add voxceleb and rirs noise dataset

pull/1630/head
xiongxinlei 3 years ago
parent 9944fec3d4
commit 965f486dd5

@ -81,6 +81,10 @@ def create_manifest(data_dir, manifest_path_prefix):
},
ensure_ascii=False))
manifest_path = manifest_path_prefix + '.' + dtype
if not os.path.exists(os.path.dirname(manifest_path)):
os.makedirs(os.path.dirname(manifest_path))
with codecs.open(manifest_path, 'w', 'utf-8') as fout:
for line in json_lines:
fout.write(line + '\n')

@ -0,0 +1,120 @@
# 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.
import collections
from paddle.io import Dataset
from paddleaudio import load as load_audio
class VoxCelebDataset(Dataset):
meta_info = collections.namedtuple(
'META_INFO', ('id', 'duration', 'wav', 'start', 'stop', 'spk_id'))
def __init__(self, csv_path, spk_id2label_path, config):
super().__init__()
self.csv_path = csv_path
self.spk_id2label_path = spk_id2label_path
self.config = config
self.data = self.load_data_csv()
self.spk_id2label = self.load_speaker_to_label()
def load_data_csv(self):
data = []
with open(self.csv_path, 'r') as rf:
for line in rf.readlines()[1:]:
audio_id, duration, wav, start, stop, spk_id = line.strip(
).split(',')
data.append(
self.meta_info(audio_id,
float(duration), wav,
int(start), int(stop), spk_id))
return data
def load_speaker_to_label(self):
with open(self.spk_id2label_path, 'r') as f:
for line in f.readlines():
spk_id, label = line.strip().split(' ')
self.spk_id2label[spk_id] = int(label)
def convert_to_record(self, idx: int):
sample = self.data[idx]
record = {}
# To show all fields in a namedtuple: `type(sample)._fields`
for field in type(sample)._fields:
record[field] = getattr(sample, field)
waveform, sr = load_audio(record['wav'])
# random select a chunk audio samples from the audio
if self.config.random_chunk:
num_wav_samples = waveform.shape[0]
num_chunk_samples = int(self.config.chunk_duration * sr)
start = random.randint(0, num_wav_samples - num_chunk_samples - 1)
stop = start + num_chunk_samples
else:
start = record['start']
stop = record['stop']
# we only return the waveform as feat
waveform = waveform[start:stop]
record.update({'feat': waveform})
record.update({'label': self.spk_id2label[record['spk_id']]})
return record
def __getitem__(self, idx):
return self.convert_to_record(idx)
def __len__(self):
return len(self.data)
class RIRSNoiseDataset(Dataset):
meta_info = collections.namedtuple('META_INFO', ('id', 'duration', 'wav'))
def __init__(self, csv_path):
super().__init__()
self.csv_path = csv_path
self.data = self.load_csv_data()
def load_csv_data(self):
data = []
with open(self.csv_path, 'r') as rf:
for line in rf.readlines()[1:]:
audio_id, duration, wav = line.strip().split(',')
data.append(self.meta_info(audio_id, float(duration), wav))
random.shuffle(data)
return data
def convert_to_record(self, idx: int):
sample = self.data[idx]
record = {}
# To show all fields in a namedtuple: `type(sample)._fields`
for field in type(sample)._fields:
record[field] = getattr(sample, field)
waveform, sr = load_audio(record['wav'])
record.update({'feat': waveform})
return record
def __getitem__(self, idx):
return self.convert_to_record(idx)
def __len__(self):
return len(self.data)
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