def fast_time_stretch(signals, constant=False, extreme=False):
def overlap(tup):
framed_signals, frame_step_out = tup
new_wav = reconstruction_ops.overlap_and_add(framed_signals,
frame_step_out)
return tf_get_word(new_wav)
if extreme:
print("extreme time warp activated")
speedx = tf.random_uniform([tf.shape(signals)[0]], 0.7, 1.3)
else:
speedx = tf.truncated_normal([tf.shape(signals)[0]], 1.0, 0.2)
frame_length = 300
frame_step_in = int(300 * 0.25)
frame_step_out = tf.cast(speedx * frame_step_in, tf.int32)
hann_window = window_ops.hann_window(frame_length)
framed_signals = shape_ops.frame(signals,
frame_length,
frame_step_in,
pad_end=False)
framed_signals *= hann_window
return tf.map_fn(overlap, [framed_signals, frame_step_out],
parallel_iterations=120,
back_prop=False,
dtype=tf.float32)
def test_inverse_stft_window_fn_special_case(self):
"""Test inverse_stft_window_fn in special overlap = 3/4 case."""
# Cases in which frame_length is an integer multiple of 4 * frame_step are
# special because they allow exact reproduction of the waveform with a
# squared Hann window (Hann window in both forward and reverse transforms).
# In the case where frame_length = 4 * frame_step, that combination
# produces a constant gain of 1.5, and so the corrected window will be the
# Hann window / 1.5.
# Tuples of (frame_length, frame_step).
test_configs = [
(256, 64),
(128, 32),
]
for (frame_length, frame_step) in test_configs:
hann_window = window_ops.hann_window(frame_length,
dtype=dtypes.float32)
inverse_window_fn = spectral_ops.inverse_stft_window_fn(frame_step)
inverse_window = inverse_window_fn(frame_length,
dtype=dtypes.float32)
with self.test_session(use_gpu=True) as sess:
hann_window, inverse_window = sess.run(
[hann_window, inverse_window])
self.assertAllClose(hann_window, inverse_window * 1.5)
def test_inverse_stft_window_fn(self):
"""Test that inverse_stft_window_fn has unit gain at each window phase."""
# Tuples of (frame_length, frame_step).
test_configs = [
(256, 32),
(256, 64),
(128, 25),
(127, 32),
(128, 64),
]
for (frame_length, frame_step) in test_configs:
hann_window = window_ops.hann_window(frame_length,
dtype=dtypes.float32)
inverse_window_fn = spectral_ops.inverse_stft_window_fn(frame_step)
inverse_window = inverse_window_fn(frame_length,
dtype=dtypes.float32)
with self.test_session(use_gpu=True) as sess:
hann_window, inverse_window = sess.run(
[hann_window, inverse_window])
# Expect unit gain at each phase of the window.
product_window = hann_window * inverse_window
for i in range(frame_step):
self.assertAllClose(1.0, np.sum(product_window[i::frame_step]))
def test_inverse_stft_window_fn(self):
"""Test that inverse_stft_window_fn has unit gain at each window phase."""
# Tuples of (frame_length, frame_step).
test_configs = [
(256, 32),
(256, 64),
(128, 25),
(127, 32),
(128, 64),
]
for (frame_length, frame_step) in test_configs:
hann_window = window_ops.hann_window(frame_length, dtype=dtypes.float32)
inverse_window_fn = spectral_ops.inverse_stft_window_fn(frame_step)
inverse_window = inverse_window_fn(frame_length, dtype=dtypes.float32)
with self.test_session(use_gpu=True) as sess:
hann_window, inverse_window = sess.run([hann_window, inverse_window])
# Expect unit gain at each phase of the window.
product_window = hann_window * inverse_window
for i in range(frame_step):
self.assertAllClose(1.0, np.sum(product_window[i::frame_step]))
def test_inverse_stft_window_fn_special_case(self):
"""Test inverse_stft_window_fn in special overlap = 3/4 case."""
# Cases in which frame_length is an integer multiple of 4 * frame_step are
# special because they allow exact reproduction of the waveform with a
# squared Hann window (Hann window in both forward and reverse transforms).
# In the case where frame_length = 4 * frame_step, that combination
# produces a constant gain of 1.5, and so the corrected window will be the
# Hann window / 1.5.
# Tuples of (frame_length, frame_step).
test_configs = [
(256, 64),
(128, 32),
]
for (frame_length, frame_step) in test_configs:
hann_window = window_ops.hann_window(frame_length, dtype=dtypes.float32)
inverse_window_fn = spectral_ops.inverse_stft_window_fn(frame_step)
inverse_window = inverse_window_fn(frame_length, dtype=dtypes.float32)
with self.test_session(use_gpu=True) as sess:
hann_window, inverse_window = sess.run([hann_window, inverse_window])
self.assertAllClose(hann_window, inverse_window * 1.5)
