File size: 2,735 Bytes
901e06a | 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 53 54 55 56 57 58 59 60 61 62 63 64 65 66 67 68 69 70 71 72 73 74 75 76 77 78 79 80 81 82 83 84 85 86 87 88 89 | #!/usr/bin/env python3
# Copyright (c) Facebook, Inc. and its affiliates.
#
# This source code is licensed under the MIT license found in the
# LICENSE file in the root directory of this source tree.
#
# Adapted from examples/wav2vec/wav2vec_manifest.py
"""
Data preparation for the speech normalizer
"""
import argparse
import glob
import os
import soundfile
from examples.speech_to_speech.preprocessing.data_utils import load_units, process_units
def process(args):
assert (
args.for_inference or args.target_unit is not None
), "missing --target-unit or --for-inference"
if not os.path.exists(args.output_dir):
os.makedirs(args.output_dir)
dir_path = os.path.realpath(args.audio_dir)
search_path = os.path.join(dir_path, "**/*." + args.ext)
if args.target_unit:
unit_data = load_units(args.target_unit)
with open(os.path.join(args.output_dir, f"{args.data_name}.tsv"), "w") as o_t, open(
os.path.join(args.output_dir, f"{args.data_name}.unit"), "w"
) as o_u:
print(dir_path, file=o_t)
for fname in glob.iglob(search_path, recursive=True):
file_path = os.path.realpath(fname)
frames = soundfile.info(fname).frames
print(
"{}\t{}".format(os.path.relpath(file_path, dir_path), frames), file=o_t
)
if args.for_inference:
print("0", file=o_u)
else:
sample_id = os.path.basename(file_path)[: -len(args.ext) - 1]
assert (
sample_id in unit_data
), f'{fname} does not have unit data in {args.target_unit}. Expecting sample_id "{sample_id}".'
target_units = process_units(unit_data[sample_id], reduce=True)
print(" ".join(target_units), file=o_u)
def main():
parser = argparse.ArgumentParser()
parser.add_argument("--audio-dir", required=True, type=str, help="audio directory")
parser.add_argument("--ext", default="flac", type=str, help="audio extension")
parser.add_argument(
"--data-name",
required=True,
type=str,
help="dataset name",
)
parser.add_argument(
"--output-dir", required=True, type=str, help="output directory"
)
parser.add_argument(
"--for-inference",
action="store_true",
help="set this if preparing data for running inference with a speech normalizer",
)
parser.add_argument(
"--target-unit",
default=None,
type=str,
help="a file containing unit sequences in the format: sample_id|u1 u2 ...",
)
args = parser.parse_args()
process(args)
if __name__ == "__main__":
main()
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