File size: 22,515 Bytes
a7c2243 | 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 53 54 55 56 57 58 59 60 61 62 63 64 65 66 67 68 69 70 71 72 73 74 75 76 77 78 79 80 81 82 83 84 85 86 87 88 89 90 91 92 93 94 95 96 97 98 99 100 101 102 103 104 105 106 107 108 109 110 111 112 113 114 115 116 117 118 119 120 121 122 123 124 125 126 127 128 129 130 131 132 133 134 135 136 137 138 139 140 141 142 143 144 145 146 147 148 149 150 151 152 153 154 155 156 157 158 159 160 161 162 163 164 165 166 167 168 169 170 171 172 173 174 175 176 177 178 179 180 181 182 183 184 185 186 187 188 189 190 191 192 193 194 195 196 197 198 199 200 201 202 203 204 205 206 207 208 209 210 211 212 213 214 215 216 217 218 219 220 221 222 223 224 225 226 227 228 229 230 231 232 233 234 235 236 237 238 239 240 241 242 243 244 245 246 247 248 249 250 251 252 253 254 255 256 257 258 259 260 261 262 263 264 265 266 267 268 269 270 271 272 273 274 275 276 277 278 279 280 281 282 283 284 285 286 287 288 289 290 291 292 293 294 295 296 297 298 299 300 301 302 303 304 305 306 307 308 309 310 311 312 313 314 315 316 317 318 319 320 321 322 323 324 325 326 327 328 329 330 331 332 333 334 335 336 337 338 339 340 341 342 343 344 345 346 347 348 349 350 351 352 353 354 355 356 357 358 359 360 361 362 363 364 365 366 367 368 369 370 371 372 373 374 375 376 377 378 379 380 381 382 383 384 385 386 387 388 389 390 391 392 393 394 395 396 397 398 399 400 401 402 403 404 405 406 407 408 409 410 411 412 413 414 415 416 417 418 419 420 421 422 423 424 425 426 427 428 429 430 431 432 433 434 435 436 437 438 439 440 441 442 443 444 445 446 447 448 449 450 451 452 453 454 455 456 457 458 459 460 461 462 463 464 465 466 467 468 469 470 471 472 473 474 475 476 477 478 479 480 481 482 483 484 485 486 487 488 | # Copyright (c) 2022, NVIDIA CORPORATION. All rights reserved.
#
# Licensed under the Apache License, Version 2.0 (the "License");
# you may not use this file except in compliance with the License.
# You may obtain a copy of the License at
#
# http://www.apache.org/licenses/LICENSE-2.0
#
# Unless required by applicable law or agreed to in writing, software
# distributed under the License is distributed on an "AS IS" BASIS,
# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
# See the License for the specific language governing permissions and
# limitations under the License.
import json
import os
import tempfile
from collections import namedtuple
from typing import List, Type, Union
import numpy as np
import pytest
import soundfile as sf
from nemo.collections.asr.parts.preprocessing.perturb import NoisePerturbation, SilencePerturbation
from nemo.collections.asr.parts.preprocessing.segment import AudioSegment, select_channels
class TestSelectChannels:
num_samples = 1000
max_diff_tol = 1e-9
@pytest.mark.unit
@pytest.mark.parametrize("channel_selector", [None, 'average', 0, 1, [0, 1]])
def test_single_channel_input(self, channel_selector: Type[Union[str, int, List[int]]]):
"""Cover the case with single-channel input signal.
Channel selector should not do anything in this case.
"""
golden_out = signal_in = np.random.rand(self.num_samples)
if channel_selector not in [None, 0, 'average']:
# Expect a failure if looking for a different channel when input is 1D
with pytest.raises(ValueError):
# UUT
select_channels(signal_in, channel_selector)
else:
# UUT
signal_out = select_channels(signal_in, channel_selector)
# Check difference
max_diff = np.max(np.abs(signal_out - golden_out))
assert max_diff < self.max_diff_tol
@pytest.mark.unit
@pytest.mark.parametrize("num_channels", [2, 4])
@pytest.mark.parametrize("channel_selector", [None, 'average', 0, [1], [0, 1]])
def test_multi_channel_input(self, num_channels: int, channel_selector: Type[Union[str, int, List[int]]]):
"""Cover the case with multi-channel input signal and single-
or multi-channel output.
"""
signal_in = np.random.rand(self.num_samples, num_channels)
# calculate golden output
if channel_selector is None:
golden_out = signal_in
elif channel_selector == 'average':
golden_out = np.mean(signal_in, axis=1)
else:
golden_out = signal_in[:, channel_selector].squeeze()
# UUT
signal_out = select_channels(signal_in, channel_selector)
# Check difference
max_diff = np.max(np.abs(signal_out - golden_out))
assert max_diff < self.max_diff_tol
@pytest.mark.unit
@pytest.mark.parametrize("num_channels", [1, 2])
@pytest.mark.parametrize("channel_selector", [2, [1, 2]])
def test_select_more_channels_than_available(
self, num_channels: int, channel_selector: Type[Union[str, int, List[int]]]
):
"""This test is expecting the UUT to fail because we ask for more channels
than available in the input signal.
"""
signal_in = np.random.rand(self.num_samples, num_channels)
# expect failure since we ask for more channels than available
with pytest.raises(ValueError):
# UUT
select_channels(signal_in, channel_selector)
class TestAudioSegment:
sample_rate = 16000
signal_duration_sec = 2
max_diff_tol = 1e-9
@property
def num_samples(self):
return self.sample_rate * self.signal_duration_sec
@pytest.mark.unit
@pytest.mark.parametrize("num_channels", [1, 4])
@pytest.mark.parametrize("channel_selector", [None, 'average', 0, 1, [0, 1]])
def test_init_single_channel(self, num_channels: int, channel_selector: Type[Union[str, int, List[int]]]):
"""Test the constructor directly."""
if num_channels == 1:
# samples is a one-dimensional vector for single-channel signal
samples = np.random.rand(self.num_samples)
else:
samples = np.random.rand(self.num_samples, num_channels)
if (isinstance(channel_selector, int) and channel_selector >= num_channels) or (
isinstance(channel_selector, list) and max(channel_selector) >= num_channels
):
# Expect a failure if looking for a different channel when input is 1D
with pytest.raises(ValueError):
# Construct UUT
uut = AudioSegment(samples=samples, sample_rate=self.sample_rate, channel_selector=channel_selector)
else:
# Construct UUT
uut = AudioSegment(samples=samples, sample_rate=self.sample_rate, channel_selector=channel_selector)
# Create golden reference
# Note: AudioSegment converts input samples to float32
golden_samples = select_channels(samples.astype('float32'), channel_selector)
expected_num_channels = 1 if golden_samples.ndim == 1 else golden_samples.shape[1]
# Test UUT
assert uut.num_channels == expected_num_channels
assert uut.num_samples == self.num_samples
assert uut.sample_rate == self.sample_rate
assert uut.duration == self.signal_duration_sec
max_diff = np.max(np.abs(uut.samples - golden_samples))
assert max_diff < self.max_diff_tol
# Test zero padding
pad_length = 42
uut.pad(pad_length, symmetric=False)
# compare to golden references
assert uut.num_samples == self.num_samples + pad_length
assert np.all(uut.samples[-pad_length:] == 0.0)
max_diff = np.max(np.abs(uut.samples[:-pad_length] - golden_samples))
assert max_diff < self.max_diff_tol
# Test subsegment
start_time = 0.2 * self.signal_duration_sec
end_time = 0.5 * self.signal_duration_sec
uut.subsegment(start_time=start_time, end_time=end_time)
# compare to golden references
start_sample = int(round(start_time * self.sample_rate))
end_sample = int(round(end_time * self.sample_rate))
max_diff = np.max(np.abs(uut.samples - golden_samples[start_sample:end_sample]))
assert max_diff < self.max_diff_tol
@pytest.mark.unit
@pytest.mark.parametrize("num_channels", [1, 4])
@pytest.mark.parametrize("channel_selector", [None, 'average', 0])
def test_from_file(self, num_channels, channel_selector):
"""Test loading a signal from a file."""
with tempfile.TemporaryDirectory() as test_dir:
# Prepare a wav file
audio_file = os.path.join(test_dir, 'audio.wav')
if num_channels == 1:
# samples is a one-dimensional vector for single-channel signal
samples = np.random.rand(self.num_samples)
else:
samples = np.random.rand(self.num_samples, num_channels)
sf.write(audio_file, samples, self.sample_rate, 'float')
# Create UUT
uut = AudioSegment.from_file(audio_file, channel_selector=channel_selector)
# Create golden reference
# Note: AudioSegment converts input samples to float32
golden_samples = select_channels(samples.astype('float32'), channel_selector)
expected_num_channels = 1 if golden_samples.ndim == 1 else golden_samples.shape[1]
# Test UUT
assert uut.num_channels == expected_num_channels
assert uut.num_samples == self.num_samples
assert uut.sample_rate == self.sample_rate
assert uut.duration == self.signal_duration_sec
max_diff = np.max(np.abs(uut.samples - golden_samples))
assert max_diff < self.max_diff_tol
@pytest.mark.unit
@pytest.mark.parametrize("data_channels", [1, 4])
@pytest.mark.parametrize("noise_channels", [1, 4])
def test_noise_perturb_channels(self, data_channels, noise_channels):
"""Test loading a signal from a file."""
with tempfile.TemporaryDirectory() as test_dir:
# Prepare a wav file
audio_file = os.path.join(test_dir, 'audio.wav')
if data_channels == 1:
# samples is a one-dimensional vector for single-channel signal
samples = np.random.rand(self.num_samples)
else:
samples = np.random.rand(self.num_samples, data_channels)
sf.write(audio_file, samples, self.sample_rate, 'float')
noise_file = os.path.join(test_dir, 'noise.wav')
if noise_channels == 1:
# samples is a one-dimensional vector for single-channel signal
samples = np.random.rand(self.num_samples)
else:
samples = np.random.rand(self.num_samples, noise_channels)
sf.write(noise_file, samples, self.sample_rate, 'float')
manifest_file = os.path.join(test_dir, 'noise_manifest.json')
with open(manifest_file, 'w') as fout:
item = {'audio_filepath': os.path.abspath(noise_file), 'label': '-', 'duration': 0.1, 'offset': 0.0}
fout.write(f'{json.dumps(item)}\n')
perturber = NoisePerturbation(manifest_file)
audio = AudioSegment.from_file(audio_file)
noise = AudioSegment.from_file(noise_file)
if data_channels == noise_channels:
try:
_ = perturber.perturb_with_input_noise(audio, noise, ref_mic=0)
except ValueError as e:
assert False, "perturb_with_input_noise failed with ref_mic=0"
with pytest.raises(ValueError):
_ = perturber.perturb_with_input_noise(audio, noise, ref_mic=data_channels)
try:
_ = perturber.perturb_with_foreground_noise(audio, noise, ref_mic=0)
except ValueError as e:
assert False, "perturb_with_foreground_noise failed with ref_mic=0"
with pytest.raises(ValueError):
_ = perturber.perturb_with_foreground_noise(audio, noise, ref_mic=data_channels)
else:
with pytest.raises(ValueError):
_ = perturber.perturb_with_input_noise(audio, noise)
with pytest.raises(ValueError):
_ = perturber.perturb_with_foreground_noise(audio, noise)
def test_silence_perturb(self):
"""Test loading a signal from a file and apply silence perturbation"""
with tempfile.TemporaryDirectory() as test_dir:
# Prepare a wav file
audio_file = os.path.join(test_dir, 'audio.wav')
# samples is a one-dimensional vector for single-channel signal
samples = np.random.rand(self.num_samples)
sf.write(audio_file, samples, self.sample_rate, 'float')
dur = 2
perturber = SilencePerturbation(
min_start_silence_secs=dur,
max_start_silence_secs=dur,
min_end_silence_secs=dur,
max_end_silence_secs=dur,
)
audio = AudioSegment.from_file(audio_file)
ori_audio_len = len(audio._samples)
_ = perturber.perturb(audio)
assert len(audio._samples) == ori_audio_len + 2 * dur * self.sample_rate
@pytest.mark.unit
@pytest.mark.parametrize(
"num_channels, channel_selectors",
[
(1, [None, 'average', 0]),
(3, [None, 'average', 0, 1, [0, 1]]),
],
)
@pytest.mark.parametrize("sample_rate", [8000, 16000, 22500])
def test_audio_segment_from_file(self, tmpdir, num_channels, channel_selectors, sample_rate):
"""Test loading and audio signal from a file."""
signal_len_sec = 4
num_samples = signal_len_sec * sample_rate
num_examples = 10
rtol, atol = 1e-5, 1e-6
for n in range(num_examples):
# Create a test vector
audio_file = os.path.join(tmpdir, f'test_audio_{n:02}.wav')
samples = np.random.randn(num_samples, num_channels)
sf.write(audio_file, samples, sample_rate, 'float')
for channel_selector in channel_selectors:
if channel_selector is None:
ref_samples = samples
elif isinstance(channel_selector, int) or isinstance(channel_selector, list):
ref_samples = samples[:, channel_selector]
elif channel_selector == 'average':
ref_samples = np.mean(samples, axis=1)
else:
raise ValueError(f'Unexpected value of channel_selector {channel_selector}')
# 1) Load complete audio
# Reference
ref_samples = ref_samples.squeeze()
ref_channels = 1 if ref_samples.ndim == 1 else ref_samples.shape[1]
# UUT
audio_segment = AudioSegment.from_file(audio_file, channel_selector=channel_selector)
# Test
assert (
audio_segment.sample_rate == sample_rate
), f'channel_selector {channel_selector}, sample rate not matching: {audio_segment.sample_rate} != {sample_rate}'
assert (
audio_segment.num_channels == ref_channels
), f'channel_selector {channel_selector}, num channels not matching: {audio_segment.num_channels} != {ref_channels}'
assert audio_segment.num_samples == len(
ref_samples
), f'channel_selector {channel_selector}, num samples not matching: {audio_segment.num_samples} != {len(ref_samples)}'
assert np.allclose(
audio_segment.samples, ref_samples, rtol=rtol, atol=atol
), f'channel_selector {channel_selector}, samples not matching'
# 2) Load a with duration=None and offset=None, should load the whole audio
# UUT
audio_segment = AudioSegment.from_file(
audio_file, offset=None, duration=None, channel_selector=channel_selector
)
# Test
assert (
audio_segment.sample_rate == sample_rate
), f'channel_selector {channel_selector}, offset {offset}, duration {duration}, sample rate not matching: {audio_segment.sample_rate} != {sample_rate}'
assert (
audio_segment.num_channels == ref_channels
), f'channel_selector {channel_selector}, offset {offset}, duration {duration}, num channels not matching: {audio_segment.num_channels} != {ref_channels}'
assert audio_segment.num_samples == len(
ref_samples
), f'channel_selector {channel_selector}, offset {offset}, duration {duration}, num samples not matching: {audio_segment.num_samples} != {len(ref_samples)}'
assert np.allclose(
audio_segment.samples, ref_samples, rtol=rtol, atol=atol
), f'channel_selector {channel_selector}, offset {offset}, duration {duration}, samples not matching'
# 3) Load a random segment
offset = 0.45 * np.random.rand() * signal_len_sec
duration = 0.45 * np.random.rand() * signal_len_sec
# Reference
start = int(offset * sample_rate)
end = start + int(duration * sample_rate)
ref_samples = ref_samples[start:end, ...]
# UUT
audio_segment = AudioSegment.from_file(
audio_file, offset=offset, duration=duration, channel_selector=channel_selector
)
# Test
assert (
audio_segment.sample_rate == sample_rate
), f'channel_selector {channel_selector}, offset {offset}, duration {duration}, sample rate not matching: {audio_segment.sample_rate} != {sample_rate}'
assert (
audio_segment.num_channels == ref_channels
), f'channel_selector {channel_selector}, offset {offset}, duration {duration}, num channels not matching: {audio_segment.num_channels} != {ref_channels}'
assert audio_segment.num_samples == len(
ref_samples
), f'channel_selector {channel_selector}, offset {offset}, duration {duration}, num samples not matching: {audio_segment.num_samples} != {len(ref_samples)}'
assert np.allclose(
audio_segment.samples, ref_samples, rtol=rtol, atol=atol
), f'channel_selector {channel_selector}, offset {offset}, duration {duration}, samples not matching'
@pytest.mark.unit
@pytest.mark.parametrize(
"num_channels, channel_selectors",
[
(1, [None, 'average', 0]),
(3, [None, 'average', 0, 1, [0, 1]]),
],
)
@pytest.mark.parametrize("offset", [0, 1.5])
@pytest.mark.parametrize("duration", [1, 2])
def test_audio_segment_multichannel_with_list(self, tmpdir, num_channels, channel_selectors, offset, duration):
"""Test loading an audio signal from a list of single-channel files."""
sample_rate = 16000
signal_len_sec = 5
num_samples = signal_len_sec * sample_rate
rtol, atol = 1e-5, 1e-6
# Random samples
samples = np.random.rand(num_samples, num_channels)
# Save audio
audio_files = []
for m in range(num_channels):
a_file = os.path.join(tmpdir, f'ch_{m}.wav')
sf.write(a_file, samples[:, m], sample_rate)
audio_files.append(a_file)
mc_file = os.path.join(tmpdir, f'mc.wav')
sf.write(mc_file, samples, sample_rate)
for channel_selector in channel_selectors:
# UUT: loading audio from a list of files
uut_segment = AudioSegment.from_file(
audio_file=audio_files, offset=offset, duration=duration, channel_selector=channel_selector
)
# Reference: load from the original file
ref_segment = AudioSegment.from_file(
audio_file=mc_file, offset=offset, duration=duration, channel_selector=channel_selector
)
# Check
assert (
uut_segment.sample_rate == ref_segment.sample_rate
), f'channel_selector {channel_selector}: expecting {ref_segment.sample_rate}, but UUT segment has {uut_segment.sample_rate}'
assert (
uut_segment.num_samples == ref_segment.num_samples
), f'channel_selector {channel_selector}: expecting {ref_segment.num_samples}, but UUT segment has {uut_segment.num_samples}'
assert np.allclose(
uut_segment.samples, ref_segment.samples, rtol=rtol, atol=atol
), f'channel_selector {channel_selector}: samples not matching'
# Try to get a channel that is out of range.
with pytest.raises(RuntimeError, match="Channel cannot be selected"):
AudioSegment.from_file(audio_file=audio_files, channel_selector=num_channels)
if num_channels > 1:
# Try to load a list of multichannel files
# This is expected to fail since we only support loading a single-channel signal
# from each file when audio_file is a list
with pytest.raises(RuntimeError, match="Expecting a single-channel audio signal"):
AudioSegment.from_file(audio_file=[mc_file, mc_file])
with pytest.raises(RuntimeError, match="Expecting a single-channel audio signal"):
AudioSegment.from_file(audio_file=[mc_file, mc_file], channel_selector=0)
@pytest.mark.unit
@pytest.mark.parametrize("target_sr", [8000, 16000])
def test_audio_segment_trim_match(self, tmpdir, target_sr):
"""Test loading and audio signal from a file matches when using a path and a list
for different target_sr, int_values and trim setups.
"""
sample_rate = 24000
signal_len_sec = 2
num_samples = signal_len_sec * sample_rate
num_examples = 10
TrimSetup = namedtuple("TrimSetup", "ref top_db frame_length hop_length")
trim_setups = []
trim_setups.append(TrimSetup(np.max, 10, 2048, 1024))
trim_setups.append(TrimSetup(1.0, 35, 2048, 1024))
trim_setups.append(TrimSetup(0.8, 45, 2048, 1024))
for n in range(num_examples):
# Create a test vector
audio_file = os.path.join(tmpdir, f'test_audio_{n:02}.wav')
samples = np.random.randn(num_samples)
# normalize
samples = samples / np.max(samples)
# apply random scaling and window to have some samples cut by trim
samples = np.random.rand() * np.hanning(num_samples) * samples
sf.write(audio_file, samples, sample_rate, 'float')
for trim_setup in trim_setups:
# UUT 1: load from a path
audio_segment_1 = AudioSegment.from_file(
audio_file,
target_sr=target_sr,
trim=True,
trim_ref=trim_setup.ref,
trim_top_db=trim_setup.top_db,
trim_frame_length=trim_setup.frame_length,
trim_hop_length=trim_setup.hop_length,
)
# UUT 2: load from a list
audio_segment_2 = AudioSegment.from_file(
[audio_file],
target_sr=target_sr,
trim=True,
trim_ref=trim_setup.ref,
trim_top_db=trim_setup.top_db,
trim_frame_length=trim_setup.frame_length,
trim_hop_length=trim_setup.hop_length,
)
# Test
assert audio_segment_1 == audio_segment_2, f'trim setup {trim_setup}, loaded segments not matching'
|