def get_stream(batch_size,
source_window=4000,
target_window=1000,
num_examples=5000):
from fuel.datasets.youtube_audio import YouTubeAudio
data = YouTubeAudio('XqaJ2Ol5cC4')
train_stream = data.get_example_stream()
train_stream = ForceFloatX(train_stream)
window_stream = Window(0,
source_window,
target_window,
overlapping=False,
data_stream=train_stream)
source_stream = FilterSources(window_stream, sources=('features', ))
feats_stream = Mapping(source_stream, mfcc)
targets_stream = FilterSources(window_stream, sources=('targets', ))
targets_stream = Flatten(targets_stream)
stream = Merge((feats_stream, targets_stream),
sources=('features', 'targets'))
#Add a random Scheme?
it_scheme = ConstantScheme(batch_size, num_examples)
batched_stream = Batch(stream, it_scheme, strictness=1)
return batched_stream
def get_sound(name):
data = YouTubeAudio(name)
stream = data.get_example_stream()
it = stream.get_epoch_iterator()
return next(it)[0][:, 0]
