搜索资源列表
Chinese-Word-Segment-And-POS-Tagger
- 实现了中文分词和词性标注程序。分词方法采用“三词正向最长匹配”。词性标注使用HMM方法，用Viterbi算法实现。“三词正向最长匹配”保持了“正向最长匹配算法”快速的特点，同时提高了分词的准确性。-Chinese word segmentation and implemented procedures for POS tagging. Segmentation Methods, " the longest three-match positive words." POS tag
facerecognition
- 采用OpenCV进行人脸识别，隐马尔科夫链的应用，由混合分量来分割HMM的每个内在状态的所有观测值，运用现有的图像观测值分割为所有嵌入和内部的HMM函数，计算可能的变换矩阵-Using OpenCV for face recognition, hidden Markov chain applications, from the mixed components to split the internal state of each HMM all observations, use of the
HMM
- 基于统计的分词，采用隐马尔可夫模型，并有实验报告-Based on statistics segmentation using hidden Markov models, and there is experimental report
Segmentation
- 用HMM实现的中文分词程序，用C#实现的。-HMM to achieve with the Chinese word segmentation
imdict-chinese-analyzer
- imdict-chinese-analyzer 是 imdict智能词典 的智能中文分词模块，算法基于隐马尔科夫模型(Hidden Markov Model, HMM)，是中国科学院计算技术研究所的ictclas中文分词程序的重新实现（基于Java），可以直接为lucene搜索引擎提供简体中文分词支持。-imdict-chinese-analyzer is a smart imdict Chinese Dictionary smart module segmentation algorithm
HMMforspeechrecogntion
- 一个可执行的HMM语音识别程序例程，实现了对10个数字音的识别程序，包含了HMM语音识别中的分段，MFCC特征提取，Baum-Welch训练，及Viterbi等算法，通过此例程可以很好的理解HMM的算法原理-An executable HMM-based 10 digits speech recogntion program example. this code zip file includes segmentation, MFCC feature extraction, Baum-Welc
Sfenciie
- 分词程序，HMM模型训练，维特特比解码，有说明文档。可直接使用。 -Segmentation process, HMM model training, Viterbi decoding, and documentation. Complete source code can be used directly.
attachments_01-05-2012_12-44-28
- A Tutorial on HMMs. 5. Advantage of HMM on Sequential Data ... Model Toolkit). – HMM toolbox for Matlab ... Speech recognition and segmentation. • Gesture .-A Tutorial on HMMs. 5. Advantage of HMM on Sequential Data ... Model Toolkit). – HMM too
bibliofond_7397
- A Tutorial on HMMs. 5. Advantage of HMM on Sequential Data ... Model Toolkit). – HMM toolbox for Matlab ... Speech recognition and segmentation. • Gesture .-A Tutorial on HMMs. 5. Advantage of HMM on Sequential Data ... Model Toolkit). – HMM too
Rkeyword-choue
- 基于逆向最大匹配算法的分词及基于HMM模型的词性标注系统，包括了未登登录词的识别、数据库的添加等内容。（需要手动修改数据库的路径才可以运行） -Based on the segmentation of the reverse maximum matching algorithm and the HMM-based POS tagging system, including unadvertised login word recognition, and add the database co
fenci
- 利用HMM，针对《1998年人民日报》语料库进行研究，最终实现了中文语句的自动分词-By HMM, research, and ultimately the Chinese statement for the 1998 People' s Daily " Corpus automatic segmentation
nlu_project
- 采用机器学习的方法进行自然语言处理，对中文进行分词和词性标注。分词采用crf模型，词性标注用hmm模型，解码算法为Vertibi算法。本系统使用java语言编写-Using machine learning methods for natural language processing, carried out on the Chinese word segmentation and POS tagging. Segmentation using crf model, tagging with
0nlu_project
- 本系统使用java语言编写,采用机器学习的方法进行自然语言处理，对中文进行分词和词性标注。分词采用crf模型，词性标注用hmm模型，解码算法为Vertibi算法。-The system uses java language, using machine learning methods for natural language processing, for Chinese word segmentation and POS tagging. Segmentation using crf mod
matching-Chinese-word-by-HMM-and-MM
- 该程序为在MFC下开发的正向和反向两种中文分词系统。-The program was developed in MFC under both positive and negative Chinese word segmentation system.
cwsegment-master
- 这是用hmm模型编写的中文分词源码,java 运行环静，只需要解压导入文件，将测试文本更改，便可以测试其效果-This is written in the HMM model of Chinese word segmentation source code, Java running ring is static, only need to unzip the import file, will test the text changes, can then test its effect
New-folder
- 自然语言处理中的隐尔可夫马中文分词方法，利用java实现-NLP, using HMM to automatic word segmentation
CWSS17.1.1.4
- 基于隐马尔科夫模型的中文分词系统，上交ieee专业大一作业，界面一般，主要用于学习，在此分享，注：开发环境python3.5(Based on Hidden Markov model of Chinese word segmentation system, on the IEEE professional freshman job, interface is common, mainly used for learning, in this share, note: development en
hmm机器学习
- HMM(隐马尔科夫模型)是自然语言处理中的一个基本模型，用途比较广泛，如汉语分词、词性标注及语音识别等，在NLP中占有很重要的地位(HMM (hidden Markov model) is a basic model in Natural Language Processing, which is widely used, such as Chinese segmentation, part of speech tagging and speech recognition, and plays
24.HMM
- 通过hmm实现中文分词，并且能自动发现新词的功能(The Chinese word segmentation is realized by HMM, and the function of new words can be automatically found)
Schmidt-Segmentation (HMM heart sound)-Code-master
- Matlab code for the Schmidt HMM-based heart sound segmentation. An example of the implementation of this code can be found in “run_Example_Schmidt_scr ipt.m”. This code is derived from the paper: S. E. Schmidt et al., "Segmentation of heart s