import os
import numpy as np
from scipy.io import wavfile
from audiomentations import (
Compose,
AddGaussianNoise,
TimeStretch,
PitchShift,
Shift,
Normalize,
AddImpulseResponse,
FrequencyMask,
TimeMask,
AddGaussianSNR,
Resample,
ClippingDistortion,
AddBackgroundNoise,
AddShortNoises)
SAMPLE_RATE = 16000
CHANNELS = 1
def load_wav_file(sound_file_path):
sample_rate, sound_np = wavfile.read(sound_file_path)
if sample_rate != SAMPLE_RATE:
raise Exception(
"Unexpected sample rate {} (expected {})".format(sample_rate, SAMPLE_RATE)
)
if sound_np.dtype != np.float32:
assert sound_np.dtype == np.int16
sound_np = (sound_np / 32767).astype(np.float32) # ends up roughly between -1 and 1
return sound_np
DEMO_DIR = os.path.dirname(__file__)
if __name__ == "__main__":
"""
For each transformation, apply it to an example sound and write the transformed sounds to
an output folder.
"""
output_dir = os.path.join(DEMO_DIR, "output")
os.makedirs(output_dir, exist_ok=True)
samples = load_wav_file(os.path.join(DEMO_DIR, "acoustic_guitar_0.wav"))
# AddImpulseResponse
augmenter = Compose(
[AddImpulseResponse(p=1.0, ir_path=os.path.join(DEMO_DIR, "ir"))]
)
output_file_path = os.path.join(
output_dir, "AddImpulseResponse_{:03d}.wav".format(0)
)
augmented_samples = augmenter(samples=samples, sample_rate=SAMPLE_RATE)
wavfile.write(output_file_path, rate=SAMPLE_RATE, data=augmented_samples)
# FrequencyMask
augmenter = Compose([FrequencyMask(p=1.0)])
for i in range(5):
output_file_path = os.path.join(
output_dir, "FrequencyMask_{:03d}.wav".format(i)
)
augmented_samples = augmenter(samples=samples, sample_rate=SAMPLE_RATE)
wavfile.write(output_file_path, rate=SAMPLE_RATE, data=augmented_samples)
# TimeMask
augmenter = Compose([TimeMask(p=1.0)])
for i in range(5):
output_file_path = os.path.join(output_dir, "TimeMask_{:03d}.wav".format(i))
augmented_samples = augmenter(samples=samples, sample_rate=SAMPLE_RATE)
wavfile.write(output_file_path, rate=SAMPLE_RATE, data=augmented_samples)
# AddGaussianSNR
augmenter = Compose([AddGaussianSNR(p=1.0)])
for i in range(5):
output_file_path = os.path.join(
output_dir, "AddGaussianSNR_{:03d}.wav".format(i)
)
augmented_samples = augmenter(samples=samples, sample_rate=SAMPLE_RATE)
wavfile.write(output_file_path, rate=SAMPLE_RATE, data=augmented_samples)
# AddGaussianNoise
augmenter = Compose(
[AddGaussianNoise(min_amplitude=0.001, max_amplitude=0.015, p=1.0)]
)
for i in range(5):
output_file_path = os.path.join(
output_dir, "AddGaussianNoise_{:03d}.wav".format(i)
)
augmented_samples = augmenter(samples=samples, sample_rate=SAMPLE_RATE)
wavfile.write(output_file_path, rate=SAMPLE_RATE, data=augmented_samples)
# TimeStretch
augmenter = Compose([TimeStretch(min_rate=0.8, max_rate=1.25, p=1.0)])
for i in range(5):
output_file_path = os.path.join(output_dir, "TimeStretch_{:03d}.wav".format(i))
augmented_samples = augmenter(samples=samples, sample_rate=SAMPLE_RATE)
wavfile.write(output_file_path, rate=SAMPLE_RATE, data=augmented_samples)
# PitchShift
augmenter = Compose([PitchShift(min_semitones=-4, max_semitones=4, p=1.0)])
for i in range(5):
output_file_path = os.path.join(output_dir, "PitchShift_{:03d}.wav".format(i))
augmented_samples = augmenter(samples=samples, sample_rate=SAMPLE_RATE)
wavfile.write(output_file_path, rate=SAMPLE_RATE, data=augmented_samples)
# Shift
augmenter = Compose([Shift(min_fraction=-0.5, max_fraction=0.5, p=1.0)])
for i in range(5):
output_file_path = os.path.join(output_dir, "Shift_{:03d}.wav".format(i))
augmented_samples = augmenter(samples=samples, sample_rate=SAMPLE_RATE)
wavfile.write(output_file_path, rate=SAMPLE_RATE, data=augmented_samples)
# Shift without rollover
augmenter = Compose(
[Shift(min_fraction=-0.5, max_fraction=0.5, rollover=False, p=1.0)]
)
for i in range(5):
output_file_path = os.path.join(
output_dir, "ShiftWithoutRollover_{:03d}.wav".format(i)
)
augmented_samples = augmenter(samples=samples, sample_rate=SAMPLE_RATE)
wavfile.write(output_file_path, rate=SAMPLE_RATE, data=augmented_samples)
# Normalize
augmenter = Compose([Normalize(p=1.0)])
output_file_path = os.path.join(output_dir, "Normalize_{:03d}.wav".format(0))
augmented_samples = augmenter(samples=samples, sample_rate=SAMPLE_RATE)
wavfile.write(output_file_path, rate=SAMPLE_RATE, data=augmented_samples)
# Resample
augmenter = Compose([Resample(p=1.0)])
for i in range(5):
output_file_path = os.path.join(output_dir, "Resample_{:03d}.wav".format(i))
augmented_samples = augmenter(samples=samples, sample_rate=SAMPLE_RATE)
wavfile.write(output_file_path, rate=SAMPLE_RATE, data=augmented_samples)
# ClippingDistortion
augmenter = Compose([ClippingDistortion(p=1.0)])
for i in range(5):
output_file_path = os.path.join(
output_dir, "ClippingDistortion_{:03d}.wav".format(i)
)
augmented_samples = augmenter(samples=samples, sample_rate=SAMPLE_RATE)
wavfile.write(output_file_path, rate=SAMPLE_RATE, data=augmented_samples)
# AddBackgroundNoise
augmenter = Compose(
[
AddBackgroundNoise(
sounds_path=os.path.join(DEMO_DIR, "background_noises"), p=1.0
)
]
)
for i in range(5):
output_file_path = os.path.join(
output_dir, "AddBackgroundNoise_{:03d}.wav".format(i)
)
augmented_samples = augmenter(samples=samples, sample_rate=SAMPLE_RATE)
wavfile.write(output_file_path, rate=SAMPLE_RATE, data=augmented_samples)
# AddShortNoises
augmenter = Compose(
[
AddShortNoises(
sounds_path=os.path.join(DEMO_DIR, "short_noises"),
min_snr_in_db=0,
max_snr_in_db=8,
min_time_between_sounds=2.0,
max_time_between_sounds=4.0,
burst_probability=0.4,
min_pause_factor_during_burst=0.01,
max_pause_factor_during_burst=0.95,
min_fade_in_time=0.005,
max_fade_in_time=0.08,
min_fade_out_time=0.01,
max_fade_out_time=0.1,
p=1.0,
)
]
)
for i in range(5):
output_file_path = os.path.join(
output_dir, "AddShortNoises_{:03d}.wav".format(i)
)
augmented_samples = augmenter(samples=samples, sample_rate=SAMPLE_RATE)
wavfile.write(output_file_path, rate=SAMPLE_RATE, data=augmented_samples)
