diff --git a/data_utils/augmentor/augmentation.py b/data_utils/augmentor/augmentation.py index 9dced473..8a50e440 100644 --- a/data_utils/augmentor/augmentation.py +++ b/data_utils/augmentor/augmentation.py @@ -8,6 +8,7 @@ import random from data_utils.augmentor.volume_perturb import VolumePerturbAugmentor from data_utils.augmentor.shift_perturb import ShiftPerturbAugmentor from data_utils.augmentor.speed_perturb import SpeedPerturbAugmentor +from data_utils.augmentor.noise_perturb import NoisePerturbAugmentor from data_utils.augmentor.resample import ResampleAugmentor from data_utils.augmentor.online_bayesian_normalization import \ OnlineBayesianNormalizationAugmentor @@ -89,5 +90,7 @@ class AugmentationPipeline(object): return ResampleAugmentor(self._rng, **params) elif augmentor_type == "bayesian_normal": return OnlineBayesianNormalizationAugmentor(self._rng, **params) + elif augmentor_type == "noise": + return NoisePerturbAugmentor(self._rng, **params) else: raise ValueError("Unknown augmentor type [%s]." % augmentor_type) diff --git a/data_utils/augmentor/noise_perturb.py b/data_utils/augmentor/noise_perturb.py new file mode 100644 index 00000000..c97ab843 --- /dev/null +++ b/data_utils/augmentor/noise_perturb.py @@ -0,0 +1,47 @@ +"""Contains the noise perturb augmentation model.""" +from __future__ import absolute_import +from __future__ import division +from __future__ import print_function + +from data_utils.augmentor.base import AugmentorBase +from data_utils import utils +from data_utils.speech import SpeechSegment + + +class NoisePerturbAugmentor(AugmentorBase): + """Augmentation model for adding background noise. + + :param rng: Random generator object. + :type rng: random.Random + :param min_snr_dB: Minimal signal noise ratio, in decibels. + :type min_snr_dB: float + :param max_snr_dB: Maximal signal noise ratio, in decibels. + :type max_snr_dB: float + """ + + def __init__(self, rng, min_snr_dB, max_snr_dB, noise_manifest): + self._min_snr_dB = min_snr_dB + self._max_snr_dB = max_snr_dB + self._rng = rng + self._manifest = utils.read_manifest(manifest_path=noise_manifest) + + def transform_audio(self, audio_segment): + """Add background noise audio. + + Note that this is an in-place transformation. + + :param audio_segment: Audio segment to add effects to. + :type audio_segment: AudioSegmenet|SpeechSegment + """ + noise_json = self._rng.sample(self._manifest, 1)[0] + if noise_json['duration'] < audio_segment.duration: + raise RuntimeError("The duration of sampled noise audio is smaller " + "than the audio segment to add effects to.") + diff_duration = noise_json['duration'] - audio_segment.duration + start = self._rng.uniform(0, diff_duration) + end = start + audio_segment.duration + noise_segment = SpeechSegment.slice_from_file( + noise_json['audio_filepath'], transcript="", start=start, end=end) + snr_dB = self._rng.uniform(self._min_snr_dB, self._max_snr_dB) + audio_segment.add_noise( + noise_segment, snr_dB, allow_downsampling=True, rng=self._rng) diff --git a/data_utils/augmentor/online_bayesian_normalization.py b/data_utils/augmentor/online_bayesian_normalization.py old mode 100755 new mode 100644 diff --git a/data_utils/augmentor/resample.py b/data_utils/augmentor/resample.py old mode 100755 new mode 100644 diff --git a/datasets/noise/chime3_background.py b/datasets/noise/chime3_background.py new file mode 100644 index 00000000..f79ca733 --- /dev/null +++ b/datasets/noise/chime3_background.py @@ -0,0 +1,128 @@ +"""Prepare CHiME3 background data. + +Download, unpack and create manifest files. +Manifest file is a json-format file with each line containing the +meta data (i.e. audio filepath, transcript and audio duration) +of each audio file in the data set. +""" +from __future__ import absolute_import +from __future__ import division +from __future__ import print_function + +import distutils.util +import os +import wget +import zipfile +import argparse +import soundfile +import json +from paddle.v2.dataset.common import md5file + +DATA_HOME = os.path.expanduser('~/.cache/paddle/dataset/speech') + +URL = "https://d4s.myairbridge.com/packagev2/AG0Y3DNBE5IWRRTV/?dlid=W19XG7T0NNHB027139H0EQ" +MD5 = "c3ff512618d7a67d4f85566ea1bc39ec" + +parser = argparse.ArgumentParser(description=__doc__) +parser.add_argument( + "--target_dir", + default=DATA_HOME + "/chime3_background", + type=str, + help="Directory to save the dataset. (default: %(default)s)") +parser.add_argument( + "--manifest_filepath", + default="manifest.chime3.background", + type=str, + help="Filepath for output manifests. (default: %(default)s)") +args = parser.parse_args() + + +def download(url, md5sum, target_dir, filename=None): + """Download file from url to target_dir, and check md5sum.""" + if filename == None: + filename = url.split("/")[-1] + if not os.path.exists(target_dir): os.makedirs(target_dir) + filepath = os.path.join(target_dir, filename) + if not (os.path.exists(filepath) and md5file(filepath) == md5sum): + print("Downloading %s ..." % url) + wget.download(url, target_dir) + print("\nMD5 Chesksum %s ..." % filepath) + if not md5file(filepath) == md5sum: + raise RuntimeError("MD5 checksum failed.") + else: + print("File exists, skip downloading. (%s)" % filepath) + return filepath + + +def unpack(filepath, target_dir): + """Unpack the file to the target_dir.""" + print("Unpacking %s ..." % filepath) + if filepath.endswith('.zip'): + zip = zipfile.ZipFile(filepath, 'r') + zip.extractall(target_dir) + zip.close() + elif filepath.endswith('.tar') or filepath.endswith('.tar.gz'): + tar = zipfile.open(filepath) + tar.extractall(target_dir) + tar.close() + else: + raise ValueError("File format is not supported for unpacking.") + + +def create_manifest(data_dir, manifest_path): + """Create a manifest json file summarizing the data set, with each line + containing the meta data (i.e. audio filepath, transcription text, audio + duration) of each audio file within the data set. + """ + print("Creating manifest %s ..." % manifest_path) + json_lines = [] + for subfolder, _, filelist in sorted(os.walk(data_dir)): + for filename in filelist: + if filename.endswith('.wav'): + filepath = os.path.join(data_dir, subfolder, filename) + audio_data, samplerate = soundfile.read(filepath) + duration = float(len(audio_data)) / samplerate + json_lines.append( + json.dumps({ + 'audio_filepath': filepath, + 'duration': duration, + 'text': '' + })) + with open(manifest_path, 'w') as out_file: + for line in json_lines: + out_file.write(line + '\n') + + +def prepare_chime3(url, md5sum, target_dir, manifest_path): + """Download, unpack and create summmary manifest file.""" + if not os.path.exists(os.path.join(target_dir, "CHiME3")): + # download + filepath = download(url, md5sum, target_dir, + "myairbridge-AG0Y3DNBE5IWRRTV.zip") + # unpack + unpack(filepath, target_dir) + unpack( + os.path.join(target_dir, 'CHiME3_background_bus.zip'), target_dir) + unpack( + os.path.join(target_dir, 'CHiME3_background_caf.zip'), target_dir) + unpack( + os.path.join(target_dir, 'CHiME3_background_ped.zip'), target_dir) + unpack( + os.path.join(target_dir, 'CHiME3_background_str.zip'), target_dir) + else: + print("Skip downloading and unpacking. Data already exists in %s." % + target_dir) + # create manifest json file + create_manifest(target_dir, manifest_path) + + +def main(): + prepare_chime3( + url=URL, + md5sum=MD5, + target_dir=args.target_dir, + manifest_path=args.manifest_filepath) + + +if __name__ == '__main__': + main() diff --git a/datasets/run_all.sh b/datasets/run_all.sh index ef2b721f..61747a50 100644 --- a/datasets/run_all.sh +++ b/datasets/run_all.sh @@ -6,8 +6,17 @@ if [ $? -ne 0 ]; then fi cd - +cd noise +python chime3_background.py +if [ $? -ne 0 ]; then + echo "Prepare CHiME3 background noise failed. Terminated." + exit 1 +fi +cd - + cat librispeech/manifest.train* | shuf > manifest.train cat librispeech/manifest.dev-clean > manifest.dev cat librispeech/manifest.test-clean > manifest.test +cat noise/manifest.* > manifest.noise echo "All done."