize the performance on the test domain (e.g. weblogs). In previous work, weighting the training instances was use... 详细信息
来源: 评论
Spoken language Translation Using Automatically Transcribed Text in Training  9
Spoken Language Translation Using Automatically Transcribed ...
收藏 引用
9th International Workshop on Spoken language Translation, IWSLT 2012
作者: Peitz, Stephan Wiesler, Simon Nußbaum-Thom, Markus Ney, Hermann Human Language Technology and Pattern Recognition Computer Science Department RWTH Aachen University Aachen Germany
In spoken language translation a machine translation system takes speech as input and translates it into another language. A standard machine translation system is trained on written language data and expects written ... 详细信息
来源: 评论
Hierarchical Hybrid language models for Open Vocabulary Continuous Speech Recognition using WFST
Hierarchical Hybrid Language models for Open Vocabulary Cont...
收藏 引用
2012 SAPA-SCALE Conference
作者: Shaik, M. Ali Basha Rybach, David Hahn, Stefan Schlüter, Ralf Ney, Hermann Human Language Technology and Pattern Recognition Computer Science Department RWTH Aachen University Aachen52056 Germany
One of the main challenges in automatic speech recognition is recognizing an open, partly unseen vocabulary. To implicitly reduce the out-of-vocabulary (OOV) rate, hybrid vocabularies consisting of full-words and sub-... 详细信息
来源: 评论
The RWTH Aachen Speech Recognition and Machine Translation System for IWSLT 2012  9
The RWTH Aachen Speech Recognition and Machine Translation S...
收藏 引用
9th International Workshop on Spoken language Translation, IWSLT 2012
作者: Peitz, Stephan Mansour, Saab Freitag, Markus Feng, Minwei Huck, Matthias Wuebker, Joern Nuhn, Malte Nußbaum-Thom, Markus Ney, Hermann Human Language Technology and Pattern Recognition Group Computer Science Department RWTH Aachen University Aachen Germany
In this paper, the automatic speech recognition (ASR) and statistical machine translation (SMT) systems of RWTH Aachen University developed for the evaluation campaign of the International Workshop on Spoken language ... 详细信息
来源: 评论
Sequence Labeling-based Reordering Model for Phrase-based SMT  9
Sequence Labeling-based Reordering Model for Phrase-based SM...
收藏 引用
9th International Workshop on Spoken language Translation, IWSLT 2012
作者: Feng, Minwei Peter, Jan-Thorsten Ney, Hermann Human Language Technology and Pattern Recognition Group Computer Science Department RWTH Aachen University Aachen Germany
For current statistical machine translation system, reordering is still a major problem for language pairs like Chinese-English, where the source and target language have significant word order differences. In this pa... 详细信息
来源: 评论
Non-Stationary Signal Processing and its Application in Speech Recognition
Non-Stationary Signal Processing and its Application in Spee...
收藏 引用
2012 SAPA-SCALE Conference
作者: Tüske, Zoltán Drepper, Friedhelm R. Schlüter, Ralf Human Language Technology and Pattern Recognition Computer Science Department RWTH Aachen University Aachen52056 Germany
The most widely used acoustic feature extraction methods of current automatic speech recognition (ASR) systems are based on the assumption of stationarity. In this paper we extensively evaluate a recently introduced f... 详细信息
来源: 评论
Insertion and deletion models for statistical machine translation
Insertion and deletion models for statistical machine transl...
收藏 引用
2012 Conference of the North American Chapter of the Association for Computational Linguistics: human language Technologies, NAACL HLT 2012
作者: Huck, Matthias Ney, Hermann Human Language Technology and Pattern Recognition Group Computer Science Department RWTH Aachen University AachenD-52056 Germany
We investigate insertion and deletion models for hierarchical phrase-based statistical machine translation. Insertion and deletion models are designed as a means to avoid the omission of content words in the hypothese... 详细信息
来源: 评论
The RWTH Aachen Machine Translation System for WMT 2012  7
The RWTH Aachen Machine Translation System for WMT 2012
收藏 引用
7th Workshop on Statistical Machine Translation, WMT 2012, immediately following the Conference of the North-American Chapter of the Association for Computational Linguistics - human language Technologies, NAACL HLT 2012
作者: Huck, Matthias Peitz, Stephan Freitag, Markus Nuhn, Malte Ney, Hermann Computer Science Department Human Language Technology And Pattern Recognition Group Rwth Aachen University AachenD-52056 Germany
This paper describes the statistical machine translation (SMT) systems developed at RWTH Aachen University for the translation task of the NAACL 2012 Seventh Workshop on Statistical Machine Translation (WMT 2012). We ... 详细信息
来源: 评论