| import os |
|
|
| import librosa |
| import numpy as np |
| from scipy.io import wavfile |
| from tqdm import tqdm |
|
|
|
|
| def prepare_align(config): |
| in_dir = config["path"]["corpus_path"] |
| out_dir = config["path"]["raw_path"] |
| sampling_rate = config["preprocessing"]["audio"]["sampling_rate"] |
| max_wav_value = config["preprocessing"]["audio"]["max_wav_value"] |
| for dataset in ["train", "test"]: |
| print("Processing {}ing set...".format(dataset)) |
| with open(os.path.join(in_dir, dataset, "content.txt"), encoding="utf-8") as f: |
| for line in tqdm(f): |
| wav_name, text = line.strip("\n").split("\t") |
| speaker = wav_name[:7] |
| text = text.split(" ")[1::2] |
| wav_path = os.path.join(in_dir, dataset, "wav", speaker, wav_name) |
| if os.path.exists(wav_path): |
| os.makedirs(os.path.join(out_dir, speaker), exist_ok=True) |
| wav, _ = librosa.load(wav_path, sampling_rate) |
| wav = wav / max(abs(wav)) * max_wav_value |
| wavfile.write( |
| os.path.join(out_dir, speaker, wav_name), |
| sampling_rate, |
| wav.astype(np.int16), |
| ) |
| with open( |
| os.path.join(out_dir, speaker, "{}.lab".format(wav_name[:11])), |
| "w", |
| ) as f1: |
| f1.write(" ".join(text)) |
