initial commit

dnn/lpcnet.py

@@ -0,0 +1,23 @@
+#!/usr/bin/python3
+
+import math
+from keras.models import Model
+from keras.layers import Input, LSTM, CuDNNGRU, Dense, Embedding, Reshape, Concatenate, Lambda, Conv1D, Multiply, Bidirectional, MaxPooling1D, Activation
+from keras import backend as K
+from mdense import MDense
+import numpy as np
+import h5py
+import sys
+
+rnn_units=256
+pcm_bits = 8
+pcm_levels = 1+2**pcm_bits
+
+def new_wavernn_model():
+    pcm = Input(shape=(None, 1))
+    rnn = CuDNNGRU(rnn_units, return_sequences=True)
+    md = MDense(pcm_levels, activation='softmax')
+    ulaw_prob = md(rnn(pcm))
+    
+    model = Model(pcm, ulaw_prob)
+    return model