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APM-QA Test data generation: environmental noise looped.

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SignalProcessingUtils.MixSignals() now allows different padding options.
This CL also adds more unit tests for SignalProcessingUtils.MixSignals().

Bug: webrtc:7494
Change-Id: Id62fe9998e512c275cb6399e0aedf11f23a9f36e
Reviewed-on: https://webrtc-review.googlesource.com/5780
Commit-Queue: Alessio Bazzica <alessiob@webrtc.org>
Reviewed-by: Alex Loiko <aleloi@webrtc.org>
Cr-Commit-Position: refs/heads/master@{#20122}
This commit is contained in:
Alessio Bazzica 2017-10-03 17:47:41 +02:00 committed by Commit Bot
parent 90e1f539a5
commit 6967553240
4 changed files with 159 additions and 32 deletions
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2
modules/audio_processing/test/py_quality_assessment/README.md
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@ -10,7 +10,7 @@ reference one used for evaluation.
## Dependencies
- OS: Linux
- Python 2.7
- Python libraries: numpy, scipy, pydub (0.17.0+), pandas (0.20.1+)
- Python libraries: enum34, numpy, scipy, pydub (0.17.0+), pandas (0.20.1+)
- It is recommended that a dedicated Python environment is used
- install `virtualenv`
- `$ sudo apt-get install python-virtualenv`

75
modules/audio_processing/test/py_quality_assessment/quality_assessment/signal_processing.py
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@ -10,6 +10,7 @@
"""
import array
import enum
import logging
import os
import sys
@ -29,6 +30,7 @@ except ImportError:
try:
import scipy.signal
import scipy.fftpack
except ImportError:
logging.critical('Cannot import the third-party Python package scipy')
sys.exit(1)
@ -40,6 +42,12 @@ class SignalProcessingUtils(object):
"""Collection of signal processing utilities.
"""
@enum.unique
class MixPadding(enum.Enum):
NO_PADDING = 0
ZERO_PADDING = 1
LOOP = 2
def __init__(self):
pass
@ -155,6 +163,14 @@ class SignalProcessingUtils(object):
raise exceptions.SignalProcessingException('Unsupported samples type')
return np.array(signal.get_array_of_samples(), np.int16)
@classmethod
def Fft(cls, signal, normalize=True):
x = cls.AudioSegmentToRawData(signal).astype(np.float32)
if normalize:
x /= max(abs(np.max(x)), 1.0)
y = scipy.fftpack.fft(x)
return y[:len(y) / 2]
@classmethod
def DetectHardClipping(cls, signal, threshold=2):
"""Detects hard clipping.
@ -272,18 +288,24 @@ class SignalProcessingUtils(object):
})
@classmethod
def MixSignals(cls, signal, noise, target_snr=0.0, bln_pad_shortest=False):
"""Mixes two signals with a target SNR.
def MixSignals(cls, signal, noise, target_snr=0.0,
pad_noise=MixPadding.NO_PADDING):
"""Mixes |signal| and |noise| with a target SNR.
Mix two signals with a desired SNR by scaling noise (noise).
Mix |signal| and |noise| with a desired SNR by scaling |noise|.
If the target SNR is +/- infinite, a copy of signal/noise is returned.
If |signal| is shorter than |noise|, the length of the mix equals that of
|signal|. Otherwise, the mix length depends on whether padding is applied.
When padding is not applied, that is |pad_noise| is set to NO_PADDING
(default), the mix length equals that of |noise| - i.e., |signal| is
truncated. Otherwise, |noise| is extended and the resulting mix has the same
length of |signal|.
Args:
signal: AudioSegment instance (signal).
noise: AudioSegment instance (noise).
target_snr: float, numpy.Inf or -numpy.Inf (dB).
bln_pad_shortest: if True, it pads the shortest signal with silence at the
end.
pad_noise: SignalProcessingUtils.MixPadding, default: NO_PADDING.
Returns:
An AudioSegment instance.
@ -310,28 +332,23 @@ class SignalProcessingUtils(object):
raise exceptions.SignalProcessingException(
'cannot mix a signal with -Inf power')
# Pad signal (if necessary). If noise is the shortest, the AudioSegment
# overlay() method implictly pads noise. Hence, the only case to handle
# is signal shorter than noise and bln_pad_shortest True.
if bln_pad_shortest:
signal_duration = len(signal)
noise_duration = len(noise)
logging.warning('mix signals with padding')
logging.warning(' signal: %d ms', signal_duration)
logging.warning(' noise: %d ms', noise_duration)
padding_duration = noise_duration - signal_duration
if padding_duration > 0: # That is signal_duration < noise_duration.
logging.debug(' padding: %d ms', padding_duration)
padding = pydub.AudioSegment.silent(
duration=padding_duration,
frame_rate=signal.frame_rate)
logging.debug(' signal (pre): %d ms', len(signal))
signal = signal + padding
logging.debug(' signal (post): %d ms', len(signal))
# Update power.
signal_power = float(signal.dBFS)
# Mix signals using the target SNR.
# Mix.
gain_db = signal_power - noise_power - target_snr
return cls.Normalize(signal.overlay(noise.apply_gain(gain_db)))
signal_duration = len(signal)
noise_duration = len(noise)
if signal_duration <= noise_duration:
# Ignore |pad_noise|, |noise| is truncated if longer that |signal|, the
# mix will have the same length of |signal|.
return signal.overlay(noise.apply_gain(gain_db))
elif pad_noise == cls.MixPadding.NO_PADDING:
# |signal| is longer than |noise|, but no padding is applied to |noise|.
# Truncate |signal|.
return noise.overlay(signal, gain_during_overlay=gain_db)
elif pad_noise == cls.MixPadding.ZERO_PADDING:
# TODO(alessiob): Check that this works as expected.
return signal.overlay(noise.apply_gain(gain_db))
elif pad_noise == cls.MixPadding.LOOP:
# |signal| is longer than |noise|, extend |noise| by looping.
return signal.overlay(noise.apply_gain(gain_db), loop=True)
else:
raise exceptions.SignalProcessingException('invalid padding type')

109
modules/audio_processing/test/py_quality_assessment/quality_assessment/signal_processing_unittest.py
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@ -75,3 +75,112 @@ class TestSignalProcessing(unittest.TestCase):
with self.assertRaises(exceptions.SignalProcessingException):
_ = signal_processing.SignalProcessingUtils.MixSignals(
silence, signal, 0.0)
def testMixSignalNoiseDifferentLengths(self):
# Test signals.
shorter = signal_processing.SignalProcessingUtils.GenerateWhiteNoise(
pydub.AudioSegment.silent(duration=1000, frame_rate=8000))
longer = signal_processing.SignalProcessingUtils.GenerateWhiteNoise(
pydub.AudioSegment.silent(duration=2000, frame_rate=8000))
# When the signal is shorter than the noise, the mix length always equals
# that of the signal regardless of whether padding is applied.
# No noise padding, length of signal less than that of noise.
mix = signal_processing.SignalProcessingUtils.MixSignals(
signal=shorter,
noise=longer,
pad_noise=signal_processing.SignalProcessingUtils.MixPadding.NO_PADDING)
self.assertEqual(len(shorter), len(mix))
# With noise padding, length of signal less than that of noise.
mix = signal_processing.SignalProcessingUtils.MixSignals(
signal=shorter,
noise=longer,
pad_noise=signal_processing.SignalProcessingUtils.MixPadding.ZERO_PADDING)
self.assertEqual(len(shorter), len(mix))
# When the signal is longer than the noise, the mix length depends on
# whether padding is applied.
# No noise padding, length of signal greater than that of noise.
mix = signal_processing.SignalProcessingUtils.MixSignals(
signal=longer,
noise=shorter,
pad_noise=signal_processing.SignalProcessingUtils.MixPadding.NO_PADDING)
self.assertEqual(len(shorter), len(mix))
# With noise padding, length of signal greater than that of noise.
mix = signal_processing.SignalProcessingUtils.MixSignals(
signal=longer,
noise=shorter,
pad_noise=signal_processing.SignalProcessingUtils.MixPadding.ZERO_PADDING)
self.assertEqual(len(longer), len(mix))
def testMixSignalNoisePaddingTypes(self):
# Test signals.
shorter = signal_processing.SignalProcessingUtils.GenerateWhiteNoise(
pydub.AudioSegment.silent(duration=1000, frame_rate=8000))
longer = signal_processing.SignalProcessingUtils.GeneratePureTone(
pydub.AudioSegment.silent(duration=2000, frame_rate=8000), 440.0)
# Zero padding: expect pure tone only in 1-2s.
mix_zero_pad = signal_processing.SignalProcessingUtils.MixSignals(
signal=longer,
noise=shorter,
target_snr=-6,
pad_noise=signal_processing.SignalProcessingUtils.MixPadding.ZERO_PADDING)
# Loop: expect pure tone plus noise in 1-2s.
mix_loop = signal_processing.SignalProcessingUtils.MixSignals(
signal=longer,
noise=shorter,
target_snr=-6,
pad_noise=signal_processing.SignalProcessingUtils.MixPadding.LOOP)
def Energy(signal):
samples = signal_processing.SignalProcessingUtils.AudioSegmentToRawData(
signal).astype(np.float32)
return np.sum(samples * samples)
e_mix_zero_pad = Energy(mix_zero_pad[-1000:])
e_mix_loop = Energy(mix_loop[-1000:])
self.assertLess(0, e_mix_zero_pad)
self.assertLess(e_mix_zero_pad, e_mix_loop)
def testMixSignalSnr(self):
# Test signals.
tone_low = signal_processing.SignalProcessingUtils.GeneratePureTone(
pydub.AudioSegment.silent(duration=64, frame_rate=8000), 250.0)
tone_high = signal_processing.SignalProcessingUtils.GeneratePureTone(
pydub.AudioSegment.silent(duration=64, frame_rate=8000), 3000.0)
def ToneAmplitudes(mix):
"""Returns the amplitude of the coefficients #16 and #192, which
correspond to the tones at 250 and 3k Hz respectively."""
mix_fft = np.absolute(signal_processing.SignalProcessingUtils.Fft(mix))
return mix_fft[16], mix_fft[192]
mix = signal_processing.SignalProcessingUtils.MixSignals(
signal=tone_low,
noise=tone_high,
target_snr=-6)
ampl_low, ampl_high = ToneAmplitudes(mix)
self.assertLess(ampl_low, ampl_high)
mix = signal_processing.SignalProcessingUtils.MixSignals(
signal=tone_high,
noise=tone_low,
target_snr=-6)
ampl_low, ampl_high = ToneAmplitudes(mix)
self.assertLess(ampl_high, ampl_low)
mix = signal_processing.SignalProcessingUtils.MixSignals(
signal=tone_low,
noise=tone_high,
target_snr=6)
ampl_low, ampl_high = ToneAmplitudes(mix)
self.assertLess(ampl_high, ampl_low)
mix = signal_processing.SignalProcessingUtils.MixSignals(
signal=tone_high,
noise=tone_low,
target_snr=6)
ampl_low, ampl_high = ToneAmplitudes(mix)
self.assertLess(ampl_low, ampl_high)

5
modules/audio_processing/test/py_quality_assessment/quality_assessment/test_data_generation.py
View File

@ -394,7 +394,8 @@ class EnvironmentalNoiseTestDataGenerator(TestDataGenerator):
if not os.path.exists(noisy_signal_filepath):
# Create noisy signal.
noisy_signal = signal_processing.SignalProcessingUtils.MixSignals(
input_signal, noise_signal, snr)
input_signal, noise_signal, snr,
pad_noise=signal_processing.SignalProcessingUtils.MixPadding.LOOP)
# Save.
signal_processing.SignalProcessingUtils.SaveWav(
@ -489,7 +490,7 @@ class ReverberationTestDataGenerator(TestDataGenerator):
if not os.path.exists(noisy_signal_filepath):
# Create noisy signal.
noisy_signal = signal_processing.SignalProcessingUtils.MixSignals(
input_signal, noise_signal, snr, bln_pad_shortest=True)
input_signal, noise_signal, snr)
# Save.
signal_processing.SignalProcessingUtils.SaveWav(