def main():
parser = get_parser()
args = parser.parse_args()
logfmt = "%(asctime)s (%(module)s:%(lineno)d) %(levelname)s: %(message)s"
if args.verbose > 0:
logging.basicConfig(level=logging.INFO, format=logfmt)
else:
logging.basicConfig(level=logging.WARN, format=logfmt)
logging.info(get_commandline_args())
with kaldiio.ReadHelper(args.rspecifier,
segments=args.segments) as reader, \
file_writer_helper(args.wspecifier,
filetype=args.filetype,
write_num_frames=args.write_num_frames,
compress=args.compress,
compression_method=args.compression_method
) as writer:
for utt_id, (_, array) in reader:
array = array.astype(numpy.float32)
if args.normalize is not None and args.normalize != 1:
array = array / (1 << (args.normalize - 1))
spc = spectrogram(x=array,
n_fft=args.n_fft,
n_shift=args.n_shift,
win_length=args.win_length,
window=args.window)
writer[utt_id] = spc
def test_compatible_with_espnet1():
layer = LogSpectrogram(n_fft=16, hop_length=4)
x = torch.randn(1, 100)
y, _ = layer(x, torch.LongTensor([100]))
y = y.numpy()[0]
y2 = np.log10(spectrogram(x[0].numpy(), n_fft=16, n_shift=4))
np.testing.assert_allclose(y, y2, rtol=0, atol=1e-4)