搜索资源列表
generatesample
- 生成《matlab扩展编程》中对于HMM训练的samples.mat程序，自己编写-Generation ‘matlab programming expansion’ in the HMM training samples.mat procedures, written by myself
hmmfan
- 一个用于 词性标注的 HMM程序。 包含 训练和测试功能。-One for the HMM-speech tagging procedures. Includes training and testing.
ASR_matlab
- 语音识别的MATLAB代码，包括用于测试的语音，实现了利用HMM(隐含马尔可夫)和DTW(动态规划)两种方法的实现。-ASR use HMM and DTW method include wave files use for test and training.
HMM_Training_in_speech
- 改进的HMM训练方法在语音识别中的应用,论文-Improved HMM training methods in speech recognition applications, papers
DTW
- DTW（Dynamic Time Warping，动态时间归整）算法，该算法基于动态规划（DP）的思想，解决了发音长短不一的模板匹配问题，是语音识别中出现较早、较为经典的一种算法。用于孤立词识别，DTW算法与HMM算法在训练阶段需要提供大量的语音数据，通过反复计算才能得到模型参数，而DTW算法的训练中几乎不需要额外的计算。所以在孤立词语音识别中，DTW算法仍然得到广泛的应用。 -DTW (Dynamic Time Warping, dynamic time warping) algorithm
hmm-1.03
- This code implements in C++ a basic left-right hidden Markov model and corresponding Baum-Welch (ML) training algorithm. It is meant as an example of the HMM algorithms described by L.Rabiner (1) and others.-This code implements in C++ a basic
dtkirsch-hmm-v0.2.0-0-g7feffa1
- 这是一个Ruby机器学习项目中本地实现广义隐马尔可夫模型的分类。目前，它能够监督学习和Viterbi解码。-This project is a Ruby gem ( hmm ) for machine learning that natively implements a (somewhat) generalized Hidden Markov Model classifier. At present, it is capable of supervised learning (using la
HMM
- 隐马尔科夫模型源代码，隐马尔科夫模型的训练，输入序列得到隐马尔科夫模型。-Hidden Markov model source code, training of hidden Markov model, the input sequence hidden Markov model.
Ggeneratesampe
- 生成《matlab扩展编程》中对于HMM训练的sammples.mat程序，自己编写，已通过测试。 -Generation " matlab programming expansion" in the HMM training sammples.mat procedures, I have written a complete source code, has been tested.
speech-recognize-HMM-CPP
- 在语音识别中，用隐马尔科夫模型（HMM）进行训练，用C++编写的仿真代码-In speech recognition, hidden Markov model (HMM) for training, simulation code written in C++
HMM-voice-recognition
- 声音识别程序，matlab，有例子，对于学习不错，HMM的，包括训练和识别-Voice recognition program matlab, there are examples of good for learning, HMM, including training and recognition
hmm(train-and-recognize)
- 用于DHMM模型的训练和识别，提供例子测试-Used for DHMM model training and recognition, provide sample testing
hmm
- this is .cc file. hidden markov model. include generate and training source. good for you
HMM
- hmm，包括前向，后向，前向-后向，EM，训练等算法的java实现-hmm, including forward, backward, forward- backward, EM, training algorithm to achieve the java
hmm
- DHMM问题3matlab实现，即给出训练数据，求解（A，B,pi）-Implement of DHMM，i.e，given training data ,estimate (P,Q,pi)
hmm-matlab
- 实现最简单的HMM的模型例子，给定一组观察值，训练HMM的模型；再给出一组观察值，评估出其状态值 -Realize the simplest HMM model example, given a set of observations, training of HMM model To give a set of observations, uate its status value to achieve the simplest HMM model example, given a set
hmm-program
- HMM的示例程序，包含特征样本和产生训练数据的程序，注释详细，适合参考学习-HMM sample program, including feature samples and generator training data, detailed notes for reference study
SpeechRec
- 在孤立词语音识别中，最为简单有效的方法是采用DTW（Dynamic Time Warping，动态时间归整）算法，该算法基于动态规划（DP）的思想，解决了发音长短不一的模板匹配问题，是语音识别中出现较早、较为经典的一种算法，用于孤立词识别。HMM算法在训练阶段需要提供大量的语音数据，通过反复计算才能得到模型参数，而DTW算法的训练中几乎不需要额外的计算。所以在孤立词语音识别中，DTW算法仍然得到广泛的应用。-Isolated word speech recognition, the most s
HMM_VoiceRecognation
- 通过基于HMM的语音识别系统的基本结构,详细介绍了语音信号采集、预处理、MFCC特征参数提取、HMM训练和HMM识别等主要模块的基本原理 并针对实际应用中HMM存在的模型初始化和数据溢出等问题进行分析,引入了一些能提高系统性能的相应措施。-By the basic structure of HMM-based speech recognition system, details the basic principles of audio signal acquisition, preproces
HMM-speech-recognition-
- 这个方法之所以如此流行就在于其固有的统计框架：从有限语音训练集数据中训练出模型近似参数的简单易行；模型可根据特殊的词汇、声音等改变认知系统的大小、种类或模型的架构的灵活多变；实现整个认知系统的简单方便。在这篇解释性的文章中，我们将讲解应用在语音识别中的非常重要的统计方法，并讨论一系列尚未解决的原理性的和实际性的问题，因为他们很重要并对不同系统实现的性能有很大影响。-This method is so popular lies in its inherent statistical framewo