shithub: opus

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--- a/dnn/lpcnet.py

+++ b/dnn/lpcnet.py

@@ -10,7 +10,7 @@

 import h5py

 import sys

-rnn_units1=128

+rnn_units1=256

 rnn_units2=32

 pcm_bits = 8

 embed_size = 128

@@ -77,7 +77,7 @@

     rnn_in = Concatenate()([cpcm, cexc, rep(cfeat)])

     md = MDense(pcm_levels, activation='softmax')

     gru_out1, _ = rnn(rnn_in)

-    gru_out2, _ = rnn2(gru_out1)

+    gru_out2, _ = rnn2(Concatenate()([gru_out1, rep(cfeat)]))

     ulaw_prob = md(gru_out2)

     model = Model([pcm, exc, feat, pitch], ulaw_prob)

@@ -85,7 +85,7 @@

     dec_rnn_in = Concatenate()([cpcm, cexc, dec_feat])

     dec_gru_out1, state1 = rnn(dec_rnn_in, initial_state=dec_state1)

-    dec_gru_out2, state2 = rnn2(dec_gru_out1, initial_state=dec_state2)

+    dec_gru_out2, state2 = rnn2(Concatenate()([dec_gru_out1, dec_feat]), initial_state=dec_state2)

     dec_ulaw_prob = md(dec_gru_out2)

     decoder = Model([pcm, exc, dec_feat, dec_state1, dec_state2], [dec_ulaw_prob, state1, state2])

--- a/dnn/test_wavenet_audio.py

+++ b/dnn/test_wavenet_audio.py

@@ -59,7 +59,7 @@

 out_data = np.reshape(data, (nb_frames*pcm_chunk_size, 1))

-model.load_weights('wavenet5d0_19.h5')

+model.load_weights('wavenet5e3_60.h5')

 order = 16

-- 

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