language identification
英 [ˈlæŋɡwɪdʒ aɪˌdentɪfɪˈkeɪʃn]
美 [ˈlæŋɡwɪdʒ aɪˌdentɪfɪˈkeɪʃn]
网络 语言辨别; 语种识别; 语言识别; 语言辨识; 语言鉴别
双语例句
- For example," language identification "=>" language specific segmentation "=>" sentence boundary detection "=>" entity detection ( person/ place names etc.)". " language specific segmentation "=>" sentence boundary detection "=>" entity detection ( person/ place names etc.)"." data-id="552571">
例如“语言识别”=>“特定于语言的部分”=>“句子范围检测”=>“实体检测（人员/位置的名称等等）”。 - In GMM-based language identification system, the environment and individual characteristics are always the factors that influence the identification accuracy.
在基于GMM的语种识别系统中，实际环境和个人因素一直是影响识别率提高的因素。 - An auditory-based feature extraction algorithm was developed to improve the recognition performance of language identification algorithms using human auditory characteristics.
为了在语种识别时充分利用人的听感知特性提高识别性能，提出了一种基于听感知模型的特征。 - Factor Analysis in GMM-Based Language Identification
因子分析在基于GMM的自动语种识别中的应用 - Shifted delta cepstra have been widely used in automatic language identification, but only delta cepstrum information is employed.
滑动差分倒谱在自动语言辨识的研究中获得了广泛的应用。 - Language identification in the limit of enumeration
穷举极限内的语言识别 - Overview of Approaches to Automatic Language Identification and Recent Development
自动语言辨识的研究方法及发展概述 - The Inhomogeneous HMM with General Topological Structure and Its Application in Language Identification between Mandarin and English
一般拓扑结构的非齐次隐含马尔科夫模型及其在中、英文语种辨识中的应用 - Language identification is one of important aspects in speech recognition technologies, and has an extensive application foreground.
语言辨识（又称语种识别）技术是语音识别技术的一个重要方向，具有广泛的应用前景。 - Discriminative Training of GMM for Language Identification
基于GMM区分性训练方法的语言辨识系统 - A language identification system includes three parts: feature extraction, modeling and judgment rule.
语言辨识系统主要可分为三个部分，即特征提取、模型建立和判决规则。 - Study on decision level fusion of language identification system
语言辨识系统的决策级融合研究 - Automatic language identification based on GMM-UBM
基于GMM-UBM模型的语言辨识研究 - Language identification is accomplished under the condition of text-independence and speaker-independence, thus it is necessary for language identification to eliminate the individual information of the signal of speech sound of different languages as far as possible so as to achieve a better result of recognition.
语种识别强调在与文本无关和与说话人无关的条件下进行，因而语种识别需要尽量消除语音信号中个体发音的差异，并且尽量找到不同语种的语音间不同的声学特征，从而达到更好的识别效果。 - Classification of speech signals is an important base of the speech recognition, speaker recognition, language identification and speech synthesis, and representation of signals and the choice of distance measures dramatically the performance of the classification of signals.
语音信号分类是语音识别、说话人识别、语种辨识和语音合成的一个重要基础，而信号表示的方式和距离测度的选择，对分类性能影响很大。 - Application of Natural Language Identification in Search Engine
自然语言识别在WWW搜索引擎中的应用 - Automatic Language Identification Using Structure C_nV
基于CnV结构的自动语言辨识研究 - SDC Feature-based Language Identification Using GMM-UBM
基于SDC特征和GMM-UBM模型的自动语种识别 - Language Identification Using Speaker Clustering and Gaussian Mixed Model
基于说话人聚类和高斯混合模型的语言辨识研究 - In study of phonology, language identification system based on pseudo-syllable is built. The speech signal is processed in five steps.
音韵学信息研究中，建立了基于伪音节结构的自动语言辨识系统。 - Through the study of the histories of automatic language identification technology, the paper points out that two important problems of features are seeking for the new efficient feature and the balance between high efficiency and the performing cost.
通过对自动语言辨识技术发展史的研究，本文指出特征研究的两个重点问题是新的高效辨识特征的寻找和辨识率与执行代价之间的平衡。 - Research on Automatic Language Identification System for Internet Speech
关于网络语音的自动语言辨识系统研究 - Language identification is the process of determining the language to which a given utterance belongs by a computer, which is an important research direction in speech recognition.
语种识别是利用计算机对一定长度的语音材料进行处理，判别其所属语言种类的过程，是语音识别的一个重要研究方向。 - This paper studies the key techniques of the Robust Language Identification.
本论文研究的是鲁棒语言辨识的关键技术。 - Nowadays, with the increasingly open international environment and rapid development of network, Language Identification is facing challenges.
如今，日益开放的国际环境和互联网的飞速发展为语种识别带来了新的挑战。 - According to the ideas of modeling on the speech, there are two mainstream categories of language identification: based on acoustic model and based on language model.
根据建模思路的不同，主流的语种识别方法可以分为两大类：基于声学模型的方法和基于语言模型的方法。 - In this thesis, a document image processing system is designed and performed. It can be applied for language identification. The system consists of image preprocessing, layout analysis, and language identification. The main contributions of this dissertation include: ( 1) Back Ground.
本文设计和实现了一个文档图像的文种识别系统，主要研究工作有：（1）课题背景。 - The statistical language identification models represented by the GMM which translate the problem of identification into the problem of estimating the distribution of speech features can get a good identifying effect.
以GMM为代表的概率统计模型将辨识问题转换成对语音特征分布的估计问题，取得了较好的识别效果。 - Language Identification is widely applied in many fields such as network security, authentication and multilingual information service.
语种识别在网络安全、身份验证、多语种信息服务等领域有着广泛的应用。 - Based on GMM for language identification system does not require manual tagging corpus, so it has a good portable.
基于GMM的语种识别系统，不需要人工标注语料，具有良好的移植性，特别适合于中国少数民族语的语种识别。