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Description: 基于HMM的词性标注程序，包含了HMM思想的核心，稍作修改就可以移植-HMM-based speech tagging process, including the ideological core of HMM, a little modification can be transplant
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Author: kobee |
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Description: HMM model to learn about various algos like vitribri fwd backward etc and their implementation too
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Author: Abhinav Dasu |
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Description: rabinar paper Hmm model
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Author: 郑良 |
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Description: 关于产生红球绿球观察的HMM若干实验和训练H-red or green ball observation generation HMM
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Author: xuanzhisi |
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Description: A document about H-A document about HMM
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Author: Stephan |
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Description: real-time 3D pointing gesture
recognition algorithm for natural human-robot interaction
(HRI). The recognition errors in previous pointing gesture
recognition algorithms are mainly caused by the low performance
of the hands tracking module and by the unreliability
of the direction estimate itself, therefore our proposed algorithm
uses 3D particle filter for achieving reliability in hand
tracking and cascade hidden Markov model (HMM) for a
robust estimate for the pointing direction. When someone
enters the field of view of the camera, his or her face and
two hands are located and tracked using the particle filters.
The first stage HMM takes the hand position estimate and
maps it to a more accurate position by modeling the kinematic
characteristics of finger pointing.
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Author: ALI |
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Description: hmm code source for speaker
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Size: 4096 |
Author: mmor |
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Description: 维特比算法
寻找最可能的隐藏状态序列(Finding most probable sequence of hidden states)
对于一个特殊的隐马尔科夫模型(HMM)及一个相应的观察序列，我们常常希望能找到生成此序列最可能的隐藏状态序列。
-Viterbi algorithm to find the most likely hidden state sequence (Finding most probable sequence of hidden states) for a particular hidden Markov model (HMM) and a corresponding observation sequence, we often want to find the most likely generated the sequence hidden state sequence.
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Size: 52224 |
Author: machinery |
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Description: This first part of the book attempts to provide this information. In this chapter, the basic ideas
of HMMs and their use in speech recognition are introduced. The following chapter then presents a
brief overview of HTK and, for users of older versions, it highlights the main differences in version
2.0 and later. Finally in this tutorial part of the book, chapter 3 describes how a HMM-based
speech recogniser can be built using HTK. It does this by describing the construction of a simple
small vocabulary continuous speech recogniser.-This first part of the book attempts to provide this information. In this chapter, the basic ideas of HMMs and their use in speech recognition are introduced. The following chapter then presents a brief overview of HTK and, for users of older versions, it highlights the main differences in version 2.0 and later. Finally in this tutorial part of the book, chapter 3 describes how a HMM-based speech recogniser can be built using HTK. It does this by describing the construction of a simple small vocabulary continuous speech recogniser.
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Author: static |
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Description: 实现hmm基本算法。此代码实现基本的viterbi算法。有学习功能-The matlab code implements Viterbi algorith to realize HMM s learning.
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Author: 孙先生 |
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Description: 可以运行的HMM算法模型，代码有详细注释-HMM algorithm model can run the code with detailed comments
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Author: nebula |
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Description: 一个HMM模型的c语言实现，可以参考其过程-HMM model of a c-language
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Size: 200704 |
Author: nebula |
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Description: 用matlab仿真0到9十个数字的语音识别
1、对语音的WAV文件和LAB文件进行处理，产生十个文件，每个文件对应于一个数字，存贮着该数字的波形文件。（shujuzhengli.m）
2、分别利用上面十个文件训练出十个HMM模板，具体方法是：首先将语音的波形文件分帧，以128个点为一帧，帧移为64，每一帧通过mfcc.m计算出13个系数，随着波形的长度不同，一个语音文件可以计算得到13*N个系数，截取13*15的矩阵（mfcc系数）用作训练数据。一般一个HMM模板用20组mfcc系数训练，得到初始状态分布、状态转移矩阵、高斯正态分布的均值和方差以及混合矩阵，这就是该语音的特征，存贮下来，识别的时候使用。（trainmfcc.m）
3、识别过程：识别的前面部分与训练相似，都是要计算得到mfcc系数，不同在于，识别时，将计算得到的mfcc 参数分别代入训练得到的HMM模板求出概率，比较出最大概率者，则该模板对应的数字就是识别的数字。(shibiesb.m)
4、用大量语音文件做测试，结果正确率为90 以上。-Speech Recogonition: Mumber 0-9
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Author: Fatso Ding |
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Description: 本文从HMM的基本思想、概念出发，建立了基于网络的HMM异常检测原型。对原型在实际应用环境中产生的问题，提出了对观测对象（数据包头部）进行分段的改进办法，进而建立了具有可操作性的HMM异常检测模型。-From the basic thought and concept of HMM,the article establishes the prototype of HMM anomaly detection based on network.To resolve some problems which produced from the practical application environment,a improved means that partition the observed object to several fields is proposed to improve the prototype,by which we establish the feasible HMM of anomalous detection based on network.
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Author: 陈中 |
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Description: Hidden Markov Models
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Author: Namek |
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Description: hmm, hiden markov models
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Author: Luke |
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Description: this is a cdvd hmm ... a basic paper on this topic
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Author: Abhinav |
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Description: this a cdvd hmm ... a basic paper on this topic
basically deas with mle algorithm-this is a cdvd hmm ... a basic paper on this topic
basically deas with mle algorithm
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Author: Abhinav |
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Description: SUMMARY:
The Algorithms such as SVD, Eigen decomposition, Gaussian Mixture Model, HMM etc. are scattered in different fields. There is the need to collect all such algorithms for quick reference. Also there is the need to view such algorithms in application point of view. Algorithm Collections for Digital Signal Processing Applications using MATLAB attempts to satisfy the above requirement. Also the algorithms are made clear using MATLAB programs.
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Author: Jose Cardenas |
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Description: 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 tagging using HMM method, the Viterbi algorithm. " Three words maximum positive match" to maintain a " positive maximum matching algorithm," Fast features, while improving the accuracy of segmentation.
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Author: paul |
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