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哼歌识曲

于 2021-01-10 发布 文件大小:26704KB
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代码说明：

  通过语音分帧、端点检测、pitch提取、DTW算法，实现歌曲识别(Through voice framing, endpoint detection, pit extraction, DTW algorithm, song recognition is realized)

文件列表：

哼歌识曲\mfcc\buffer2.m, 451 , 2016-07-06
哼歌识曲\mfcc\DTWmat.m, 1001 , 2017-06-30
哼歌识曲\mfcc\fftOneSide.m, 1942 , 2017-06-25
哼歌识曲\mfcc\frame2mfcc.m, 1499 , 2017-06-30
哼歌识曲\mfcc\frame2pitch.m, 4873 , 2016-04-11
哼歌识曲\mfcc\frame2sampleIndex.m, 128 , 2016-07-06
哼歌识曲\mfcc\frame2volume.m, 310 , 2016-07-06
哼歌识曲\mfcc\freq2pitch.m, 64 , 2016-07-06
哼歌识曲\mfcc\getTriFilterBankParam.m, 1251 , 2006-04-17
哼歌识曲\mfcc\lin2melFreq.m, 425 , 2006-04-17
哼歌识曲\mfcc\mel2linFreq.m, 462 , 2006-04-17
哼歌识曲\mfcc\myAcf2pitch.m, 132 , 2016-07-06
哼歌识曲\mfcc\myFrame2acf.m, 203 , 2016-07-06
哼歌识曲\mfcc\PointDetect.m, 955 , 2016-07-06
哼歌识曲\mfcc\QIEYINGKUANG.m, 1330 , 2017-06-30
哼歌识曲\mfcc\R1.mfc, 1526 , 2017-06-30
哼歌识曲\mfcc\R1.wav, 320044 , 2017-06-30
哼歌识曲\mfcc\R2.mfc, 43442 , 2017-06-30
哼歌识曲\mfcc\R2.wav, 320044 , 2017-06-30
哼歌识曲\mfcc\R3.mfc, 44240 , 2017-06-30
哼歌识曲\mfcc\R3.wav, 240044 , 2017-06-30
哼歌识曲\mfcc\R4.mfc, 11202 , 2017-06-30
哼歌识曲\mfcc\R4.wav, 320044 , 2017-06-30
哼歌识曲\mfcc\R5.mfc, 31426 , 2017-06-30
哼歌识曲\mfcc\R5.wav, 400044 , 2017-06-30
哼歌识曲\mfcc\segmentFind.m, 582 , 2016-07-06
哼歌识曲\mfcc\Test1.m, 2058 , 2017-06-30
哼歌识曲\mfcc\Test1.wav, 320044 , 2017-06-30
哼歌识曲\mfcc\wave2pitch.m, 501 , 2017-06-25
哼歌识曲\mfcc\wave2record.m, 577 , 2016-07-09
哼歌识曲\mfcc\同桌的你.mfc, 1526 , 2017-06-30
哼歌识曲\mfcc\同桌的你.wav, 320044 , 2017-06-30
哼歌识曲\mfcc\回梦游仙.mfc, 43442 , 2017-06-30
哼歌识曲\mfcc\回梦游仙.wav, 320044 , 2017-06-30
哼歌识曲\mfcc\女儿情.mfc, 44240 , 2017-06-30
哼歌识曲\mfcc\女儿情.wav, 240044 , 2017-06-30
哼歌识曲\mfcc\彩虹.mfc, 11202 , 2017-06-30
哼歌识曲\mfcc\彩虹.wav, 320044 , 2017-06-30
哼歌识曲\mfcc\滴答.mfc, 31426 , 2017-06-30
哼歌识曲\mfcc\滴答.wav, 400044 , 2017-06-30
哼歌识曲\参考歌曲\同桌的你_不详_0.wav, 2973740 , 2012-03-31
哼歌识曲\参考歌曲\女儿情_不详_0.wav, 2687020 , 2012-03-31
哼歌识曲\参考歌曲\彩虹_不详_0.wav, 6299692 , 2012-04-05
哼歌识曲\参考歌曲\月亮代表我的心_不详_0.wav, 5185580 , 2012-04-05
哼歌识曲\参考歌曲\梦回游仙_不详_0.wav, 7397420 , 2012-04-05
哼歌识曲\参考歌曲\滴答_不详_0.wav, 8233004 , 2012-04-05
哼歌识曲\参考歌曲\知足_不详_0.wav, 4161580 , 2012-03-31
哼歌识曲\参考歌曲\突然好想你_不详_0.wav, 2433068 , 2012-03-31
哼歌识曲\参考歌曲\童话_不详_0.wav, 2850860 , 2012-03-31
哼歌识曲\端点检测\buffer2.m, 316 , 2017-06-20
哼歌识曲\端点检测\frame2sampleIndex.m, 266 , 2016-07-05
哼歌识曲\端点检测\frame2volume.m, 322 , 2017-04-11
哼歌识曲\端点检测\ly.m, 919 , 2017-06-30
哼歌识曲\端点检测\R0.m, 2520 , 2017-06-30
哼歌识曲\端点检测\SegmentFind.m, 711 , 2017-04-17
哼歌识曲\端点检测\同桌的你.wav, 320044 , 2017-06-30
哼歌识曲\端点检测\回梦游仙.wav, 320044 , 2017-06-30
哼歌识曲\端点检测\女儿情.wav, 240044 , 2017-06-30
哼歌识曲\端点检测\彩虹.wav, 320044 , 2017-06-30
哼歌识曲\端点检测\滴答.wav, 400044 , 2017-06-30
哼歌识曲\mfcc, 0 , 2017-06-30
哼歌识曲\参考歌曲, 0 , 2017-06-15
哼歌识曲\端点检测, 0 , 2017-06-30
哼歌识曲, 0 , 2018-01-22

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  • MFCC-LPCC
    基于MFCC的利用LPCC做的说话人识别论文(Based on the MFCC the use of LPCC do the speaker identification papers)
    2013-05-13 15:54:48下载
    积分：1
  • 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
  • yuchuli
    一种用于语音或者心音去噪和提取包络的预处理方法，对于后面信号处理更加方便(A method for denoising and extract voice or heart sounds envelope pretreatment method, the signal processing is more convenient for the latter)
    2013-10-30 14:32:33下载
    积分：1
  • attentionModel
    attention model for saliency detection.
    2010-02-01 08:58:57下载
    积分：1
  • rebuilt.HumanTimbre_recognition-master
    利用mfcc特性进行语音识别，分类算法为svm。(Speech recognition using MFCC characteristics)
    2018-03-31 11:16:48下载
    积分：1
  • CS-dft
    对一维语音信号，用正交匹配追踪的方法进行重构，首先对其进行了分帧，然后再一帧一帧的重构，最后计算了平均帧重构误差(One-dimensional speech signal reconstruction, orthogonal matching pursuit, the first of its sub-frame, and then again a reconstruction of a final calculation of the average frame reconstruction error)
    2020-10-20 11:07:25下载
    积分：1
  • Voice-conversion
    源－目标说话人声音转换的学位论文：源－目标说话人声音转换则是指将源说话人的语音模式转换成某个指定的特定目标说话人的语音模式，即保持源说话人原有的语音信息内容不变，使转换后的语音具有目标说话人的声音特点。(Source- target speaker voice conversion refers to the source speaker voice patterns into a designated target speaker-specific speech patterns, that is, the source speaker to keep the original voice message unchanged, so that the converted speech with the goal of the speaker s voice characteristics.)
    2011-01-19 22:33:56下载
    积分：1
  • FFTofWaveFile
    这是一个语音的文件的一个FFT转换文件,是用C++写的源程序,相信对大家有用(This is a voice of a paper document conversion FFT is written in C source files, it may be useful to think)
    2006-12-06 09:54:06下载
    积分：1
  • specsub_modified11
    语音唤醒就是在设备待机状态下，用户说出特定的语音指令（唤醒词）使设备进入工作状态或完成某一操作。设备为了实现语音唤醒功能，就需要设备实时监听，也就是实时的录音并分析有没有唤醒词来唤醒设备。评价一个语音唤醒系统的标准有三个：唤醒正确率、误报率、功耗。一般情况下，唤醒正确率越高 ，误报率也越高。好的系统就需要唤醒率高，误报率低，功耗低。(Speech wakeup is when the device is in standby mode, the user speaks a particular voice command (wake up word), so that the device enters the work state or completes an operation. In order to realize the function of speech wakeup, the device needs real-time monitoring, that is, real-time recording and analyzing whether or not wake words are used to wake up the equipment. There are three criteria for evaluating a voice wakeup system: wakeup accuracy, false positive rate, and power consumption. Generally, the higher the correct rate of arousal, the higher the false positive rate. A good system requires high wake-up rate, low false positive rate and low power consumption.)
    2017-08-15 16:45:55下载
    积分：1
  • HHT
    台湾国立中央大学开发的EMD-HHT算法,其中,EMD-HHT的创始人为该中心的主任.(EMD-HHT IS SPECIALLY DESIGNED FOR PROCESSING NONSTATIONARY AND NONLINEAR SIGNALS. IT CAN DECOMPSE SIGNALS AND THEN RECONSTRUCT SIGNALS ACCORDING TO SOME CRITERIA. AFTER THE PROCESS, SIGNALS WOULD HAVE HIGH SIGNALTO NOISE RATIO. IT HAS BEEN APPLIED TO VARIOUS TYPES OF SINALS FROM INDUSTRY AND ACHIEVED GREAT SUCCESS. IT EVOLVES FROM THREE SOURCES: FRANCE SCIENTIST G RILLING, MATLAB FILE EXCHANGE CENTRE BY MR TAN AND TAIWAN NATIONAL CENTRAL UNIVERSITY CENTRE.)
    2009-04-24 11:59:08下载
    积分：1
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