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Philippe Remy authored 2020-04-20 16:22 . libri speech
# Constants.
SAMPLE_RATE = 16000 # not higher than that otherwise we may have errors when computing the fbanks.
# Train/Test sets share the same speakers. They contain different utterances.
# 0.8 means 20% of the utterances of each speaker will be held out and placed in the test set.
TRAIN_TEST_RATIO = 0.8
CHECKPOINTS_SOFTMAX_DIR = 'checkpoints-softmax'
CHECKPOINTS_TRIPLET_DIR = 'checkpoints-triplets'
BATCH_SIZE = 32 * 3 # have to be a multiple of 3.
# Input to the model will be a 4D image: (batch_size, num_frames, num_fbanks, 3)
# Where the 3 channels are: FBANK, DIFF(FBANK), DIFF(DIFF(FBANK)).
NUM_FRAMES = 160 # 1 second ~ 100 frames with default params winlen=0.025,winstep=0.01
NUM_FBANKS = 64
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