Datasets:
File size: 1,669 Bytes
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#!/usr/bin/env python3
import os
import torchaudio
import tqdm
SAMPLE_RATE = 16_000
path = "/home/patrick/kaldi/egs/ami/s5/mdm_downloaded/{folder}/audio/{folder}.Array1-01.wav"
new_path = "/home/patrick/ami/audio/sdm"
for split in ["train", "dev", "eval"]:
new_split_path = os.path.join(new_path, split)
audio_chunks_path = os.path.join("/home/patrick/ami/annotations/", split, "segments")
files = {}
with open(audio_chunks_path, "r") as f:
lines = f.readlines()
for line in lines:
file_name, folder, start_time, end_time = line.strip().split()
folder = folder.split("_")[1]
os.system(f"mkdir -p {os.path.join(new_split_path, folder)}")
if folder not in files:
files[folder] = []
files[folder].append((file_name, start_time, end_time))
for folder, audios in tqdm.tqdm(files.items()):
orig_file = path.format(folder=folder)
try:
waveform, sr = torchaudio.load(orig_file)
except:
print(f"File {orig_file} does not exist!")
continue
# for file_name, start_time, end_time in audios:
# chunk = waveform[:, int(SAMPLE_RATE * float(start_time)): int(SAMPLE_RATE * float(end_time))]
# out_path = f"{split}_{file_name.lower().replace('h00', 'sdm')}.wav"
# out_path = os.path.join(new_split_path, folder, out_path)
# torchaudio.save(out_path, chunk, sr)
abs_folder = os.path.join(new_split_path, folder)
os.system(f"cd {new_split_path} && tar -czf {folder}.tar.gz {folder}")
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