Dataset statistics


In [35]:
import numpy as np
import pandas as pd
import librosa
from tqdm import tqdm

In [36]:
wavlist = '/data/hktxt/AISHELL-2/iOS/data/wav.scp'  # wav files list
trans = '/data/hktxt/AISHELL-2/iOS/data/trans.txt'  # transition
spk_info = '/data/hktxt/AISHELL-2/iOS/data/spk_info.txt' #speaker info

In [37]:
wav = pd.read_csv(wavlist, header=None, sep="\s+", names=["label","file"])

In [38]:
wav


Out[38]:
label file
0 IC0001W0001 wav/C0001/IC0001W0001.wav
1 IC0001W0002 wav/C0001/IC0001W0002.wav
2 IC0001W0003 wav/C0001/IC0001W0003.wav
3 IC0001W0004 wav/C0001/IC0001W0004.wav
4 IC0001W0005 wav/C0001/IC0001W0005.wav
5 IC0001W0006 wav/C0001/IC0001W0006.wav
6 IC0001W0007 wav/C0001/IC0001W0007.wav
7 IC0001W0008 wav/C0001/IC0001W0008.wav
8 IC0001W0009 wav/C0001/IC0001W0009.wav
9 IC0001W0010 wav/C0001/IC0001W0010.wav
10 IC0001W0011 wav/C0001/IC0001W0011.wav
11 IC0001W0012 wav/C0001/IC0001W0012.wav
12 IC0001W0013 wav/C0001/IC0001W0013.wav
13 IC0001W0014 wav/C0001/IC0001W0014.wav
14 IC0001W0015 wav/C0001/IC0001W0015.wav
15 IC0001W0016 wav/C0001/IC0001W0016.wav
16 IC0001W0017 wav/C0001/IC0001W0017.wav
17 IC0001W0018 wav/C0001/IC0001W0018.wav
18 IC0001W0019 wav/C0001/IC0001W0019.wav
19 IC0001W0020 wav/C0001/IC0001W0020.wav
20 IC0001W0021 wav/C0001/IC0001W0021.wav
21 IC0001W0022 wav/C0001/IC0001W0022.wav
22 IC0001W0023 wav/C0001/IC0001W0023.wav
23 IC0001W0024 wav/C0001/IC0001W0024.wav
24 IC0001W0025 wav/C0001/IC0001W0025.wav
25 IC0001W0026 wav/C0001/IC0001W0026.wav
26 IC0001W0027 wav/C0001/IC0001W0027.wav
27 IC0001W0028 wav/C0001/IC0001W0028.wav
28 IC0001W0029 wav/C0001/IC0001W0029.wav
29 IC0001W0030 wav/C0001/IC0001W0030.wav
... ... ...
1009193 ID2166W0491 wav/D2166/ID2166W0491.wav
1009194 ID2166W0492 wav/D2166/ID2166W0492.wav
1009195 ID2166W0493 wav/D2166/ID2166W0493.wav
1009196 ID2166W0494 wav/D2166/ID2166W0494.wav
1009197 ID2166W0495 wav/D2166/ID2166W0495.wav
1009198 ID2166W0496 wav/D2166/ID2166W0496.wav
1009199 ID2166W0497 wav/D2166/ID2166W0497.wav
1009200 ID2166W0498 wav/D2166/ID2166W0498.wav
1009201 ID2166W0499 wav/D2166/ID2166W0499.wav
1009202 ID2166W0500 wav/D2166/ID2166W0500.wav
1009203 ID2166W0501 wav/D2166/ID2166W0501.wav
1009204 ID2166W0502 wav/D2166/ID2166W0502.wav
1009205 ID2166W0503 wav/D2166/ID2166W0503.wav
1009206 ID2166W0504 wav/D2166/ID2166W0504.wav
1009207 ID2166W0505 wav/D2166/ID2166W0505.wav
1009208 ID2166W0506 wav/D2166/ID2166W0506.wav
1009209 ID2166W0507 wav/D2166/ID2166W0507.wav
1009210 ID2166W0508 wav/D2166/ID2166W0508.wav
1009211 ID2166W0509 wav/D2166/ID2166W0509.wav
1009212 ID2166W0510 wav/D2166/ID2166W0510.wav
1009213 ID2166W0511 wav/D2166/ID2166W0511.wav
1009214 ID2166W0512 wav/D2166/ID2166W0512.wav
1009215 ID2166W0513 wav/D2166/ID2166W0513.wav
1009216 ID2166W0514 wav/D2166/ID2166W0514.wav
1009217 ID2166W0515 wav/D2166/ID2166W0515.wav
1009218 ID2166W0516 wav/D2166/ID2166W0516.wav
1009219 ID2166W0517 wav/D2166/ID2166W0517.wav
1009220 ID2166W0518 wav/D2166/ID2166W0518.wav
1009221 ID2166W0519 wav/D2166/ID2166W0519.wav
1009222 ID2166W0520 wav/D2166/ID2166W0520.wav

1009223 rows × 2 columns


In [39]:
len(wav) # total wav files 1009223


Out[39]:
1009223

wav duration statistics


In [40]:
pth = '/data/hktxt/AISHELL-2/iOS/data/'
dur = {}
for i in tqdm(range(len(wav.file))):
    loc = pth + wav.file[i]
    try:
        #y, sr = librosa.load(loc)
        #dur[loc] = librosa.get_duration(y=y, sr=sr) #suprer slow
        dur[wav.file[i]] = librosa.get_duration(filename=loc) # faster
    except:
        print('Read wav failed.')


100%|██████████| 1009223/1009223 [04:53<00:00, 3439.06it/s]

In [41]:
dur


Out[41]:
{'wav/C0001/IC0001W0001.wav': 2.027,
 'wav/C0001/IC0001W0002.wav': 1.914,
 'wav/C0001/IC0001W0003.wav': 1.914,
 'wav/C0001/IC0001W0004.wav': 2.211,
 'wav/C0001/IC0001W0005.wav': 2.375,
 'wav/C0001/IC0001W0006.wav': 3.316,
 'wav/C0001/IC0001W0007.wav': 1.761,
 'wav/C0001/IC0001W0008.wav': 2.19,
 'wav/C0001/IC0001W0009.wav': 1.904,
 'wav/C0001/IC0001W0010.wav': 2.18,
 'wav/C0001/IC0001W0011.wav': 1.955,
 'wav/C0001/IC0001W0012.wav': 1.801,
 'wav/C0001/IC0001W0013.wav': 2.119,
 'wav/C0001/IC0001W0014.wav': 2.099,
 'wav/C0001/IC0001W0015.wav': 2.876,
 'wav/C0001/IC0001W0016.wav': 1.751,
 'wav/C0001/IC0001W0017.wav': 1.904,
 'wav/C0001/IC0001W0018.wav': 1.669,
 'wav/C0001/IC0001W0019.wav': 1.9549375,
 'wav/C0001/IC0001W0020.wav': 1.71,
 'wav/C0001/IC0001W0021.wav': 1.853,
 'wav/C0001/IC0001W0022.wav': 2.252,
 'wav/C0001/IC0001W0023.wav': 1.914,
 'wav/C0001/IC0001W0024.wav': 2.129,
 'wav/C0001/IC0001W0025.wav': 2.447,
 'wav/C0001/IC0001W0026.wav': 2.037,
 'wav/C0001/IC0001W0027.wav': 2.795,
 'wav/C0001/IC0001W0028.wav': 2.734,
 'wav/C0001/IC0001W0029.wav': 2.16,
 'wav/C0001/IC0001W0030.wav': 4.013,
 'wav/C0001/IC0001W0031.wav': 1.874,
 'wav/C0001/IC0001W0032.wav': 3.174,
 'wav/C0001/IC0001W0033.wav': 2.231,
 'wav/C0001/IC0001W0034.wav': 2.211,
 'wav/C0001/IC0001W0035.wav': 2.764,
 'wav/C0001/IC0001W0036.wav': 2.416,
 'wav/C0001/IC0001W0037.wav': 1.771,
 'wav/C0001/IC0001W0038.wav': 2.272,
 'wav/C0001/IC0001W0039.wav': 1.75,
 'wav/C0001/IC0001W0040.wav': 2.396,
 'wav/C0001/IC0001W0041.wav': 2.272,
 'wav/C0001/IC0001W0042.wav': 1.914,
 'wav/C0001/IC0001W0043.wav': 2.027,
 'wav/C0001/IC0001W0044.wav': 2.324,
 'wav/C0001/IC0001W0045.wav': 1.73,
 'wav/C0001/IC0001W0046.wav': 2.007,
 'wav/C0001/IC0001W0047.wav': 2.119,
 'wav/C0001/IC0001W0048.wav': 1.781,
 'wav/C0001/IC0001W0049.wav': 1.884,
 'wav/C0001/IC0001W0050.wav': 1.914,
 'wav/C0001/IC0001W0051.wav': 2.395,
 'wav/C0001/IC0001W0052.wav': 2.365,
 'wav/C0001/IC0001W0053.wav': 1.996,
 'wav/C0001/IC0001W0054.wav': 3.02,
 'wav/C0001/IC0001W0055.wav': 2.314,
 'wav/C0001/IC0001W0056.wav': 2.211,
 'wav/C0001/IC0001W0057.wav': 2.611,
 'wav/C0001/IC0001W0058.wav': 2.017,
 'wav/C0001/IC0001W0059.wav': 2.057,
 'wav/C0001/IC0001W0060.wav': 2.263,
 'wav/C0001/IC0001W0061.wav': 1.996,
 'wav/C0001/IC0001W0062.wav': 1.975,
 'wav/C0001/IC0001W0063.wav': 2.17,
 'wav/C0001/IC0001W0064.wav': 1.996,
 'wav/C0001/IC0001W0065.wav': 2.539,
 'wav/C0001/IC0001W0066.wav': 2.263,
 'wav/C0001/IC0001W0067.wav': 2.2519375,
 'wav/C0001/IC0001W0068.wav': 2.2310625,
 'wav/C0001/IC0001W0069.wav': 1.751,
 'wav/C0001/IC0001W0070.wav': 2.539,
 'wav/C0001/IC0001W0071.wav': 2.006,
 'wav/C0001/IC0001W0072.wav': 2.498,
 'wav/C0001/IC0001W0073.wav': 2.426,
 'wav/C0001/IC0001W0074.wav': 2.959,
 'wav/C0001/IC0001W0075.wav': 2.99,
 'wav/C0001/IC0001W0076.wav': 2.181,
 'wav/C0001/IC0001W0077.wav': 1.996,
 'wav/C0001/IC0001W0078.wav': 1.925,
 'wav/C0001/IC0001W0079.wav': 2.13,
 'wav/C0001/IC0001W0080.wav': 2.109,
 'wav/C0001/IC0001W0081.wav': 2.59,
 'wav/C0001/IC0001W0082.wav': 3.603,
 'wav/C0001/IC0001W0083.wav': 3.931,
 'wav/C0001/IC0001W0084.wav': 3.573,
 'wav/C0001/IC0001W0085.wav': 4.044,
 'wav/C0001/IC0001W0086.wav': 3.357,
 'wav/C0001/IC0001W0087.wav': 3.399,
 'wav/C0001/IC0001W0088.wav': 3.675,
 'wav/C0001/IC0001W0089.wav': 3.348,
 'wav/C0001/IC0001W0090.wav': 3.787,
 'wav/C0001/IC0001W0091.wav': 3.89,
 'wav/C0001/IC0001W0092.wav': 3.531,
 'wav/C0001/IC0001W0093.wav': 3.921,
 'wav/C0001/IC0001W0094.wav': 3.542,
 'wav/C0001/IC0001W0095.wav': 4.002,
 'wav/C0001/IC0001W0096.wav': 3.378,
 'wav/C0001/IC0001W0097.wav': 3.788,
 'wav/C0001/IC0001W0098.wav': 3.194,
 'wav/C0001/IC0001W0099.wav': 3.706,
 'wav/C0001/IC0001W0100.wav': 2.867,
 'wav/C0001/IC0001W0101.wav': 3.614,
 'wav/C0001/IC0001W0102.wav': 4.177,
 'wav/C0001/IC0001W0103.wav': 4.095,
 'wav/C0001/IC0001W0104.wav': 3.737,
 'wav/C0001/IC0001W0105.wav': 4.044,
 'wav/C0001/IC0001W0106.wav': 3.532,
 'wav/C0001/IC0001W0107.wav': 3.9,
 'wav/C0001/IC0001W0108.wav': 3.256,
 'wav/C0001/IC0001W0109.wav': 3.787,
 'wav/C0001/IC0001W0110.wav': 3.031,
 'wav/C0001/IC0001W0111.wav': 1.986,
 'wav/C0001/IC0001W0112.wav': 2.211,
 'wav/C0001/IC0001W0113.wav': 2.303,
 'wav/C0001/IC0001W0114.wav': 2.345,
 'wav/C0001/IC0001W0115.wav': 2.007,
 'wav/C0001/IC0001W0116.wav': 2.191,
 'wav/C0001/IC0001W0117.wav': 2.273,
 'wav/C0001/IC0001W0118.wav': 1.904,
 'wav/C0001/IC0001W0119.wav': 2.078,
 'wav/C0001/IC0001W0120.wav': 2.775,
 'wav/C0001/IC0001W0121.wav': 4.433,
 'wav/C0001/IC0001W0122.wav': 3.716,
 'wav/C0001/IC0001W0123.wav': 4.474,
 'wav/C0001/IC0001W0124.wav': 3.839,
 'wav/C0001/IC0001W0125.wav': 3.337,
 'wav/C0001/IC0001W0126.wav': 3.552,
 'wav/C0001/IC0001W0127.wav': 5.416,
 'wav/C0001/IC0001W0128.wav': 2.426,
 'wav/C0001/IC0001W0129.wav': 3.03,
 'wav/C0001/IC0001W0130.wav': 4.085,
 'wav/C0001/IC0001W0131.wav': 4.524,
 'wav/C0001/IC0001W0132.wav': 4.668,
 'wav/C0001/IC0001W0133.wav': 4.269,
 'wav/C0001/IC0001W0134.wav': 3.89,
 'wav/C0001/IC0001W0135.wav': 2.856,
 'wav/C0001/IC0001W0136.wav': 3.788,
 'wav/C0001/IC0001W0137.wav': 3.388,
 'wav/C0001/IC0001W0138.wav': 5.661,
 'wav/C0001/IC0001W0139.wav': 6.204,
 'wav/C0001/IC0001W0140.wav': 3.44,
 'wav/C0001/IC0001W0141.wav': 4.832,
 'wav/C0001/IC0001W0142.wav': 2.918,
 'wav/C0001/IC0001W0143.wav': 3.122,
 'wav/C0001/IC0001W0144.wav': 4.074,
 'wav/C0001/IC0001W0145.wav': 4.31,
 'wav/C0001/IC0001W0146.wav': 4.412,
 'wav/C0001/IC0001W0147.wav': 4.043,
 'wav/C0001/IC0001W0148.wav': 4.381,
 'wav/C0001/IC0001W0149.wav': 4.0739375,
 'wav/C0001/IC0001W0150.wav': 4.679,
 'wav/C0001/IC0001W0151.wav': 3.081,
 'wav/C0001/IC0001W0152.wav': 2.897,
 'wav/C0001/IC0001W0153.wav': 3.48,
 'wav/C0001/IC0001W0154.wav': 3.061,
 'wav/C0001/IC0001W0155.wav': 4.545,
 'wav/C0001/IC0001W0156.wav': 5.313,
 'wav/C0001/IC0001W0157.wav': 4.1049375,
 'wav/C0001/IC0001W0158.wav': 2.303,
 'wav/C0001/IC0001W0159.wav': 5.334,
 'wav/C0001/IC0001W0160.wav': 3.194,
 'wav/C0001/IC0001W0161.wav': 3.245,
 'wav/C0001/IC0001W0162.wav': 3.747,
 'wav/C0001/IC0001W0163.wav': 3.777,
 'wav/C0001/IC0001W0164.wav': 5.446,
 'wav/C0001/IC0001W0165.wav': 5.395,
 'wav/C0001/IC0001W0166.wav': 3.685,
 'wav/C0001/IC0001W0167.wav': 6.635,
 'wav/C0001/IC0001W0168.wav': 4.382,
 'wav/C0001/IC0001W0169.wav': 4.31,
 'wav/C0001/IC0001W0170.wav': 3.079,
 'wav/C0001/IC0001W0171.wav': 4.413,
 'wav/C0001/IC0001W0172.wav': 4.506,
 'wav/C0001/IC0001W0173.wav': 4.051,
 'wav/C0001/IC0001W0174.wav': 4.8159375,
 'wav/C0001/IC0001W0175.wav': 3.865,
 'wav/C0001/IC0001W0176.wav': 2.614,
 'wav/C0001/IC0001W0177.wav': 4.33,
 'wav/C0001/IC0001W0178.wav': 2.315,
 'wav/C0001/IC0001W0179.wav': 3.296,
 'wav/C0001/IC0001W0180.wav': 3.917,
 'wav/C0001/IC0001W0181.wav': 2.8519375,
 'wav/C0001/IC0001W0182.wav': 4.909,
 'wav/C0001/IC0001W0183.wav': 5.363,
 'wav/C0001/IC0001W0184.wav': 4.5369375,
 'wav/C0001/IC0001W0185.wav': 2.832,
 'wav/C0001/IC0001W0186.wav': 4.393,
 'wav/C0001/IC0001W0187.wav': 2.594,
 'wav/C0001/IC0001W0188.wav': 3.3999375,
 'wav/C0001/IC0001W0189.wav': 2.759,
 'wav/C0001/IC0001W0190.wav': 2.4499375,
 'wav/C0001/IC0001W0191.wav': 3.741,
 'wav/C0001/IC0001W0192.wav': 2.708,
 'wav/C0001/IC0001W0193.wav': 3.4000625,
 'wav/C0001/IC0001W0194.wav': 3.318,
 'wav/C0001/IC0001W0195.wav': 3.307,
 'wav/C0001/IC0001W0196.wav': 3.245,
 'wav/C0001/IC0001W0197.wav': 3.07,
 'wav/C0001/IC0001W0198.wav': 3.0489375,
 'wav/C0001/IC0001W0199.wav': 3.534,
 'wav/C0001/IC0001W0200.wav': 4.0920625,
 'wav/C0001/IC0001W0201.wav': 2.7900625,
 'wav/C0001/IC0001W0202.wav': 2.717875,
 'wav/C0001/IC0001W0203.wav': 4.3200625,
 'wav/C0001/IC0001W0204.wav': 3.7519375,
 'wav/C0001/IC0001W0205.wav': 3.3889375,
 'wav/C0001/IC0001W0206.wav': 5.0950625,
 'wav/C0001/IC0001W0207.wav': 2.9970625,
 'wav/C0001/IC0001W0208.wav': 3.308,
 'wav/C0001/IC0001W0209.wav': 4.8060625,
 'wav/C0001/IC0001W0210.wav': 3.773125,
 'wav/C0001/IC0001W0211.wav': 4.579125,
 'wav/C0001/IC0001W0212.wav': 3.6380625,
 'wav/C0001/IC0001W0213.wav': 3.39,
 'wav/C0001/IC0001W0214.wav': 7.100125,
 'wav/C0001/IC0001W0215.wav': 3.1009375,
 'wav/C0001/IC0001W0216.wav': 2.1700625,
 'wav/C0001/IC0001W0217.wav': 4.495,
 'wav/C0001/IC0001W0218.wav': 3.7930625,
 'wav/C0001/IC0001W0219.wav': 3.834,
 'wav/C0001/IC0001W0220.wav': 3.5450625,
 'wav/C0001/IC0001W0221.wav': 3.1620625,
 'wav/C0001/IC0001W0222.wav': 2.8730625,
 'wav/C0001/IC0001W0223.wav': 4.2889375,
 'wav/C0001/IC0001W0224.wav': 3.141125,
 'wav/C0001/IC0001W0225.wav': 5.767,
 'wav/C0001/IC0001W0226.wav': 4.599,
 'wav/C0001/IC0001W0227.wav': 3.7109375,
 'wav/C0001/IC0001W0228.wav': 3.896,
 'wav/C0001/IC0001W0229.wav': 3.1730625,
 'wav/C0001/IC0001W0230.wav': 3.6170625,
 'wav/C0001/IC0001W0231.wav': 3.296,
 'wav/C0001/IC0001W0232.wav': 5.974,
 'wav/C0001/IC0001W0233.wav': 5.436,
 'wav/C0001/IC0001W0234.wav': 5.3430625,
 'wav/C0001/IC0001W0235.wav': 6.0459375,
 'wav/C0001/IC0001W0236.wav': 3.5549375,
 'wav/C0001/IC0001W0237.wav': 3.359,
 'wav/C0001/IC0001W0238.wav': 3.8859375,
 'wav/C0001/IC0001W0239.wav': 3.1009375,
 'wav/C0001/IC0001W0240.wav': 3.09,
 'wav/C0001/IC0001W0241.wav': 4.2170625,
 'wav/C0001/IC0001W0242.wav': 3.338,
 'wav/C0001/IC0001W0243.wav': 3.514,
 'wav/C0001/IC0001W0244.wav': 3.193,
 'wav/C0001/IC0001W0245.wav': 4.3100625,
 'wav/C0001/IC0001W0246.wav': 5.292,
 'wav/C0001/IC0001W0247.wav': 7.121,
 'wav/C0001/IC0001W0248.wav': 2.853,
 'wav/C0001/IC0001W0249.wav': 3.865,
 'wav/C0001/IC0001W0250.wav': 3.5250625,
 'wav/C0001/IC0001W0251.wav': 4.3510625,
 'wav/C0001/IC0001W0252.wav': 5.746,
 'wav/C0001/IC0001W0253.wav': 2.739,
 'wav/C0001/IC0001W0254.wav': 2.0560625,
 'wav/C0001/IC0001W0255.wav': 3.5339375,
 'wav/C0001/IC0001W0256.wav': 3.152125,
 'wav/C0001/IC0001W0257.wav': 3.6279375,
 'wav/C0001/IC0001W0258.wav': 2.594,
 'wav/C0001/IC0001W0259.wav': 3.0489375,
 'wav/C0001/IC0001W0260.wav': 3.1929375,
 'wav/C0001/IC0001W0261.wav': 4.744,
 'wav/C0001/IC0001W0262.wav': 1.7149375,
 'wav/C0001/IC0001W0263.wav': 5.4150625,
 'wav/C0001/IC0001W0264.wav': 3.957875,
 'wav/C0001/IC0001W0265.wav': 2.8730625,
 'wav/C0001/IC0001W0266.wav': 2.5209375,
 'wav/C0001/IC0001W0267.wav': 3.307,
 'wav/C0001/IC0001W0268.wav': 3.08,
 'wav/C0001/IC0001W0269.wav': 3.5970625,
 'wav/C0001/IC0001W0270.wav': 4.3920625,
 'wav/C0001/IC0001W0271.wav': 3.4310625,
 'wav/C0001/IC0001W0272.wav': 3.575875,
 'wav/C0001/IC0001W0273.wav': 4.588,
 'wav/C0001/IC0001W0274.wav': 4.506,
 'wav/C0001/IC0001W0275.wav': 2.9559375,
 'wav/C0001/IC0001W0276.wav': 3.772,
 'wav/C0001/IC0001W0277.wav': 3.958,
 'wav/C0001/IC0001W0278.wav': 4.2579375,
 'wav/C0001/IC0001W0279.wav': 3.028,
 'wav/C0001/IC0001W0280.wav': 3.5970625,
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 'wav/C0002/IC0002W0493.wav': 4.192125,
 'wav/C0002/IC0002W0494.wav': 6.8640625,
 'wav/C0002/IC0002W0495.wav': 6.396,
 'wav/C0002/IC0002W0496.wav': 5.022,
 'wav/C0002/IC0002W0497.wav': 3.271,
 'wav/C0002/IC0002W0498.wav': 3.668,
 'wav/C0002/IC0002W0499.wav': 2.5971875,
 'wav/C0003/IC0003W0001.wav': 2.121,
 'wav/C0003/IC0003W0002.wav': 2.183,
 ...}

In [42]:
max(dur.values()) #longest


Out[42]:
19.322

In [43]:
min(dur.values()) #shortest


Out[43]:
0.032

In [44]:
## stati dur
stdur = {'0':0,'1':0,'2':0,'3':0,'4':0,'5':0,'6':0,'7':0,'8':0,'9':0,'10':0,'11':0,'12':0,'13':0,'14':0,'15':0,'16':0,'17':0,'18':0,'19':0}
for value in dur.values():
    if value <= 1:
        stdur['0'] = stdur['0']+1
    elif value > 1 and value < 2:
        stdur['1'] = stdur['1']+1
    elif value >= 2 and value < 3:
        stdur['2'] = stdur['2']+1
    elif value >= 3 and value < 4:
        stdur['3'] = stdur['3']+1
    elif value >= 4 and value < 5:
        stdur['4'] = stdur['4']+1
    elif value >= 5 and value < 6:
        stdur['5'] = stdur['5']+1
    elif value >= 6 and value < 7:
        stdur['6'] = stdur['6']+1
    elif value >= 7 and value < 8:
        stdur['7'] = stdur['7']+1
    elif value >= 8 and value < 9:
        stdur['8'] = stdur['8']+1
    elif value >= 9 and value < 10:
        stdur['9'] = stdur['9']+1
    elif value >= 10 and value < 11:
        stdur['10'] = stdur['10']+1
    elif value >= 11 and value < 12:
        stdur['11'] = stdur['11']+1
    elif value >= 12 and value < 13:
        stdur['12'] = stdur['12']+1
    elif value >= 13 and value < 14:
        stdur['13'] = stdur['13']+1
    elif value >= 14 and value < 15:
        stdur['14'] = stdur['14']+1
    elif value >= 15 and value < 16:
        stdur['15'] = stdur['15']+1
    elif value >= 16 and value < 17:
        stdur['16'] = stdur['16']+1
    elif value >= 17 and value < 18:
        stdur['17'] = stdur['17']+1
    elif value >= 18 and value < 19:
        stdur['18'] = stdur['18']+1
    else:
        stdur['19'] = stdur['19']+1

In [45]:
stdur


Out[45]:
{'0': 129,
 '1': 120219,
 '2': 300849,
 '3': 258813,
 '4': 162054,
 '5': 92979,
 '6': 46219,
 '7': 18309,
 '8': 6293,
 '9': 2118,
 '10': 741,
 '11': 293,
 '12': 106,
 '13': 40,
 '14': 28,
 '15': 15,
 '16': 8,
 '17': 5,
 '18': 4,
 '19': 1}

In [46]:
sum(stdur.values())


Out[46]:
1009223

In [47]:
#plot dur
import matplotlib.pyplot as plt

data = [stdur['0'], stdur['1'], stdur['2'], stdur['3'], stdur['4'], stdur['5'], 
             stdur['6'], stdur['7'], stdur['8'], stdur['9'], stdur['10'], stdur['11'],
             stdur['12'], stdur['13'], stdur['14'], stdur['15'], stdur['16'], stdur['17'],
             stdur['18'], stdur['19']]
labels = ['0','1', '2', '3', '4', '5','6', '7', '8', '9', '10','11', '12', '13', '14', '15','16', '17', '18', '19']

plt.bar(range(len(data)), data, tick_label=labels)
plt.show();



In [48]:
#sigle out less than 1s 
short = {}
for k,v in dur.items():
    if v <= 1:
        short[k] = v

In [51]:
short


Out[51]:
{'wav/C0124/IC0124W0002.wav': 0.982,
 'wav/C0125/IC0125W0001.wav': 0.966,
 'wav/C0125/IC0125W0002.wav': 0.708,
 'wav/C0125/IC0125W0011.wav': 0.88,
 'wav/C0125/IC0125W0017.wav': 0.759,
 'wav/C0128/IC0128W0004.wav': 0.831,
 'wav/C0144/IC0144W0112.wav': 0.992,
 'wav/C0144/IC0144W0500.wav': 0.931875,
 'wav/C0165/IC0165W0005.wav': 0.952,
 'wav/C0287/IC0287W0023.wav': 0.956,
 'wav/C0333/IC0333W0111.wav': 1.0,
 'wav/C0515/IC0515W0043.wav': 0.976,
 'wav/C0605/IC0605W0003.wav': 1.0,
 'wav/C0620/IC0620W0113.wav': 0.768,
 'wav/C0622/IC0622W0021.wav': 0.896,
 'wav/C0651/IC0651W0104.wav': 0.768,
 'wav/C0653/IC0653W0001.wav': 0.896,
 'wav/C0669/IC0669W0061.wav': 0.768,
 'wav/C0669/IC0669W0063.wav': 0.896,
 'wav/C0671/IC0671W0044.wav': 0.896,
 'wav/C0671/IC0671W0065.wav': 0.896,
 'wav/C0671/IC0671W0070.wav': 0.896,
 'wav/C0671/IC0671W0071.wav': 0.896,
 'wav/C0671/IC0671W0081.wav': 0.896,
 'wav/C0671/IC0671W0118.wav': 0.896,
 'wav/C0677/IC0677W0056.wav': 0.768,
 'wav/C0677/IC0677W0059.wav': 0.896,
 'wav/C0677/IC0677W0065.wav': 0.896,
 'wav/C0677/IC0677W0080.wav': 0.768,
 'wav/C0679/IC0679W0038.wav': 0.768,
 'wav/C0679/IC0679W0044.wav': 0.768,
 'wav/C0679/IC0679W0052.wav': 0.64,
 'wav/C0679/IC0679W0064.wav': 0.768,
 'wav/C0679/IC0679W0079.wav': 0.896,
 'wav/C0803/IC0803W0380.wav': 0.032,
 'wav/C9002/IC9002W0003.wav': 0.946,
 'wav/C9012/IC9012W0006.wav': 0.896,
 'wav/C9012/IC9012W0011.wav': 0.896,
 'wav/C9012/IC9012W0022.wav': 0.896,
 'wav/C9012/IC9012W0112.wav': 0.768,
 'wav/C9016/IC9016W0116.wav': 0.896,
 'wav/C9023/IC9023W0008.wav': 0.896,
 'wav/C9023/IC9023W0009.wav': 0.896,
 'wav/C9025/IC9025W0005.wav': 0.896,
 'wav/C9025/IC9025W0113.wav': 0.896,
 'wav/C9029/IC9029W0025.wav': 0.896,
 'wav/C9029/IC9029W0034.wav': 0.64,
 'wav/C9029/IC9029W0120.wav': 0.768,
 'wav/C9029/IC9029W0121.wav': 0.896,
 'wav/C9029/IC9029W0269.wav': 0.896,
 'wav/C9029/IC9029W0331.wav': 0.896,
 'wav/C9029/IC9029W0332.wav': 0.768,
 'wav/C9029/IC9029W0375.wav': 0.896,
 'wav/C9029/IC9029W0433.wav': 0.896,
 'wav/C9029/IC9029W0434.wav': 0.64,
 'wav/C9029/IC9029W0435.wav': 0.896,
 'wav/C9029/IC9029W0436.wav': 0.768,
 'wav/C9042/IC9042W0003.wav': 0.896,
 'wav/C9042/IC9042W0009.wav': 0.896,
 'wav/C9042/IC9042W0011.wav': 0.768,
 'wav/C9044/IC9044W0010.wav': 0.896,
 'wav/C9051/IC9051W0015.wav': 0.9045625,
 'wav/C9052/IC9052W0006.wav': 0.896,
 'wav/C9052/IC9052W0119.wav': 0.896,
 'wav/C9059/IC9059W0470.wav': 0.3415625,
 'wav/C9068/IC9068W0002.wav': 0.896,
 'wav/C9072/IC9072W0002.wav': 0.768,
 'wav/C9072/IC9072W0003.wav': 0.768,
 'wav/C9084/IC9084W0005.wav': 0.768,
 'wav/C9084/IC9084W0012.wav': 0.64,
 'wav/C9084/IC9084W0025.wav': 0.896,
 'wav/C9087/IC9087W0021.wav': 0.768,
 'wav/C9087/IC9087W0022.wav': 0.768,
 'wav/C9087/IC9087W0121.wav': 0.896,
 'wav/C9104/IC9104W0004.wav': 0.896,
 'wav/C9109/IC9109W0003.wav': 0.768,
 'wav/C9109/IC9109W0012.wav': 0.512,
 'wav/C9111/IC9111W0002.wav': 0.896,
 'wav/C9118/IC9118W0017.wav': 0.896,
 'wav/C9120/IC9120W0028.wav': 0.896,
 'wav/C9121/IC9121W0012.wav': 0.896,
 'wav/C9123/IC9123W0004.wav': 0.896,
 'wav/C9123/IC9123W0012.wav': 0.896,
 'wav/C9123/IC9123W0118.wav': 0.896,
 'wav/C9130/IC9130W0113.wav': 0.896,
 'wav/C9144/IC9144W0121.wav': 0.896,
 'wav/C9147/IC9147W0019.wav': 0.768,
 'wav/C9156/IC9156W0006.wav': 0.896,
 'wav/C9156/IC9156W0009.wav': 0.768,
 'wav/C9156/IC9156W0015.wav': 0.896,
 'wav/C9165/IC9165W0004.wav': 0.896,
 'wav/C9165/IC9165W0117.wav': 0.896,
 'wav/C9171/IC9171W0019.wav': 0.896,
 'wav/C9171/IC9171W0114.wav': 0.896,
 'wav/C9193/IC9193W0023.wav': 0.896,
 'wav/C9203/IC9203W0126.wav': 0.896,
 'wav/C9210/IC9210W0111.wav': 0.896,
 'wav/C9212/IC9212W0005.wav': 0.896,
 'wav/C9218/IC9218W0013.wav': 0.896,
 'wav/C9231/IC9231W0113.wav': 0.896,
 'wav/C9231/IC9231W0202.wav': 0.896,
 'wav/C9245/IC9245W0121.wav': 0.896,
 'wav/C9266/IC9266W0001.wav': 0.896,
 'wav/C9303/IC9303W0114.wav': 0.896,
 'wav/C9309/IC9309W0189.wav': 0.64,
 'wav/C9309/IC9309W0190.wav': 0.768,
 'wav/C9309/IC9309W0191.wav': 0.512,
 'wav/C9309/IC9309W0192.wav': 0.512,
 'wav/C9309/IC9309W0193.wav': 0.896,
 'wav/C9309/IC9309W0194.wav': 0.64,
 'wav/C9309/IC9309W0197.wav': 0.896,
 'wav/C9309/IC9309W0202.wav': 0.896,
 'wav/C9309/IC9309W0203.wav': 0.896,
 'wav/C9310/IC9310W0003.wav': 0.896,
 'wav/C9325/IC9325W0001.wav': 0.768,
 'wav/C9653/IC9653W0190.wav': 0.9935,
 'wav/C9653/IC9653W0193.wav': 0.9656875,
 'wav/C9653/IC9653W0194.wav': 0.9658125,
 'wav/D0079/ID0079W0443.wav': 0.541,
 'wav/D0149/ID0149W0001.wav': 0.989,
 'wav/D0171/ID0171W0508.wav': 0.541,
 'wav/D0174/ID0174W0006.wav': 0.953,
 'wav/D0203/ID0203W0003.wav': 0.958,
 'wav/D0205/ID0205W0255.wav': 0.958,
 'wav/D0305/ID0305W0008.wav': 0.91,
 'wav/D0376/ID0376W0255.wav': 0.9510625,
 'wav/D0377/ID0377W0003.wav': 0.852,
 'wav/D0406/ID0406W0226.wav': 0.997,
 'wav/D0473/ID0473W0002.wav': 0.924}

In [52]:
min(short.values())


Out[52]:
0.032

In [53]:
len(short)


Out[53]:
129

In [54]:
#drop less than 1s from wav, not feed into train
wav = pd.read_csv('wav91.csv', sep=',')
twav = wav.copy()
n=0
for i in range(len(wav)):
    if twav.file[i] in short.keys():
        n=n+1
        print('delete: {} {}'.format(n,i))
        twav = twav.drop(i)


delete: 1 61308
delete: 2 61807
delete: 3 61808
delete: 4 61817
delete: 5 61823
delete: 6 63309
delete: 7 71379
delete: 8 71767
delete: 9 81726
delete: 10 142644
delete: 11 165518
delete: 12 255205
delete: 13 299540
delete: 14 307059
delete: 15 307953
delete: 16 322357
delete: 17 323219
delete: 18 331200
delete: 19 331202
delete: 20 332181
delete: 21 332202
delete: 22 332207
delete: 23 332208
delete: 24 332218
delete: 25 332255
delete: 26 335183
delete: 27 335185
delete: 28 335191
delete: 29 335206
delete: 30 336140
delete: 31 336146
delete: 32 336153
delete: 33 336165
delete: 34 336180
delete: 35 397866
delete: 36 496351
delete: 37 501530
delete: 38 501535
delete: 39 501546
delete: 40 501633
delete: 41 503178
delete: 42 506690
delete: 43 506691
delete: 44 507724
delete: 45 507831
delete: 46 509815
delete: 47 509824
delete: 48 509909
delete: 49 509910
delete: 50 510053
delete: 51 510110
delete: 52 510111
delete: 53 510153
delete: 54 510209
delete: 55 510210
delete: 56 510211
delete: 57 510212
delete: 58 515998
delete: 59 516004
delete: 60 516006
delete: 61 517043
delete: 62 520670
delete: 63 521181
delete: 64 521293
delete: 65 525272
delete: 66 529474
delete: 67 531025
delete: 68 531026
delete: 69 537233
delete: 70 537239
delete: 71 537251
delete: 72 538781
delete: 73 538782
delete: 74 538881
delete: 75 547549
delete: 76 550138
delete: 77 550147
delete: 78 551170
delete: 79 553774
delete: 80 554824
delete: 81 555322
delete: 82 556353
delete: 83 556361
delete: 84 556466
delete: 85 560092
delete: 86 566835
delete: 87 568236
delete: 88 572888
delete: 89 572891
delete: 90 572897
delete: 91 577027
delete: 92 577140
delete: 93 579294
delete: 94 579389
delete: 95 590711
delete: 96 596012
delete: 97 599629
delete: 98 600561
delete: 99 603686
delete: 100 610528
delete: 101 610616
delete: 102 617277
delete: 103 628066
delete: 104 637522
delete: 105 640705
delete: 106 640706
delete: 107 640707
delete: 108 640708
delete: 109 640709
delete: 110 640710
delete: 111 640713
delete: 112 640718
delete: 113 640719
delete: 114 641038
delete: 115 648816
delete: 116 675857
delete: 117 675860
delete: 118 675861
delete: 119 718184
delete: 120 754090
delete: 121 765992
delete: 122 767048
delete: 123 782100
delete: 124 783391
delete: 125 833791
delete: 126 870346
delete: 127 870614
delete: 128 885823
delete: 129 919340

In [55]:
len(twav)


Out[55]:
1009094

In [56]:
len(wav)


Out[56]:
1009223

In [57]:
# reindex
twav[61306:61310]


Out[57]:
phase label folder file
61306 1 122 IC0123W0500 wav/C0123/IC0123W0500.wav
61307 1 123 IC0124W0001 wav/C0124/IC0124W0001.wav
61309 1 123 IC0124W0003 wav/C0124/IC0124W0003.wav
61310 1 123 IC0124W0004 wav/C0124/IC0124W0004.wav

In [58]:
# reindex
twav.reset_index(drop=True, inplace=True)

In [59]:
twav[61306:61310]


Out[59]:
phase label folder file
61306 1 122 IC0123W0500 wav/C0123/IC0123W0500.wav
61307 1 123 IC0124W0001 wav/C0124/IC0124W0001.wav
61308 1 123 IC0124W0003 wav/C0124/IC0124W0003.wav
61309 1 123 IC0124W0004 wav/C0124/IC0124W0004.wav

In [60]:
# save reindexing twav for training
## save to csv
dataframe = pd.DataFrame({'phase':twav.phase,'label':twav.label, 'folder':twav.folder, 'file':twav.file})
dataframe.to_csv("droped_wav91.csv", index = False, sep=',')

In [61]:
ttwav = pd.read_csv('droped_wav.csv', sep=',')
ttwav[61306:61310]


Out[61]:
phase label folder file
61306 2 122 IC0123W0500 wav/C0123/IC0123W0500.wav
61307 2 123 IC0124W0001 wav/C0124/IC0124W0001.wav
61308 1 123 IC0124W0003 wav/C0124/IC0124W0003.wav
61309 1 123 IC0124W0004 wav/C0124/IC0124W0004.wav

In [ ]: