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Desktop
语音识别,有GUI界面，实现0~9数字语音识别(speaker identification)
- 2015-05-21 02:57:26下载
- 积分：1
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VoiceToWord_yysb
简单语音识别源码是一个调用讯飞语音识别SDK的例子源码是一个最纯净的Demo比较容易看懂。实现的是点击按钮开始语音监听，手机需要联网，2/3G的均可，识别后会以Toast的方式提示出来，识别率还是比较高的。之前自己是用别人的Demo总是不成功，是因为，讯飞的SDK想使用是需要APPID的，可能过太长时间久会注销，还有，未通过审核的APPID每天只能试用500次，如果太多人试用，就是达到上限导致无法使用。(A simple speech recognition source code is a call Ifly speech recognition SDK example source code is a demo of the purest easier to understand. The realization of the click button to start the voice listening, mobile phone need to networking, 2/3G can, after the recognition will be prompted by Toast way out, the recognition rate is still relatively high. Before he is with someone else s demo is not always successful, is because the Xunfei SDK to use is appid, may be too long for a long time will be canceled, and not through the audit appid every day can only be tried out 500 times, if too many people tried is reaching the limit to use.)
- 2016-06-11 22:06:15下载
- 积分：1
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VAD-1
C语言实现的端点检测,具有良好的效果,对于做语音识别者来说，是很好的参考(C language implementation of endpoint detection, with good results)
- 2020-12-10 15:19:18下载
- 积分：1
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为均衡带限信号所引起失真的横向或格型自适应均衡器
为均衡带限信号所引起失真的横向或格型自适应均衡器(其中横向FIR系统长M=11), 系统输入是取值为±1的随机序列 ，其均值为零；参考信号 ；信道具有脉冲响应：
式中w用来控制信道的幅度失真(w = 2～4，例如，取w = 2.9,3.1,3.3,3.5等),而且信道受到均值为零、方差为 (例如，取 ，相当于信噪比为30dB)的高斯白噪声 的干扰。试比较基于下列五种算法自适应均衡器在不同信道失真、不同噪声干扰下的收敛情况(对应于每一种情况，在同一坐标下画出其学习曲线)：
横向/格-梯型结构LMS算法[1-4]
横向/格-梯型结构RLS算法[1-4]
()
- 2007-09-12 20:18:58下载
- 积分：1
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HLMSSmatlaabe
这 里主要对LMS算法及一些改进的LMS算法（NLMS算法、变步长LMS算法、变换域LMS算法）之间的不同点进行了比较，，在传统的LMS算法的基础上发 展了LMS算法的应用。另一方面又从RLS算法的分析析中对其与LMS算法的不同特性进行了比较。
(Here the main difference between the LMS algorithm and improved LMS algorithm (NLMS algorithm, variable step size LMS algorithm, the transform domain LMS algorithm) comparison, the traditional LMS algorithm based on the development of the application of the LMS algorithm . On the other hand and from its different characteristics of the LMS algorithm of the analytical analysis of the RLS algorithm.)
- 2012-07-26 11:43:36下载
- 积分：1
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PESQ 用于语音质量评估 ITU提供了代码
PESQ是用于语音质量评估的一种方法，ITU提供了代码(P.862 : Perceptual evaluation of speech quality (PESQ): An objective method for end-to-end speech quality assessment of narrow-band telephone networks and speech codecs)
- 2020-06-19 00:00:02下载
- 积分：1
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FLMS
这是一个很好的频域分块自适应滤波的程序，应用于回声消除上，并与NLMS自适应滤波做了运行速度的比较,FLMS比NLMS快几十倍。(This is a very good frequency-domain block adaptive filtering procedure applied to echo cancellation, and comparison with the NLMS adaptive filter for speed, FLMS several times faster than the NLMS.)
- 2021-05-14 04:30:02下载
- 积分：1
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hmm
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；train.m是训练程序；main.m是训练程序的脚本文件；recog.m是识别程序。(hmm HMM algorithm file using speech recognition in noisy environments. Which is the endpoint detection process vad.m mfcc.m procedure is to calculate the MFCC parameters pdf.m function is calculated for a given observation vector of the Gaussian probability density function of output probability mixture.m is to calculate the observation vector for a HMM state output probability of observation vector is the number of Gaussian mixture per state output probability of the linear combination getparam.m before the calculation of the probability function, backward probability, calibration coefficients and other parameters viterbi.m is Viterbi algorithm implementation baum.m Baum-Welch algorithm to achieve inithmm.m is the initialization parameters train.m is the training program main.m training program is a script file recog.m is to identify procedures.)
- 2010-09-16 20:51:49下载
- 积分：1
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matlabyuyin
matlab在语音信号处理中的使用，包括基频提取，语音识别，语音增强等(The application of MATLAB in speech signal processing including pitch extraction, speech recognition, speech enhancement and so on.It uses matlab.)
- 2017-11-09 18:24:13下载
- 积分：1
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voice-recognition
3、语音特征提取与分类
首先, 待识别语音转化为电信号后输入识别系统, 经过预处理后用数学方法提取语音特征信号, 提取出的语音特征信号可以看成该段语音的模式。(3, the voice feature extraction and classification First, to be recognized voice into electrical signals input recognition system, after pretreatment with a mathematical method to extract speech characteristic signal extracted speech characteristic signal can be seen as the voice segment model.)
- 2014-08-05 15:30:46下载
- 积分：1
