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Remove the need for useless exc and pred files

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This commit is contained in:
Jean-Marc Valin 2018-12-01 12:05:23 -05:00
parent b05f950e38
commit 91d90676e1
3 changed files with 11 additions and 21 deletions
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9
dnn/train_lpcnet.py
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@ -56,10 +56,8 @@ model, _, _ = lpcnet.new_lpcnet_model()
model.compile(optimizer='adam', loss='sparse_categorical_crossentropy', metrics=['sparse_categorical_accuracy'])
model.summary()
exc_file = sys.argv[1] # not used at present
feature_file = sys.argv[2]
pred_file = sys.argv[3] # LPC predictor samples. Not used at present, see below
pcm_file = sys.argv[4] # 16 bit unsigned short PCM samples
feature_file = sys.argv[1]
pcm_file = sys.argv[2] # 16 bit unsigned short PCM samples
frame_size = 160
nb_features = 55
nb_used_features = model.nb_used_features
@ -96,8 +94,7 @@ features = np.reshape(features, (nb_frames*feature_chunk_size, nb_features))
# Note: the LPC predictor output is now calculated by the loop below, this code was
# for an ealier version that implemented the prediction filter in C
upred = np.fromfile(pred_file, dtype='int16')
upred = upred[:nb_frames*pcm_chunk_size]
upred = np.zeros((nb_frames*pcm_chunk_size,), dtype='int16')
# Use 16th order LPC to generate LPC prediction output upred[] and (in
# mu-law form) pred[]