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| import os | |
| import sys | |
| sys.path.append(os.getcwd()) | |
| import json | |
| from importlib.resources import files | |
| from pathlib import Path | |
| from tqdm import tqdm | |
| import soundfile as sf | |
| from datasets.arrow_writer import ArrowWriter | |
| def main(): | |
| result = [] | |
| duration_list = [] | |
| text_vocab_set = set() | |
| with open(meta_info, "r") as f: | |
| lines = f.readlines() | |
| for line in tqdm(lines): | |
| uttr, text, norm_text = line.split("|") | |
| norm_text = norm_text.strip() | |
| wav_path = Path(dataset_dir) / "wavs" / f"{uttr}.wav" | |
| duration = sf.info(wav_path).duration | |
| if duration < 0.4 or duration > 30: | |
| continue | |
| result.append({"audio_path": str(wav_path), "text": norm_text, "duration": duration}) | |
| duration_list.append(duration) | |
| text_vocab_set.update(list(norm_text)) | |
| # save preprocessed dataset to disk | |
| if not os.path.exists(f"{save_dir}"): | |
| os.makedirs(f"{save_dir}") | |
| print(f"\nSaving to {save_dir} ...") | |
| with ArrowWriter(path=f"{save_dir}/raw.arrow") as writer: | |
| for line in tqdm(result, desc="Writing to raw.arrow ..."): | |
| writer.write(line) | |
| # dup a json separately saving duration in case for DynamicBatchSampler ease | |
| with open(f"{save_dir}/duration.json", "w", encoding="utf-8") as f: | |
| json.dump({"duration": duration_list}, f, ensure_ascii=False) | |
| # vocab map, i.e. tokenizer | |
| # add alphabets and symbols (optional, if plan to ft on de/fr etc.) | |
| with open(f"{save_dir}/vocab.txt", "w") as f: | |
| for vocab in sorted(text_vocab_set): | |
| f.write(vocab + "\n") | |
| print(f"\nFor {dataset_name}, sample count: {len(result)}") | |
| print(f"For {dataset_name}, vocab size is: {len(text_vocab_set)}") | |
| print(f"For {dataset_name}, total {sum(duration_list)/3600:.2f} hours") | |
| if __name__ == "__main__": | |
| tokenizer = "char" # "pinyin" | "char" | |
| dataset_dir = "<SOME_PATH>/LJSpeech-1.1" | |
| dataset_name = f"LJSpeech_{tokenizer}" | |
| meta_info = os.path.join(dataset_dir, "metadata.csv") | |
| save_dir = str(files("f5_tts").joinpath("../../")) + f"/data/{dataset_name}" | |
| print(f"\nPrepare for {dataset_name}, will save to {save_dir}\n") | |
| main() | |