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HTS-2.1_for_HTK-3.4
- HTS version 2.1 includes hidden semi-Markov model (HSMM) training/adaptation/synthesis, speech parameter generation algorithm considering global variance (GV), SMAPLR/CSMAPLR adaptation, and other minor new features.
2028
- OTOMATİ K KONUŞ MA TANIMA ALGORİ TMALARININ UYGULAMALARI Kö ksal Ö CAL Ankara Ü niversitesi Fen Bilimleri Enstitüsü Elektronik Mühendisliğ i Anabilim Dalı Danı ş man : Yrd. Doç . Dr. H. Gö kh
MarkovChain
- 模擬馬可夫矩陣，可以看出穩態機率的值的趨勢-Simulated Markov matrix, we can see the trend of the value of steady-state probability
hmm
- 隐马尔可夫模型源代码，实现了最基本的三个算法-Hidden Markov model source code, to achieve the most basic of the three algorithms
new_hmm
- 隐马尔可夫模型，适用于DTW定点算法寻址。有很强的功能性-Hidden Markov model for fixed-point algorithm for addressing DTW. Has a strong functional ~ ~
hmm_training_DTW
- 隐马尔可夫模型的寻址型DTW定点算法，测试可以通过，欢迎大家分享学习~-Hidden Markov Model-based DTW fixed-point algorithm for addressing the test can be welcome to share learning ~
pdf
- 关于语音识别的论文，有关隐马尔科夫模型的-Papers on speech recognition, the Hidden Markov Model
VoiceBox_HMM
- Toolbox for speech recognition by using Mel-Frequency and Hidden Markov Modelling
htkbook
- 该书详细介绍了语音识别工具箱htk的使用方法和隐马尔科夫模型用于语音识别的原理，对工具箱中各个主要函数的原理及参数说明都有详细的说明。-The book details the use of speech recognition toolkit htk methods and hidden Markov models for speech recognition in principle, each of the major functions of the toolbox to the pri
weitebisuanfa
- 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
HTK-Presentation
- The Hidden Markov Model Toolkit (HTK) is a portable toolkit for building and manipulating hidden Markov models. HTK is primarily used for speech recognition research although it has been used for numerous other applications including research into sp
HMMall
- Speaker recognition using HMM(Hidden Markov Model)
hmm
- hidden markov model toolkit
markov
- MRF classification for remote sensing images
MFCC
- 基于MFCC参数和HMM的低空目标声识别方法研究 ，隐马尔科夫研究语音识别检测敌机-HMM-based MFCC parameters and low-altitude target identification method of sound, speech recognition, hidden Markov detection of enemy aircraft
Continuous-Speech-Recognition
- 连续语音识别资料，包括各种隐性马尔科夫算法。-Continuous speech recognition, including a variety of hidden Markov algorithm.
gmm
- 这是一章详解高斯模型的文章，非常适合初学者，理论思路讲解清晰，也是学习隐马尔科夫模型的准备知识。-This is an article Detailed Gaussian model, very suitable for beginners, theoretical ideas to explain clearly, but also to learn a ready knowledge of the hidden Markov model.
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.
Speech-Recognition-in-MATLAB
- 介绍了MATLAB 环境下的语音识别系统, 阐述了具体的实现过程。采用离散隐马尔科夫模型, 为提高识别率采用男女2 套参数, 对离散隐马尔科夫模型在实际语音识别系统中遇到的问题进行分析, 并给出相应的解决办法-】A digital speech recognition system and its realization course are introduced in the MATLAB environment. The DHMM(Discrete Hidden Markov Model
study-on-speech-
- 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