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import os
from pathlib import Path
import argparse
import numpy as np
from data_utils import get_fbanks , train_test_split
np.random.seed(42)
def check_test_size(value):
if not 0 < float(value) < 0.31:
raise argparse.ArgumentTypeError("Test size must be a float between 0 and 0.3 .")
return float(value)
def assert_out_dir_exists(output_path, index):
dir_ = os.path.join(output_path, str(index))
if not os.path.exists(dir_):
os.makedirs(dir_)
print('Created directory {}'.format(dir_))
else:
print('Directory {} already exists'.format(dir_))
return dir_
def main(base_path, output_path, test_size):
speaker_dirs = [f for f in Path(base_path).iterdir() if f.is_dir()]
for id , speaker_dir in enumerate(speaker_dirs):
speaker_id = speaker_dir.name
print(f'Processing speaker ID: {speaker_id}')
index_target_dir = assert_out_dir_exists(output_path, id)
sample_counter = 0
files_ = list(speaker_dir.glob('**/*.flac'))
for f in files_:
fbanks = get_fbanks(str(f))
if fbanks is None:
continue
num_frames = fbanks.shape[0]
# Sample sets of 64 frames each
file_sample_counter = 0
start = 0
while start < num_frames + 64:
slice_ = fbanks[start:start + 64]
if slice_ is not None and slice_.shape[0] == 64:
assert slice_.shape[0] == 64
assert slice_.shape[1] == 64
assert slice_.shape[2] == 1
np.save(os.path.join(index_target_dir, f'{sample_counter}.npy'), slice_)
file_sample_counter += 1
sample_counter += 1
start = start + 64
print(f'Done for speaker ID: {speaker_id}, Samples from this file: {file_sample_counter}')
print(f'Done for speaker ID: {speaker_id}, total number of samples for this ID: {sample_counter}')
print('')
print('All done, YAY! Look at the files')
train_test_split(output_path, test_size)
if __name__ == '__main__':
parser = argparse.ArgumentParser(description="Extract filter banks from audio files.")
parser.add_argument('--input', default = "./LibriSpeech/train-clean-100", type=str, help='Input folder containing the audio files.')
parser.add_argument('--out', default = "./fbannks", type=str, help='Output folder to save the extracted features.')
parser.add_argument('--test_size', default =0.05, type=check_test_size, help='Test size.')
args = parser.parse_args()
main(args.input, args.out, args.test_size)
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