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PaddleSpeech/examples/csmsc/voc5/local/link_wav.py

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2.8 KiB

# Copyright (c) 2021 PaddlePaddle Authors. 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 argparse
import os
from operator import itemgetter
from pathlib import Path
import jsonlines
import numpy as np
def main():
# parse config and args
parser = argparse.ArgumentParser(
description="Preprocess audio and then extract features .")
parser.add_argument(
"--old-dump-dir",
default=None,
type=str,
help="directory to dump feature files.")
parser.add_argument(
"--dump-dir",
type=str,
required=True,
help="directory to finetune dump feature files.")
args = parser.parse_args()
old_dump_dir = Path(args.old_dump_dir).expanduser()
old_dump_dir = old_dump_dir.resolve()
dump_dir = Path(args.dump_dir).expanduser()
# use absolute path
dump_dir = dump_dir.resolve()
dump_dir.mkdir(parents=True, exist_ok=True)
assert old_dump_dir.is_dir()
assert dump_dir.is_dir()
for sub in ["train", "dev", "test"]:
# 把 old_dump_dir 里面的 *-wave.npy 软连接到 dump_dir 的对应位置
output_dir = dump_dir / sub
output_dir.mkdir(parents=True, exist_ok=True)
results = []
for name in os.listdir(output_dir / "raw"):
# 003918_feats.npy
utt_id = name.split("_")[0]
mel_path = output_dir / ("raw/" + name)
gen_mel = np.load(mel_path)
wave_name = utt_id + "_wave.npy"
wav = np.load(old_dump_dir / sub / ("raw/" + wave_name))
os.symlink(old_dump_dir / sub / ("raw/" + wave_name),
output_dir / ("raw/" + wave_name))
num_sample = wav.shape[0]
num_frames = gen_mel.shape[0]
wav_path = output_dir / ("raw/" + wave_name)
record = {
"utt_id": utt_id,
"num_samples": num_sample,
"num_frames": num_frames,
"feats": str(mel_path),
"wave": str(wav_path),
}
results.append(record)
results.sort(key=itemgetter("utt_id"))
with jsonlines.open(output_dir / "raw/metadata.jsonl", 'w') as writer:
for item in results:
writer.write(item)
if __name__ == "__main__":
main()