xiongxinlei
3 years ago
parent
b75268c588
commit
ec24a169ee
@ -0,0 +1,170 @@
|
|||||||
|
# Copyright (c) 2022 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.
|
||||||
|
"""
|
||||||
|
Convert the PaddleSpeech jsonline format to csv format
|
||||||
|
Currently, Speaker Identificaton Training process need csv format.
|
||||||
|
"""
|
||||||
|
import argparse
|
||||||
|
import os
|
||||||
|
import jsonlines
|
||||||
|
import collections
|
||||||
|
import json
|
||||||
|
import csv
|
||||||
|
from yacs.config import CfgNode
|
||||||
|
import tqdm
|
||||||
|
from paddleaudio import load as load_audio
|
||||||
|
import random
|
||||||
|
from paddlespeech.vector.training.seeding import seed_everything
|
||||||
|
# voxceleb meta info for each training utterance segment
|
||||||
|
# we extract a segment from a utterance to train
|
||||||
|
# and the segment' period is between start and stop time point in the original wav file
|
||||||
|
# each field in the meta means as follows:
|
||||||
|
# id: the utterance segment name
|
||||||
|
# duration: utterance segment time
|
||||||
|
# wav: utterance file path
|
||||||
|
# start: start point in the original wav file
|
||||||
|
# stop: stop point in the original wav file
|
||||||
|
# spk_id: the utterance segment's speaker name
|
||||||
|
meta_info = collections.namedtuple(
|
||||||
|
'META_INFO', ('id', 'duration', 'wav', 'start', 'stop', 'spk_id'))
|
||||||
|
|
||||||
|
def get_chunks(seg_dur, audio_id, audio_duration):
|
||||||
|
num_chunks = int(audio_duration / seg_dur) # all in milliseconds
|
||||||
|
chunk_lst = [
|
||||||
|
audio_id + "_" + str(i * seg_dur) + "_" + str(i * seg_dur + seg_dur)
|
||||||
|
for i in range(num_chunks)
|
||||||
|
]
|
||||||
|
return chunk_lst
|
||||||
|
|
||||||
|
def prepare_csv(wav_files, output_file, config, split_chunks=True):
|
||||||
|
if not os.path.exists(os.path.dirname(output_file)):
|
||||||
|
os.makedirs(os.path.dirname(output_file))
|
||||||
|
csv_lines = []
|
||||||
|
header = ["id", "duration", "wav", "start", "stop", "spk_id"]
|
||||||
|
for item in wav_files:
|
||||||
|
item = json.loads(item.strip())
|
||||||
|
audio_id = item['utt'].replace(".wav", "")
|
||||||
|
audio_duration = item['feat_shape'][0]
|
||||||
|
wav_file = item['feat']
|
||||||
|
spk_id = audio_id.split('-')[0]
|
||||||
|
waveform, sr = load_audio(wav_file)
|
||||||
|
if split_chunks:
|
||||||
|
uniq_chunks_list = get_chunks(config.chunk_duration, audio_id, audio_duration)
|
||||||
|
for chunk in uniq_chunks_list:
|
||||||
|
s, e = chunk.split("_")[-2:] # Timestamps of start and end
|
||||||
|
start_sample = int(float(s) * sr)
|
||||||
|
end_sample = int(float(e) * sr)
|
||||||
|
# id, duration, wav, start, stop, spk_id
|
||||||
|
csv_lines.append([
|
||||||
|
chunk, audio_duration, wav_file, start_sample, end_sample,
|
||||||
|
spk_id
|
||||||
|
])
|
||||||
|
else:
|
||||||
|
csv_lines.append([audio_id, audio_duration, wav_file, 0, waveform.shape[0], spk_id])
|
||||||
|
|
||||||
|
|
||||||
|
with open(output_file, mode="w") as csv_f:
|
||||||
|
csv_writer = csv.writer(csv_f, delimiter=',', quotechar='"', quoting=csv.QUOTE_MINIMAL)
|
||||||
|
csv_writer.writerow(header)
|
||||||
|
for line in csv_lines:
|
||||||
|
csv_writer.writerow(line)
|
||||||
|
|
||||||
|
def get_enroll_test_list(filelist, verification_file):
|
||||||
|
print(f"verification file: {verification_file}")
|
||||||
|
enroll_audios = set()
|
||||||
|
test_audios = set()
|
||||||
|
with open(verification_file, 'r') as f:
|
||||||
|
for line in f:
|
||||||
|
_, enroll_file, test_file = line.strip().split(' ')
|
||||||
|
enroll_audios.add('-'.join(enroll_file.split('/')))
|
||||||
|
test_audios.add('-'.join(test_file.split('/')))
|
||||||
|
|
||||||
|
enroll_files = []
|
||||||
|
test_files = []
|
||||||
|
for item in filelist:
|
||||||
|
with open(item, 'r') as f:
|
||||||
|
for line in f:
|
||||||
|
audio_id = json.loads(line.strip())['utt']
|
||||||
|
if audio_id in enroll_audios:
|
||||||
|
enroll_files.append(line)
|
||||||
|
if audio_id in test_audios:
|
||||||
|
test_files.append(line)
|
||||||
|
|
||||||
|
enroll_files = sorted(enroll_files)
|
||||||
|
test_files = sorted(test_files)
|
||||||
|
|
||||||
|
return enroll_files, test_files
|
||||||
|
|
||||||
|
def get_train_dev_list(filelist, target_dir, split_ratio):
|
||||||
|
if not os.path.exists(os.path.join(target_dir, "meta")):
|
||||||
|
os.makedirs(os.path.join(target_dir, "meta"))
|
||||||
|
|
||||||
|
audio_files = []
|
||||||
|
speakers = set()
|
||||||
|
for item in filelist:
|
||||||
|
with open(item, 'r') as f:
|
||||||
|
for line in f:
|
||||||
|
spk_id = json.loads(line.strip())['utt2spk']
|
||||||
|
speakers.add(spk_id)
|
||||||
|
audio_files.append(line.strip())
|
||||||
|
|
||||||
|
speakers = sorted(speakers)
|
||||||
|
with open(os.path.join(target_dir, "meta", "spk_id2label.txt"), 'w') as f:
|
||||||
|
for label, spk_id in enumerate(speakers):
|
||||||
|
f.write(f'{spk_id} {label}\n')
|
||||||
|
split_idx = int(split_ratio * len(audio_files))
|
||||||
|
random.shuffle(audio_files)
|
||||||
|
train_files, dev_files = audio_files[:split_idx], audio_files[split_idx:]
|
||||||
|
|
||||||
|
return train_files, dev_files
|
||||||
|
|
||||||
|
def prepare_data(args, config):
|
||||||
|
|
||||||
|
paddle.set_device("cpu")
|
||||||
|
seed_everything(config.seed)
|
||||||
|
|
||||||
|
enroll_files, test_files = get_enroll_test_list([args.test], verification_file=config.verification_file)
|
||||||
|
prepare_csv(enroll_files, os.path.join(args.target_dir, "csv", "enroll.csv"), config, split_chunks=False)
|
||||||
|
prepare_csv(test_files, os.path.join(args.target_dir, "csv", "test.csv"), config, split_chunks=False)
|
||||||
|
|
||||||
|
train_files, dev_files = get_train_dev_list(args.train, target_dir=args.target_dir, split_ratio=config.split_ratio)
|
||||||
|
prepare_csv(train_files, os.path.join(args.target_dir, "csv", "train.csv"), config)
|
||||||
|
prepare_csv(dev_files, os.path.join(args.target_dir, "csv", "dev.csv"), config)
|
||||||
|
|
||||||
|
if __name__ == "__main__":
|
||||||
|
parser = argparse.ArgumentParser(description=__doc__)
|
||||||
|
parser.add_argument(
|
||||||
|
"--train",
|
||||||
|
required=True,
|
||||||
|
nargs='+',
|
||||||
|
help="The jsonline files list for train")
|
||||||
|
parser.add_argument(
|
||||||
|
"--test", required=True, help="The jsonline file for test")
|
||||||
|
parser.add_argument(
|
||||||
|
"--target_dir",
|
||||||
|
required=True,
|
||||||
|
help="The target directory stores the csv files and meta file")
|
||||||
|
parser.add_argument("--config",
|
||||||
|
default=None,
|
||||||
|
required=True,
|
||||||
|
type=str,
|
||||||
|
help="configuration file")
|
||||||
|
args = parser.parse_args()
|
||||||
|
|
||||||
|
# parse the yaml config file
|
||||||
|
config = CfgNode(new_allowed=True)
|
||||||
|
if args.config:
|
||||||
|
config.merge_from_file(args.config)
|
||||||
|
|
||||||
|
prepare_data(args, config)
|
||||||
Loading…
Reference in new issue