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# Copyright (c) 2023 Amphion.
#
# This source code is licensed under the MIT license found in the
# LICENSE file in the root directory of this source tree.
import os
import json
import torchaudio
from tqdm import tqdm
from glob import glob
from utils.util import has_existed
def main(output_path, dataset_path):
print("-" * 10)
print("Dataset splits for ljspeech...\n")
save_dir = os.path.join(output_path, "ljspeech")
ljspeech_path = dataset_path
wave_files = glob(ljspeech_path + "/wavs/*.wav")
train_output_file = os.path.join(save_dir, "train.json")
test_output_file = os.path.join(save_dir, "test.json")
if has_existed(train_output_file):
return
utts = []
for wave_file in tqdm(wave_files):
res = {
"Dataset": "ljspeech",
"Singer": "female1",
"Uid": "{}".format(wave_file.split("/")[-1].split(".")[0]),
}
res["Path"] = wave_file
assert os.path.exists(res["Path"])
waveform, sample_rate = torchaudio.load(res["Path"])
duration = waveform.size(-1) / sample_rate
res["Duration"] = duration
if duration <= 1e-8:
continue
utts.append(res)
test_length = len(utts) // 20
train_utts = []
train_index_count = 0
train_total_duration = 0
for i in tqdm(range(len(utts) - test_length)):
tmp = utts[i]
tmp["index"] = train_index_count
train_index_count += 1
train_total_duration += tmp["Duration"]
train_utts.append(tmp)
test_utts = []
test_index_count = 0
test_total_duration = 0
for i in tqdm(range(len(utts) - test_length, len(utts))):
tmp = utts[i]
tmp["index"] = test_index_count
test_index_count += 1
test_total_duration += tmp["Duration"]
test_utts.append(tmp)
print("#Train = {}, #Test = {}".format(len(train_utts), len(test_utts)))
print(
"#Train hours= {}, #Test hours= {}".format(
train_total_duration / 3600, test_total_duration / 3600
)
)
# Save
os.makedirs(save_dir, exist_ok=True)
with open(train_output_file, "w") as f:
json.dump(train_utts, f, indent=4, ensure_ascii=False)
with open(test_output_file, "w") as f:
json.dump(test_utts, f, indent=4, ensure_ascii=False)
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