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using features (except pitch gain which has NaNs for now)

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Jean-Marc Valin 2018-06-26 01:31:44 -04:00
parent b65031ef64
commit 617e462be3
2 changed files with 12 additions and 5 deletions
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11
dnn/lpcnet.py
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@ -12,12 +12,19 @@ import sys
rnn_units=64
pcm_bits = 8
pcm_levels = 2**pcm_bits
nb_used_features = 37
def new_wavernn_model():
pcm = Input(shape=(None, 1))
feat = Input(shape=(None, nb_used_features))
rep = Lambda(lambda x: K.repeat_elements(x, 160, 1))
rnn = CuDNNGRU(rnn_units, return_sequences=True)
rnn_in = Concatenate()([pcm, rep(feat)])
md = MDense(pcm_levels, activation='softmax')
ulaw_prob = md(rnn(pcm))
ulaw_prob = md(rnn(rnn_in))
model = Model(pcm, ulaw_prob)
model = Model([pcm, feat], ulaw_prob)
return model