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一种简单有效的基于动态时变语音识别源码
对于大多数研究者来说,寻找能够匹配二重时间序列信号的最佳途径是很重要的,因为它有许多重要的应用需求.DTW是实现这项工作的显著技术,尤其在语音识别技术领域,在这里一个测试信号被按照参照模板拉伸或压缩,
,Searching for the best path that matches two time-series signals is the main task for many researchers, because of its importa
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:建立了一个基于HMM 算法的非特定人语音识别系统,阐述了具体实现过程,包括预处理、特征参数的提取及模板的匹配-: The establishment of a non-specific algorithm based on HMM Speech Recognition System, describes a specific implementation process, including preprocessing, feature extraction and template para
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Profile hidden Markov models (profile HMMs) can be used to do sensitive database searching using statistical descr iptions of a sequence family s consensus. HMMER is a freely distributable implementation of profile HMM software for protein sequence a
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HMM模型,用C语言实现的,可以用于模式识别-HMM model, with the C language implementation, and can be used for pattern recognition
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HTS语音合成系统的设计和实现,是日本人的博士论文,做hmm based 语音合成。-HTS speech synthesis system design and implementation 。it is a doctoral thesis, about hmm based speech synthesis.
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HMMC代码实现,可以给些ANN辅助实现方面的参考意见啊-HMMC code implementation, can give some support to achieve aspects of ANN inputs to ah
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hmm文件时运用HMM算法实现噪声环境下语音识别的。其中vad.m是端点检测程序;mfcc.m是计算MFCC参数的程序;pdf.m函数是计算给定观察向量对该高斯概率密度函数的输出概率;mixture.m是计算观察向量对于某个HMM状态的输出概率,也就是观察向量对该状态的若干高斯混合元的输出概率的线性组合;getparam.m函数是计算前向概率、后向概率、标定系数等参数;viterbi.m是实现Viterbi算法;baum.m是实现Baum-Welch算法;inithmm.m是初始化参数;trai
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整理好的基于HMM语音识别系统(matlab实现)-Tidied HMM-based speech recognition system (matlab implementation)
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比较详尽的介绍了语音识别系统的实现过程,以及相关技术。
端点检测:基于短时能量和短时平均过零率的端点检测和基于倒谱特征的端点检测
特征参数提取:LPCC和MFCC
参数模板存储:HMM和N_Gram
识别阶段:DWT
各阶段的相关技术都给了详细的介绍,绝对是好东西!-More detailed introduction to the speech recognition system implementation process and related technologie
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一个HMM的Matlab实现方法,可实现孤立词语音识别-Matlab implementation of a HMM methods, an isolated word speech recognition can be achieved
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hmm算法用c语言实现,容易运行 很不错的程序啊-HMM algorithm in c language implementation
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HMM的c语言详细实现过程,以及hmm的思想介绍和实现-HMM and c language implementation process in detail,And hmm, introduction and implementation
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就目前三种主流的语音识别算法:动态时间规(DTW)、隐马尔科夫模型(HMM)和人工神经网络(ANN)。分析它们的原理、特点及实现过程,对 DTW 的语音识别进行实验,通过对比分析三种算法的特点,结合本文研究的实际情况,选择 DTW 作为研究的重点,提出利用遗传算法对其进行改进。
-The three mainstream speech recognition algorithms: Dynamic Time Regulations (DTW), hidden Markov model (HM
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hmm语音识别系统的matlab实现,包括所需函数程序。(Matlab implementation of HMM Speech Recognition)
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