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"""
extract low and high quality spectrogram data.
"""
import argparse
import multiprocessing
from pathlib import Path
from pprint import pprint
import numpy
import pysptk
import pyworld
from tqdm import tqdm
from become_yukarin.dataset.dataset import AcousticFeatureProcess
from become_yukarin.dataset.dataset import WaveFileLoadProcess
from become_yukarin.param import AcousticFeatureParam
from become_yukarin.param import VoiceParam
base_voice_param = VoiceParam()
base_acoustic_feature_param = AcousticFeatureParam()
parser = argparse.ArgumentParser()
parser.add_argument('--input_directory', '-i', type=Path)
parser.add_argument('--output_directory', '-o', type=Path)
parser.add_argument('--sample_rate', type=int, default=base_voice_param.sample_rate)
parser.add_argument('--top_db', type=float, default=base_voice_param.top_db)
parser.add_argument('--pad_second', type=float, default=base_voice_param.pad_second)
parser.add_argument('--frame_period', type=int, default=base_acoustic_feature_param.frame_period)
parser.add_argument('--order', type=int, default=base_acoustic_feature_param.order)
parser.add_argument('--alpha', type=float, default=base_acoustic_feature_param.alpha)
parser.add_argument('--f0_estimating_method', default=base_acoustic_feature_param.f0_estimating_method)
parser.add_argument('--enable_overwrite', action='store_true')
arguments = parser.parse_args()
pprint(dir(arguments))
def generate_file(path):
out = Path(arguments.output_directory, path.stem + '.npy')
if out.exists() and not arguments.enable_overwrite:
return
# load wave and padding
wave_file_load_process = WaveFileLoadProcess(
sample_rate=arguments.sample_rate,
top_db=arguments.top_db,
pad_second=arguments.pad_second,
)
wave = wave_file_load_process(path, test=True)
# make acoustic feature
acoustic_feature_process = AcousticFeatureProcess(
frame_period=arguments.frame_period,
order=arguments.order,
alpha=arguments.alpha,
f0_estimating_method=arguments.f0_estimating_method,
)
feature = acoustic_feature_process(wave, test=True).astype_only_float(numpy.float32)
high_spectrogram = feature.spectrogram
fftlen = pyworld.get_cheaptrick_fft_size(arguments.sample_rate)
low_spectrogram = pysptk.mc2sp(
feature.mfcc,
alpha=arguments.alpha,
fftlen=fftlen,
)
# save
numpy.save(out.absolute(), {
'low': low_spectrogram,
'high': high_spectrogram,
})
def main():
paths = list(sorted(arguments.input_directory.glob('*')))
arguments.output_directory.mkdir(exist_ok=True)
pool = multiprocessing.Pool()
list(tqdm(pool.imap(generate_file, paths), total=len(paths)))
if __name__ == '__main__':
main()
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