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# 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 glob
import json
import os
import os.path
import subprocess
import tarfile
from typing import Optional
import wget
# Function to build a manifest
def build_manifest(transcripts_path, manifest_path, data_dir, mount_dir, wav_path):
# create manifest with reference to this directory. This is useful when mounting the dataset.
mount_dir = mount_dir if mount_dir else data_dir
with open(transcripts_path, 'r') as fin:
with open(manifest_path, 'w') as fout:
for line in fin:
# Lines look like this:
# <s> transcript </s> (fileID)
transcript = line[: line.find('(') - 1].lower()
transcript = transcript.replace('<s>', '').replace('</s>', '')
transcript = transcript.strip()
file_id = line[line.find('(') + 1 : -2] # e.g. "cen4-fash-b"
audio_path = os.path.join(
data_dir, wav_path, file_id[file_id.find('-') + 1 : file_id.rfind('-')], file_id + '.wav'
)
mounted_audio_path = os.path.join(
mount_dir, wav_path, file_id[file_id.find('-') + 1 : file_id.rfind('-')], file_id + '.wav'
)
# import sox here to not require sox to be available for importing all utils.
import sox
duration = sox.file_info.duration(audio_path)
# Write the metadata to the manifest
metadata = {"audio_filepath": mounted_audio_path, "duration": duration, "text": transcript}
json.dump(metadata, fout)
fout.write('\n')
def download_an4(data_dir: str = "./", train_mount_dir: Optional[str] = None, test_mount_dir: Optional[str] = None):
"""
Function to download the AN4 dataset. This hides pre-processing boilerplate for notebook ASR examples.
Args:
data_dir: Path to store the data.
train_mount_dir: If you plan to mount the dataset, use this to prepend the mount directory to the
audio filepath in the train manifest.
test_mount_dir: If you plan to mount the dataset, use this to prepend the mount directory to the
audio filepath in the test manifest.
"""
print("******")
os.makedirs(data_dir, exist_ok=True)
if not os.path.exists(data_dir + '/an4_sphere.tar.gz'):
an4_url = 'https://dldata-public.s3.us-east-2.amazonaws.com/an4_sphere.tar.gz'
an4_path = wget.download(an4_url, data_dir)
print(f"Dataset downloaded at: {an4_path}")
else:
print("Tarfile already exists.")
an4_path = data_dir + '/an4_sphere.tar.gz'
if not os.path.exists(data_dir + '/an4/'):
tar = tarfile.open(an4_path)
tar.extractall(path=data_dir)
print("Converting .sph to .wav...")
sph_list = glob.glob(data_dir + '/an4/**/*.sph', recursive=True)
for sph_path in sph_list:
wav_path = sph_path[:-4] + '.wav'
cmd = ["sox", sph_path, wav_path]
subprocess.run(cmd)
print("Finished conversion.\n******")
# Building Manifests
print("******")
train_transcripts = data_dir + '/an4/etc/an4_train.transcription'
train_manifest = data_dir + '/an4/train_manifest.json'
if not os.path.isfile(train_manifest):
build_manifest(train_transcripts, train_manifest, data_dir, train_mount_dir, 'an4/wav/an4_clstk')
print("Training manifest created.")
test_transcripts = data_dir + '/an4/etc/an4_test.transcription'
test_manifest = data_dir + '/an4/test_manifest.json'
if not os.path.isfile(test_manifest):
build_manifest(test_transcripts, test_manifest, data_dir, test_mount_dir, 'an4/wav/an4test_clstk')
print("Test manifest created.")
print("***Done***")
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