def compute_spectrum():
parser = get_parser()
args = parser.parse_args()
config = {}
config['sample_rate'] = float(args.sample_rate)
config['output_type'] = int(args.output_type)
config['window_length'] = args.window_length
config['frame_length'] = args.frame_length
spectrum = Spectrum.params(config).instantiate()
with kaldiio.ReadHelper(args.rspecifier,
segments=args.segments) as reader, \
KaldiWriter(args.wspecifier, write_num_frames=args.write_num_frames,
compress=args.compress, compression_method=args.compression_method) as writer:
for utt_id, (sample_rate, array) in reader:
if sample_rate != args.sample_rate:
args.sample_rate = sample_rate
array = array.astype(np.float32)
audio_data = tf.constant(array, dtype=tf.float32)
spectrum_test = spectrum(audio_data, args.sample_rate)
sess = tf.compat.v1.Session()
spectrum_feats = spectrum_test.eval(session=sess)
writer[utt_id] = spectrum_feats
def test_spectrum(self):
wav_path = str(
Path(PACKAGE_ROOT_DIR).joinpath('layers/ops/data/sm1_cln.wav'))
with self.cached_session(use_gpu=False, force_gpu=False):
read_wav = ReadWav.params().instantiate()
input_data, sample_rate = read_wav(wav_path)
spectrum = Spectrum.params({'window_length': 0.025}).instantiate()
spectrum_test = spectrum(input_data, sample_rate)
output_true = np.array(
[[-16.863441, -16.910473, -17.077059, -16.371634, -16.845686],
[-17.922068, -20.396345, -19.396944, -17.331493, -16.118851],
[-17.017776, -17.551350, -20.332376, -17.403994, -16.617926],
[-19.873854, -17.644503, -20.679525, -17.093716, -16.535091],
[-17.074402, -17.295971, -16.896650, -15.995432, -16.560730]])
self.assertEqual(tf.rank(spectrum_test).eval(), 2)
self.assertAllClose(spectrum_test.eval()[4:9, 4:9], output_true)
def test_spectrum(self):
wav_path = str(
Path(PACKAGE_ROOT_DIR).joinpath('layers/ops/data/sm1_cln.wav'))
with self.cached_session(use_gpu=False, force_gpu=False):
read_wav = ReadWav.params().instantiate()
input_data, sample_rate = read_wav(wav_path)
spectrum = Spectrum.params({
'window_length': 0.025,
'snip_edges': 1
}).instantiate()
spectrum_test = spectrum(input_data, sample_rate)
output_true = np.array(
[[9.819611, 2.84503, 3.660894, 2.7779, 1.212233],
[9.328745, 2.553949, 3.276319, 3.000918, 2.499342]])
self.assertEqual(tf.rank(spectrum_test).eval(), 2)
self.assertAllClose(
spectrum_test.eval()[0:2, 0:5], output_true, rtol=1e-05, atol=1e-05)