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Importing DSP code from RNNoise

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This commit is contained in:
Jean-Marc Valin 2018-06-24 02:41:36 -04:00
parent c41afe41f0
commit 61c6391c21
13 changed files with 3210 additions and 4 deletions
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19
dnn/train_lpcnet.py
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@ -4,13 +4,20 @@ import lpcnet
import sys
import numpy as np
from keras.optimizers import Adam
from keras.callbacks import ModelCheckpoint
from ulaw import ulaw2lin, lin2ulaw
nb_epochs = 10
batch_size = 32
import tensorflow as tf
from keras.backend.tensorflow_backend import set_session
config = tf.ConfigProto()
config.gpu_options.per_process_gpu_memory_fraction = 0.44
set_session(tf.Session(config=config))
nb_epochs = 40
batch_size = 64
model = lpcnet.new_wavernn_model()
model.compile(optimizer=Adam(0.001), loss='sparse_categorical_crossentropy', metrics=['sparse_categorical_accuracy'])
model.compile(optimizer=Adam(0.0008), loss='sparse_categorical_crossentropy', metrics=['sparse_categorical_accuracy'])
model.summary()
pcmfile = sys.argv[1]
@ -28,4 +35,8 @@ 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)
checkpoint = ModelCheckpoint('wavernn1f_{epoch:02d}.h5')
#model.load_weights('wavernn1c_01.h5')
model.compile(optimizer=Adam(0.002, amsgrad=True, decay=1e-4), loss='sparse_categorical_crossentropy', metrics=['sparse_categorical_accuracy'])
model.fit(in_data, out_data, batch_size=batch_size, epochs=30, validation_split=0.2, callbacks=[checkpoint])