-
Notifications
You must be signed in to change notification settings - Fork 48
/
readdata_07.py
130 lines (105 loc) · 4.44 KB
/
readdata_07.py
1
2
3
4
5
6
7
8
9
10
11
12
13
14
15
16
17
18
19
20
21
22
23
24
25
26
27
28
29
30
31
32
33
34
35
36
37
38
39
40
41
42
43
44
45
46
47
48
49
50
51
52
53
54
55
56
57
58
59
60
61
62
63
64
65
66
67
68
69
70
71
72
73
74
75
76
77
78
79
80
81
82
83
84
85
86
87
88
89
90
91
92
93
94
95
96
97
98
99
100
101
102
103
104
105
106
107
108
109
110
111
112
113
114
115
116
117
118
119
120
121
122
123
124
125
126
127
128
129
130
#-*- coding:utf-8 -*-
#author:zhangwei
import numpy as np
from general_function.file_wav import *
from general_function.file_dict import *
from general_function.feature_extract import *
import random
class DataSpeech():
def __init__(self , path , type):
self.datapath = path
self.type = type
self.slash = '/'
if self.slash != self.datapath[-1]:
self.datapath = self.datapath + self.slash
self.dic_wavlist_thchs30 = {}
self.dic_symbollist_thchs30 = {}
self.symbolnum = 0
self.datanum = 0
self.wavs_data = []
self.list_wavnum_thchs30 = []
self.list_symbolnum_thchs30 = []
self.load_datalist()
self.list_symbol = self.get_symbollist()
pass
def load_datalist(self):
if self.type == 'train':
filename_wavlist_thchs30 = 'thchs30' + self.slash + 'train.wav.lst'
filename_symbollist_thchs30 = 'thchs30' + self.slash + 'train.syllable.txt'
elif self.type == 'dev':
filename_wavlist_thchs30 = 'thchs30' + self.slash + 'cv.wav.lst'
filename_symbollist_thchs30 = 'thchs30' + self.slash + 'cv.syllable.txt'
elif self.type == 'test':
filename_wavlist_thchs30 = 'thchs30' + self.slash + 'test.wav.lst'
filename_symbollist_thchs30 = 'thchs30' + self.slash + 'test.syllable.txt'
else:
pass
self.dic_wavlist_thchs30 , self.list_wavnum_thchs30 = get_wav_list(self.datapath + filename_wavlist_thchs30)
self.dic_symbollist_thchs30 , self.list_symbolnum_thchs30 = get_wav_symbol(self.datapath + filename_symbollist_thchs30)
self.datanum = self.get_datanum()
def get_datanum(self):
num_wavlist_thchs30 = len(self.dic_wavlist_thchs30)
num_symbollist_thchs30 = len(self.dic_symbollist_thchs30)
if num_wavlist_thchs30 == num_symbollist_thchs30:
datanum = num_wavlist_thchs30
else:
datanum = -1
return datanum
def get_data(self , n_start):
filename = self.dic_wavlist_thchs30[self.list_wavnum_thchs30[n_start]]
list_symbol = self.dic_symbollist_thchs30[self.list_symbolnum_thchs30[n_start]]
wavsignal , fs = read_wav_data(self.datapath + filename)
feat_out = []
for i in list_symbol:
n = self.symbol_to_num(i)
feat_out.append(n)
data_input = get_frequency_feature(wavsignal , fs)
data_input = data_input.reshape(data_input.shape[0] , data_input.shape[1] , 1)
data_label = np.array(feat_out)
return data_input , data_label
def data_generator(self , batch_size=8 , audio_length=1600):
labels = []
for i in range(0 , batch_size):
labels.append([0.0])
labels = np.array(labels , dtype=np.float)
while True:
X = np.zeros([batch_size , audio_length , 200 , 1] , dtype=np.float)
y = np.zeros([batch_size , 64] , dtype=np.int16)
input_length = []
label_length = []
for i in range(batch_size):
ran_num = random.randint(0 , self.datanum - 1)
data_input , data_labels = self.get_data(ran_num)
input_length.append([data_input.shape[0]//32])
X[i , 0 : len(data_input)] = data_input
y[i , 0 : len(data_labels)] = data_labels
label_length.append([len(data_labels)])
label_length = np.array(label_length)
input_length = np.array(input_length)
yield [X , y , input_length , label_length] , labels
pass
def get_symbollist(self):
list_symbol = []
with open('dict.txt' , 'r') as fr:
lines = fr.readlines()
for line in lines:
res = line.split()
list_symbol.append(res[0])
list_symbol.append('_')
self.symbolnum = len(list_symbol)
return list_symbol
def symbol_to_num(self , symbol):
if symbol != '':
return self.list_symbol.index(symbol)
else:
return self.symbolnum
def get_symbol_num(self):
return len(self.list_symbol)
if __name__ == '__main__':
datapath = '/home/zhangwei/PycharmProjects/ASR_Thchs30/data_list/'
Data = DataSpeech(path=datapath , type='train')
data_input , data_labels = Data.get_data(0)
print(data_labels.shape)
# aa = Data.data_generator()
# for i in aa:
# print i[0][2]