助手标题  
全文文献 工具书 数字 学术定义 翻译助手 学术趋势 更多
查询帮助
意见反馈
   sign language recognition 的翻译结果: 查询用时:0.01秒
图标索引 在分类学科中查询
所有学科
计算机软件及计算机应用
中国语言文字
更多类别查询

图标索引 历史查询
 

sign language recognition
相关语句
  手语识别
     Sign Language Recognition Method Based on ANN/HMM
     基于ANN/HMM的手语识别方法
短句来源
     A Method of Sign Language Recognition Based on DTW/ISODATA Algorithm Multilayer-classifier
     一种基于DTW/ISODATA算法的多层分类器手语识别方法
短句来源
     Application of the HMM Method in Sign Language Recognition
     HMM方法在手语识别中的应用
短句来源
     Sign Language Recognition Method Based on ANN/HMM
     基于ANN/HMM的中国手语识别系统
短句来源
     Most sign language recognition systems use HMMs(hidden Markov models) presently.
     目前大部分手语识别系统采用 HMMs(hidden Markov models)作为系统的识别技术 .
短句来源
更多       
  手语识别的
     A Classification Method for Chinese Sign Language Recognition
     一种用于手语识别的中国手语分类方法
短句来源
     Different with the traditional application manner, the expansion of isomorphic word is presented to incorporate the maximum entropy language models into the post-processing of sign language recognition. The approach can effectively improve the recognition performance, and increase by about 1.5% of the accuracy compared with the Trigram model.
     不同于传统的应用方式,本文提出的手语同形词的扩展方法将改进的最大熵语言模型应用在手语识别的后处理中,有效地提高了手语识别的性能,比Trigram模型提高识别率1.5%左右。
     A New-Style Data-Glove Used for Sign Language Recognition
     一种用于手语识别的新型数据手套
短句来源
     The objective of sign language recognition research is to “see” the language of the deaf.
     手语识别的研究目标是让机器“看懂”聋人的语言 .
短句来源
     As the sign language is not used widely, little research on it is held, and the research history of sign language recognition is only about ten years.
     由于手语使用范围不广,因此关于手语的研究较少,手语识别的研究也就只有10多年的历史。
短句来源
更多       
  “sign language recognition”译为未确定词的双语例句
     Design And Implementation Of Plain-hand Chinese Sign Language Recognition System
     中国手语徒手识别系统的设计与实现
     Lip reading is used to enhance the sign language recognition for those words with same gesture but different means.
     对于一些同形异意的手语词汇 ,利用唇读得到的辅助信息可以达到提高识别率的效果 .
短句来源
     Considering the speed and performance of the recognition system, Cyberglove is selected as gesture input device in sign language recognition system, DGMM (dynamic Gaussian mixture model) is used as recognition technique, and hierarchical recognizer is used in recognizing module, which can recognize 274 sign language words coming from the dictionary of Chinese sign language with an accuracy of 97.4%, based on Chinese sign language's own characteristic.
     考虑到系统的实时性及识别效率 ,该系统选取 Cyberglove型号数据手套作为手语输入设备 ,采用 DGMM( dynamicGaussian mixture model)作为系统的识别技术 ,并根据中国手语的具体特点 ,在识别模块中选取了多层识别器 ,可识别中国手语字典中的 2 74个词条 ,识别率为 97.4 % .
短句来源
     Considering the speed and performance of the recognition system, Cyberglove is selected as gesture input device in author's sign language recognition system, Semi continuous Dynamic Gaussian Mixture Model (SCDGMM) is used as recognition technique, and a search scheme based on relative entropy is proposed and is applied to SCDGMM based sign word recognition.
     选取Cyberglove型号数据手套作为手语输入设备 ,采用DGMM (DynamicGaus sianMixtureModel)作为手势词识别技术 ,提出了基于相对熵的搜索策略 ,并将其应用于基于半连续DGMM的手势词识别中以提高手势词识别速度。
短句来源
     And it's approved by experiments that the system can suppress the noise well, it also can solve the problem of lacking efficient feature description method in sign language recognition with plain hand, and be used as online system.
     实验结果表明,本文实现的系统具有较强的抗噪声能力,有效地解决了中国手语徒手识别特征精确提取的问题,具有一定的实时性。
查询“sign language recognition”译词为用户自定义的双语例句

    我想查看译文中含有:的双语例句
例句
为了更好的帮助您理解掌握查询词或其译词在地道英语中的实际用法,我们为您准备了出自英文原文的大量英语例句,供您参考。
  sign language recognition
To date, sign language recognition research has mostly ignored facial expressions that arise as part of a natural sign language discourse, even though they carry important grammatical and prosodic information.
      
In the age of speech and voice recognition technologies, sign language recognition is an essential part of ensuring equal access for deaf people.
      
This paper describes a comprehensive concept for robust visual sign language recognition, which represents the recent developments in this field.
      
The current state in sign language recognition is roughly 30?years behind speech recognition, which corresponds to the gradual transition from isolated to continuous recognition for small vocabulary tasks.
      
Research in the field of sign language recognition has made significant advances in recent years.
      
更多          


Sign language is the language used by deaf-mute, which is a steadier expressive system composed of posture motion assisted by expression pose. And it is the special language communicated by motion/vision. On one hand, sign language recognizer can be used as a translator between healthy person and deaf-mute, which provides better service for deaf mute; on the other hand, as a part of body langUage understanding, sign language recognition can be used as a method for human-computer interaction. In this paper...

Sign language is the language used by deaf-mute, which is a steadier expressive system composed of posture motion assisted by expression pose. And it is the special language communicated by motion/vision. On one hand, sign language recognizer can be used as a translator between healthy person and deaf-mute, which provides better service for deaf mute; on the other hand, as a part of body langUage understanding, sign language recognition can be used as a method for human-computer interaction. In this paper an ANN/HMM-based sign language recognition system is described. Using ANN, feature-mapper on posture, position and orientation is built respectively. In the process of building feature-mapper on posture, multi-feature and multi-classifier fusion algorithm is presented. By experiment, it is shown that ANN/HMM-based sign language recognition system is feasible and effective.

手语是聋哑人使用的语言。它是由手形动作辅之以表倩姿势为符号构成的比较稳定的表达系统,是一种靠动作/视觉交际的特殊的语言。一方面,手语识别可以作为健全人与聋哑人之间的翻译,为聋哑人提供更好的服务;另一方面,作为人体语言理解的一部分,手语识别可作为人机交互的一种手段。该文实现了基于ANN/HMM的手语识别系统,采用ANN方法建立了关于手形、位置、方向的特征映射器,并在建立手形特征映射器的过程中,给出了多特征多分类器融合算法。实验证明,基于ANN/HMM的手语识别系统是可行及实用的。

HMM has been used extensively and successfully in speech recognition.Recently it has attracted more attention in the domain of gesture recognition.This paper gives the survey of the application of HMM in this domain.Combining with Chinese sign language and its characteristics,the future prospect of HMM application in sign language recognition is presented in this paper.

HMM在语音识别中已得到广泛应用。近年来,HMM方法在手语识别领域越来越受到关注。本文综述了HMM方法在该领域应用的情况,并结合中国手语及其具体特点,对HMM方法在手语识别领域中的应用前景进行了展望。

Sign language is the language used by the deaf, which is a comparatively steadier expressive system composed of signs corresponding to postures and motions assisted by facial expression. It is communication using motion/vision. The objective of sign language recognition research is to “see” the language of the deaf. The integration of sign language recognition and sign language synthesis jointly comprise a “human computer sign language interpreter”, which facilitates...

Sign language is the language used by the deaf, which is a comparatively steadier expressive system composed of signs corresponding to postures and motions assisted by facial expression. It is communication using motion/vision. The objective of sign language recognition research is to “see” the language of the deaf. The integration of sign language recognition and sign language synthesis jointly comprise a “human computer sign language interpreter”, which facilitates the interaction between the deaf and their surroundings. The issue of sign language recognition is to recognize dynamic gesture signal, that is, to recognize sign language signal. Considering real time property and recognition performance of the system, Cyberglove is selected as the gesture input device in the system under discussion and DGMM(dynamic Gaussian mixture model) is used as a recognition technique, which models sign language signal by a time varying density function composed of M N Gaussian mixture density function. The system can recognize 274 sign language words coming from the dictionary of Chinese sign language with the accuracy of 98.2%. Compared with the recognition system based on HMM, the recognition rate of DGMM is nearly equal to that of HMM, and the training and recognition speed of DGMM is apparently much faster than that of HMM.

手语是聋人使用的语言 ,是由手形动作辅之以表情姿势由符号构成的比较稳定的表达系统 ,是一种靠动作 /视觉交际的语言 .手语识别的研究目标是让机器“看懂”聋人的语言 .手语识别和手语合成相结合 ,构成一个“人-机手语翻译系统”,便于聋人与周围环境的交流 .手语识别问题是动态手势信号即手语信号的识别问题 .考虑系统的实时性及识别效率 ,系统选取 Cyberglove型号数据手套作为手语输入设备 ,并采用了 DGMM(dynamic Gaussianm ixture m odel)作为系统的识别技术 ,即利用一个随时间变化的具有 M个分量的混合 Gaussian N-元混合密度来模型化手语信号 ,可识别中国手语字典中的 2 74个词条 ,识别率为 98.2 % .与基于 HMM的识别系统比较 ,这种模型的识别精度与 HMM模型的识别精度相当 ,其训练和识别速度比 HMM的训练与识别速度有明显的改善 .

 
<< 更多相关文摘    
图标索引 相关查询

 


 
CNKI小工具
在英文学术搜索中查有关sign language recognition的内容
在知识搜索中查有关sign language recognition的内容
在数字搜索中查有关sign language recognition的内容
在概念知识元中查有关sign language recognition的内容
在学术趋势中查有关sign language recognition的内容
 
 

CNKI主页设CNKI翻译助手为主页 | 收藏CNKI翻译助手 | 广告服务 | 英文学术搜索
版权图标  2008 CNKI-中国知网
京ICP证040431号 互联网出版许可证 新出网证(京)字008号
北京市公安局海淀分局 备案号:110 1081725
版权图标 2008中国知网(cnki) 中国学术期刊(光盘版)电子杂志社