mirror of
https://github.com/xiph/opus.git
synced 2025-05-17 08:58:30 +00:00
31 lines
877 B
Python
Executable file
31 lines
877 B
Python
Executable file
#!/usr/bin/python3
|
|
|
|
import lpcnet
|
|
import sys
|
|
import numpy as np
|
|
from keras.optimizers import Adam
|
|
from ulaw import ulaw2lin, lin2ulaw
|
|
|
|
nb_epochs = 10
|
|
batch_size = 32
|
|
|
|
model = lpcnet.new_wavernn_model()
|
|
model.compile(optimizer=Adam(0.001), loss='sparse_categorical_crossentropy', metrics=['sparse_categorical_accuracy'])
|
|
model.summary()
|
|
|
|
pcmfile = sys.argv[1]
|
|
chunk_size = int(sys.argv[2])
|
|
|
|
data = np.fromfile(pcmfile, dtype='int16')
|
|
#data = data[:100000000]
|
|
data = data/32768
|
|
nb_frames = (len(data)-1)//chunk_size
|
|
|
|
in_data = data[:nb_frames*chunk_size]
|
|
#out_data = data[1:1+nb_frames*chunk_size]//256 + 128
|
|
out_data = lin2ulaw(data[1:1+nb_frames*chunk_size]) + 128
|
|
|
|
in_data = np.reshape(in_data, (nb_frames, chunk_size, 1))
|
|
out_data = np.reshape(out_data, (nb_frames, chunk_size, 1))
|
|
|
|
model.fit(in_data, out_data, batch_size=batch_size, epochs=nb_epochs, validation_split=0.2)
|