Description: Hidden_Markov_model_for_automatic_speech_recognition
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. Serious students are directed to the sources listed below for
a theoretical description of the algorithm. KF Lee (2) offers an
especially good tutorial of how to build a speech recognition system
using hidden Markov models. Platform: |
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Description: HMM的学习问题和解码问题研究
这一模型逐渐被应用到很多领域，
如语音识别、基因关联分析和基因识别、文字识别、图象处理、目标跟踪和信号处理等。
隐马氏模型需要解决三个问题:学习问题、识别问题和解码问题。
-HMM learning problem and decoding study this model being applied to many fields, such as speech recognition, genetic association analysis and gene identification, character recognition, image processing, target tracking and signal processing. Hidden Markov Model of the need to address three issues: learning problems, identify problems and decoding problems. Platform: |
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Description: 自己编写的语音识别程序-基于隐马尔可夫模型的语音识别-I have written the speech recognition program- Based on Hidden Markov Model Speech Recognition Platform: |
Size: 5120 |
Author:小苗 |
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Description: 基于隐而马可夫的连续语音识别中声学模型的建立及其实现-Based on Hidden Markov and continuous speech recognition acoustic model and its realization Platform: |
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Author:王岐学 |
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Description: ：为了使应力变异在顽健语音识别系统中能够达到较好的识别效果，研究了基于隐马
尔可夫模型(HMM)的自适应技术，提出了将最大后验概率(MAP)和最大似然回归方法(MLLR)用
于应力变异语音的自适应中。实验结果表明，与基本系统相比，两种方法均有效地提高系统识别
率。以SD为初始模型的最大后验概率方法在150个训练样本时识别效果最好，可以达到90．4％ 。-: In order to stress variation in the robustness of speech recognition system can achieve better recognition results, based on Hidden Markov Model (HMM) of adaptive technology, put forward a maximum a posteriori probability (MAP) and Maximum Likelihood regression (MLLR) for the stress of the adaptive variation in voice. The experimental results show that compared with the basic system, both methods are effective to improve the system recognition rate. SD as the initial model to the maximum a posteriori probability method in 150 training samples to identify the best, can reach 90.4 . Platform: |
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Author:尹江波 |
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Description: 非常有用，功能强大的基于隐马尔科夫模型的语音识别工具箱，可在此基础上进行再开发，对于从事语音信号处理的工作人员有很好的参考价值。-Very useful and powerful hidden Markov model based speech recognition toolkit, can be re-developed on this basis, in the speech signal processing for the staff have a good reference value. Platform: |
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Author:李娜 |
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Description: 基于隐马尔可夫模型的语音单字识别研究：本文针对线性模型在语音识别中的不足, 进行了隐马尔可夫模型(HMM)在
语音单字识别中的研究,主要对观察输出概率求解、 最佳状态序列寻找、 参数估计和
模型参数的选择进行了探讨.-Based on hidden Markov model speech word recognition: the lack of the linear model in speech recognition, hidden Markov model (HMM) speech word recognition, mainly on the observation of the output probability for solving the most best state sequence search, the choice of the parameter estimation and model parameters are discussed. Platform: |
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Author:郭粉玉 |
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Description: HTK是英国剑桥大学开发的一套基于C语言的隐马尔科夫模型工具箱，主要应用于语音识别、语音合成的研究，也被用在其他领域，如字符识别和DNA排序等。HTK是重量级的HMM版本。-Cambridge University HTK is a C-based language developed by the Hidden Markov Model Toolkit, mainly used in speech recognition, speech synthesis research, has also been used in other areas, such as character recognition and DNA sequencing. HTK HMM is the heavyweight version. Platform: |
Size: 2204672 |
Author:LiJiancheng |
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Description: 一种基于隐马尔科夫模型的孤立词的的语音识别实验，可以试验0到9的数字语音识别。-An isolated word speech recognition experiment based on the hidden Markov model, can test 0 to 9 digit speech recognition. Platform: |
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Author:裴安山 |
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Description: HTKbook 3.4
包括所有的HTK 语言的用法以及samples(HTK is a toolkit for building Hidden Markov Models (HMMs). HMMs can be used to model
any time series and the core of HTK is similarly general-purpose. However, HTK is primarily
designed for building HMM-based speech processing tools, in particular recognisers. Thus, much of
the infrastructure support in HTK is dedicated to this task. As shown in the picture above, there
are two major processing stages involved. Firstly, the HTK training tools are used to estimate
the parameters of a set of HMMs using training utterances and their associated transcriptions.
Secondly, unknown utterances are transcribed using the HTK recognition tools.) Platform: |
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Author:lanlan0909
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Description: 基于动态时间规整与隐马尔科夫模型的自动语音识别系统(Automatic speech recognition system based on dynamic time warping and hidden Markov model) Platform: |
Size: 543744 |
Author:llb3112040011
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Search - Hidden Markov Model-based speech recognition