在python中加载FLAC文件，与scipy或librosa相同
在python中加载FLAC文件，与scipy或librosa相同
提问于 2018-06-12 02:43:08
我想把一些flac声音文件输入到keras模型中。使用twice文件我可以做到(人为的例子，一个音频文件使用两次)
import scipy.io.wavfile
import numpy as np
import keras
from keras.models import Sequential
from keras.layers import Dense, Dropout, Activation
from keras.optimizers import SGD
path = 'path/to/file.wav'
_, audio = scipy.io.wavfile.read(path)
dataset = [audio, audio]
x_train = np.array(dataset)
y_train = keras.utils.to_categorical([0, 1], num_classes=2)
model = Sequential()
model.add(Dense(32, activation='relu', input_shape=x_train[0].shape))
model.add(Dense(2, activation='softmax'))
model.compile(optimizer='rmsprop', loss='categorical_crossentropy', metrics=['accuracy'])
model.fit(x_train, y_train, epochs=10, batch_size=32)我如何使用flac文件来实现这一点呢？
回答 1
Stack Overflow用户
回答已采纳
发布于 2018-06-14 05:29:37
soundfile包可以加载numpy数组兼容格式的flac文件
import numpy as np
import soundfile as sf
import keras
from keras.models import Sequential
from keras.layers import Dense, Dropout, Activation
from keras.optimizers import SGD
path = 'path/to/file.flac'
data, samplerate = sf.read(path)
dataset = [data, data]
x_train = np.array(dataset)
y_train = keras.utils.to_categorical([0, 1], num_classes=2)
model = Sequential()
model.add(Dense(32, activation='relu', input_shape=x_train[0].shape))
model.add(Dense(2, activation='softmax'))
model.compile(optimizer='rmsprop', loss='categorical_crossentropy', metrics=['accuracy'])
model.fit(x_train, y_train, epochs=10, batch_size=32) 可派生的sscce https://www.kaggle.com/morenoh149/flac-keras-hello-world
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https://stackoverflow.com/questions/50804170
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