# coding=utf-8
# Copyright (C) 2020 ATHENA AUTHORS; Yiping Peng; Ne Luo
# 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.
# ==============================================================================
# Only support eager mode and TF>=2.0.0
# pylint: disable=no-member, invalid-name, relative-beyond-top-level
# pylint: disable=too-many-locals, too-many-statements, too-many-arguments, too-many-instance-attributes
""" voxceleb 1 & 2 """
import hashlib
import os
import subprocess
import sys
import zipfile
import pandas
import soundfile as sf
from absl import logging
SUBSETS = {
"vox1_dev_wav": [
"https://thor.robots.ox.ac.uk/~vgg/data/voxceleb/vox1a/vox1_dev_wav_partaa",
"https://thor.robots.ox.ac.uk/~vgg/data/voxceleb/vox1a/vox1_dev_wav_partab",
"https://thor.robots.ox.ac.uk/~vgg/data/voxceleb/vox1a/vox1_dev_wav_partac",
"https://thor.robots.ox.ac.uk/~vgg/data/voxceleb/vox1a/vox1_dev_wav_partad",
],
"vox1_test_wav": ["https://thor.robots.ox.ac.uk/~vgg/data/voxceleb/vox1a/vox1_test_wav.zip"],
"vox2_dev_aac": [
"https://thor.robots.ox.ac.uk/~vgg/data/voxceleb/vox1a/vox2_dev_aac_partaa",
"https://thor.robots.ox.ac.uk/~vgg/data/voxceleb/vox1a/vox2_dev_aac_partab",
"https://thor.robots.ox.ac.uk/~vgg/data/voxceleb/vox1a/vox2_dev_aac_partac",
"https://thor.robots.ox.ac.uk/~vgg/data/voxceleb/vox1a/vox2_dev_aac_partad",
"https://thor.robots.ox.ac.uk/~vgg/data/voxceleb/vox1a/vox2_dev_aac_partae",
"https://thor.robots.ox.ac.uk/~vgg/data/voxceleb/vox1a/vox2_dev_aac_partaf",
"https://thor.robots.ox.ac.uk/~vgg/data/voxceleb/vox1a/vox2_dev_aac_partag",
"https://thor.robots.ox.ac.uk/~vgg/data/voxceleb/vox1a/vox2_dev_aac_partah",
],
"vox2_test_aac": ["https://thor.robots.ox.ac.uk/~vgg/data/voxceleb/vox1a/vox2_test_aac.zip"],
}
MD5SUM = {
"vox1_dev_wav": "ae63e55b951748cc486645f532ba230b",
"vox2_dev_aac": "bbc063c46078a602ca71605645c2a402",
"vox1_test_wav": "185fdc63c3c739954633d50379a3d102",
"vox2_test_aac": "0d2b3ea430a821c33263b5ea37ede312",
}
USER = {"user": "", "password": ""}
speaker_id_dict = {}
def download_and_extract(directory, subset, urls):
"""Download and extract the given split of dataset.
Args:
directory: the directory where to put the downloaded data.
subset: subset name of the corpus.
urls: the list of urls to download the data file.
"""
os.makedirs(directory, exist_ok=True)
try:
for url in urls:
zip_filepath = os.path.join(directory, url.split("/")[-1])
if os.path.exists(zip_filepath):
continue
logging.info("Downloading %s to %s" % (url, zip_filepath))
subprocess.call(
"wget %s --user %s --password %s -O %s" % (url, USER["user"], USER["password"], zip_filepath),
shell=True,
)
statinfo = os.stat(zip_filepath)
logging.info("Successfully downloaded %s, size(bytes): %d" % (url, statinfo.st_size))
# concatenate all parts into zip files
if ".zip" not in zip_filepath:
zip_filepath = "_".join(zip_filepath.split("_")[:-1])
subprocess.call("cat %s* > %s.zip" % (zip_filepath, zip_filepath), shell=True)
zip_filepath += ".zip"
extract_path = zip_filepath.strip(".zip")
# check zip file md5sum
with open(zip_filepath, "rb") as f_zip:
md5 = hashlib.md5(f_zip.read()).hexdigest()
if md5 != MD5SUM[subset]:
raise ValueError("md5sum of %s mismatch" % zip_filepath)
with zipfile.ZipFile(zip_filepath, "r") as zfile:
zfile.extractall(directory)
extract_path_ori = os.path.join(directory, zfile.infolist()[0].filename)
subprocess.call("mv %s %s" % (extract_path_ori, extract_path), shell=True)
finally:
# os.remove(zip_filepath)
pass
def exec_cmd(cmd):
"""Run a command in a subprocess.
Args:
cmd: command line to be executed.
Return:
int, the return code.
"""
try:
retcode = subprocess.call(cmd, shell=True)
if retcode < 0:
logging.info(f"Child was terminated by signal {retcode}")
except OSError as e:
logging.info(f"Execution failed: {e}")
retcode = -999
return retcode
def decode_aac_with_ffmpeg(aac_file, wav_file):
"""Decode a given AAC file into WAV using ffmpeg.
Args:
aac_file: file path to input AAC file.
wav_file: file path to output WAV file.
Return:
bool, True if success.
"""
cmd = f"ffmpeg -i {aac_file} {wav_file}"
logging.info(f"Decoding aac file using command line: {cmd}")
ret = exec_cmd(cmd)
if ret != 0:
logging.error(f"Failed to decode aac file with retcode {ret}")
logging.error("Please check your ffmpeg installation.")
return False
return True
def convert_audio_and_make_label(input_dir, subset, output_dir, output_file):
"""Optionally convert AAC to WAV and make speaker labels.
Args:
input_dir: the directory which holds the input dataset.
subset: the name of the specified subset. e.g. vox1_dev_wav
output_dir: the directory to place the newly generated csv files.
output_file: the name of the newly generated csv file. e.g. vox1_dev_wav.csv
"""
logging.info("Preprocessing audio and label for subset %s" % subset)
source_dir = os.path.join(input_dir, subset)
files = []
# Convert all AAC file into WAV format. At the same time, generate the csv
for root, _, filenames in os.walk(source_dir):
for filename in filenames:
name, ext = os.path.splitext(filename)
if ext.lower() == ".wav":
_, ext2 = os.path.splitext(name)
if ext2:
continue
wav_file = os.path.join(root, filename)
elif ext.lower() == ".m4a":
# Convert AAC to WAV.
aac_file = os.path.join(root, filename)
wav_file = aac_file + ".wav"
if not os.path.exists(wav_file):
if not decode_aac_with_ffmpeg(aac_file, wav_file):
raise RuntimeError("Audio decoding failed.")
else:
continue
speaker_name = root.split(os.path.sep)[-2]
if speaker_name not in speaker_id_dict:
num = len(speaker_id_dict)
speaker_id_dict[speaker_name] = num
# wav_filesize = os.path.getsize(wav_file)
wav_length = len(sf.read(wav_file)[0])
files.append((os.path.abspath(wav_file), wav_length, speaker_id_dict[speaker_name], speaker_name))
# Write to CSV file which contains four columns:
# "wav_filename", "wav_length_ms", "speaker_id", "speaker_name".
csv_file_path = os.path.join(output_dir, output_file)
df = pandas.DataFrame(data=files, columns=["wav_filename", "wav_length_ms", "speaker_id", "speaker_name"])
df.to_csv(csv_file_path, index=False, sep="\t")
logging.info("Successfully generated csv file {}".format(csv_file_path))
def processor(directory, subset, force_process):
"""download and process"""
urls = SUBSETS
if subset not in urls:
raise ValueError(subset, "is not in voxceleb")
subset_csv = os.path.join(directory, subset + ".csv")
if not force_process and os.path.exists(subset_csv):
return subset_csv
logging.info("Downloading and process the voxceleb in %s", directory)
logging.info("Preparing subset %s", subset)
download_and_extract(directory, subset, urls[subset])
convert_audio_and_make_label(directory, subset, directory, subset + ".csv")
logging.info("Finished downloading and processing")
return subset_csv
if __name__ == "__main__":
logging.set_verbosity(logging.INFO)
if len(sys.argv) != 4:
print("Usage: python prepare_data.py save_directory user password")
sys.exit()
DIR, USER["user"], USER["password"] = sys.argv[1], sys.argv[2], sys.argv[3]
for SUBSET in SUBSETS:
processor(DIR, SUBSET, False)