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add convolution

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This commit is contained in:
Jean-Marc Valin 2018-06-26 17:14:29 -04:00
parent fd9002e98e
commit f884d7bf18
2 changed files with 12 additions and 5 deletions
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13
dnn/lpcnet.py
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@ -16,15 +16,22 @@ nb_used_features = 37
def new_wavernn_model():
pcm = Input(shape=(None, 2))
pcm = Input(shape=(None, 1))
pitch = Input(shape=(None, 1))
feat = Input(shape=(None, nb_used_features))
conv1 = Conv1D(16, 7, padding='causal')
pconv1 = Conv1D(16, 5, padding='same')
pconv2 = Conv1D(16, 5, padding='same')
cpcm = conv1(pcm)
cpitch = pconv2(pconv1(pitch))
rep = Lambda(lambda x: K.repeat_elements(x, 160, 1))
rnn = CuDNNGRU(rnn_units, return_sequences=True)
rnn_in = Concatenate()([pcm, rep(feat)])
rnn_in = Concatenate()([cpcm, cpitch, rep(feat)])
md = MDense(pcm_levels, activation='softmax')
ulaw_prob = md(rnn(rnn_in))
model = Model([pcm, feat], ulaw_prob)
model = Model([pcm, pitch, feat], ulaw_prob)
return model

4
dnn/train_lpcnet.py
View file

@ -56,7 +56,7 @@ features = np.reshape(features, (nb_frames, feature_chunk_size, nb_features))
features = features[:, :, :nb_used_features]
in_data = np.concatenate([in_data, in_pitch], axis=-1)
#in_data = np.concatenate([in_data, in_pitch], axis=-1)
#with h5py.File('in_data.h5', 'w') as f:
# f.create_dataset('data', data=in_data[:50000, :, :])
@ -66,4 +66,4 @@ checkpoint = ModelCheckpoint('lpcnet1e_{epoch:02d}.h5')
#model.load_weights('wavernn1c_01.h5')
model.compile(optimizer=Adam(0.002, amsgrad=True, decay=2e-4), loss='sparse_categorical_crossentropy', metrics=['sparse_categorical_accuracy'])
model.fit([in_data, features], out_data, batch_size=batch_size, epochs=30, validation_split=0.2, callbacks=[checkpoint])
model.fit([in_data, in_pitch, features], out_data, batch_size=batch_size, epochs=30, validation_split=0.2, callbacks=[checkpoint])