Description: HMM模型在语音识别中的应用，相信对HMM模型感兴趣的语音或图像等专业人员应该明白价值。-It is about Hidden Markov Models (HMM) method in Speech Recognition research. those interested in HMM or speech/image processing should know it s value. Platform: |
Size: 34074 |
Author:何伟 |
Hits:
Description: This class library contains more than 20 classes including feature extraction algorithms (MFCC, LPCC) and modeling techniques (HMM, GMM, DTW, VQ ) for automatic speech recognition and speaker verification Platform: |
Size: 1405952 |
Author:站长 |
Hits:
Description: 基于HMM的语音识别matlab软件，可防止数据溢出等错误-This speech recognition software based on HMM algorithm.It can prevent many errors such as data overflow effectively. Platform: |
Size: 71680 |
Author:吴昊 |
Hits:
Description: 语音识别配套的VQ及DHMM模型训练程序，C语言，已经定点化，可直接移植到8位MCU或16位DSP中。与目前市面的语音识别玩具的算法基本一致，非常实用，仅供大家参考，别去抢人家饭碗才好。-speech recognition and matching VQ DHMM model training procedures, C language, has been positioned, can be directly transplanted to eight 16-bit MCU or DSP. And the current market speech recognition algorithm toys basically the same, very practical, is for your reference. stealing jobs other people a better life. Platform: |
Size: 6388736 |
Author:xubin |
Hits:
Description: 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: |
Size: 15360 |
Author:aaaaaaa |
Hits:
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: |
Size: 23552 |
Author: |
Hits:
Description: 语音识别重要函数汇集,函数书写严格按照相关论文,是研究语音的重要工具-Speech Recognition brings together the important function, function to write in strict accordance with the relevant papers, is to study an important tool for voice Platform: |
Size: 488448 |
Author:zch |
Hits:
Description: HMM模型应用领域很多，HTM只要是用于语音识别。这是它的basic tutorial.它是用C语言实现的开源软件-HMM model for many applications, HTM as long as it is used for speech recognition. This is its basic tutorial. It is realized by C language open source software Platform: |
Size: 75776 |
Author:CPP |
Hits:
Description: 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 importance in these applications. Dynamic Time-Warping (DTW) is one of the prominent techniques to accomplish this task, especially in speech recognition systems. DTW is a cost minimisation matching technique, in which a test signal is stretched or compressed according to a reference template.
Although there are other advanced techniques in speech recognition such as the hidden Markov modelling (HMM) and artificial neural network (ANN) techniques, the DTW is widely used in the small-scale embedded-speech recognition systems such as those embedded in cell phones. The reason for this is owing to the simplicity of the hardware implementation of the DTW engine, which makes it suitable for many mobile devices. Additionally, the training procedure in DTW is very simple and fast, as compared with the HMM and ANN rivals.
Platform: |
Size: 2658304 |
Author:宋小小 |
Hits:
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: |
Size: 234496 |
Author:尹江波 |
Hits:
Description: HMM matlab 源代码，可用于语音识别，是一种经典的算法，有广泛的应用范围。-HMM matlab source code, can be used for speech recognition is a classical algorithm, a wide range of applications. Platform: |
Size: 35840 |
Author:杨明 |
Hits:
Search - hmm for speech recognition