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| # Copyright (c) 2022, NVIDIA CORPORATION. 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 argparse | |
| import json | |
| import tarfile | |
| import urllib.request | |
| from pathlib import Path | |
| import sox | |
| import wget | |
| from tqdm import tqdm | |
| try: | |
| from nemo_text_processing.text_normalization.normalize import Normalizer | |
| except (ImportError, ModuleNotFoundError): | |
| raise ModuleNotFoundError( | |
| "The package `nemo_text_processing` was not installed in this environment. Please refer to" | |
| " https://github.com/NVIDIA/NeMo-text-processing and install this package before using " | |
| "this script" | |
| ) | |
| def get_args(): | |
| parser = argparse.ArgumentParser(description='Download LJSpeech and create manifests with predefined split') | |
| parser.add_argument("--data-root", required=True, type=Path) | |
| args = parser.parse_args() | |
| return args | |
| URL = "https://data.keithito.com/data/speech/LJSpeech-1.1.tar.bz2" | |
| FILELIST_BASE = 'https://raw.githubusercontent.com/NVIDIA/tacotron2/master/filelists' | |
| def __maybe_download_file(source_url, destination_path): | |
| if not destination_path.exists(): | |
| tmp_file_path = destination_path.with_suffix('.tmp') | |
| urllib.request.urlretrieve(source_url, filename=str(tmp_file_path)) | |
| tmp_file_path.rename(destination_path) | |
| def __extract_file(filepath, data_dir): | |
| try: | |
| tar = tarfile.open(filepath) | |
| tar.extractall(data_dir) | |
| tar.close() | |
| except Exception: | |
| print(f"Error while extracting {filepath}. Already extracted?") | |
| def __process_data(data_root): | |
| text_normalizer = Normalizer( | |
| lang="en", input_case="cased", overwrite_cache=True, cache_dir=data_root / "cache_dir", | |
| ) | |
| text_normalizer_call_kwargs = {"punct_pre_process": True, "punct_post_process": True} | |
| normalizer_call = lambda x: text_normalizer.normalize(x, **text_normalizer_call_kwargs) | |
| # Create manifests (based on predefined NVIDIA's split) | |
| filelists = ['train', 'val', 'test'] | |
| for split in tqdm(filelists): | |
| # Download file list if necessary | |
| filelist_path = data_root / f"ljs_audio_text_{split}_filelist.txt" | |
| if not filelist_path.exists(): | |
| wget.download(f"{FILELIST_BASE}/ljs_audio_text_{split}_filelist.txt", out=str(data_root)) | |
| manifest_target = data_root / f"{split}_manifest.json" | |
| with open(manifest_target, 'w') as f_out: | |
| with open(filelist_path, 'r') as filelist: | |
| print(f"\nCreating {manifest_target}...") | |
| for line in tqdm(filelist): | |
| basename = line[6:16] | |
| text = line[21:].strip() | |
| norm_text = normalizer_call(text) | |
| # Make sure corresponding wavfile exists | |
| wav_path = data_root / 'wavs' / f"{basename}.wav" | |
| assert wav_path.exists(), f"{wav_path} does not exist!" | |
| entry = { | |
| 'audio_filepath': str(wav_path), | |
| 'duration': sox.file_info.duration(wav_path), | |
| 'text': text, | |
| 'normalized_text': norm_text, | |
| } | |
| f_out.write(json.dumps(entry) + '\n') | |
| def main(): | |
| args = get_args() | |
| tarred_data_path = args.data_root / "LJSpeech-1.1.tar.bz2" | |
| __maybe_download_file(URL, tarred_data_path) | |
| __extract_file(str(tarred_data_path), str(args.data_root)) | |
| data_root = args.data_root / "LJSpeech-1.1" | |
| __process_data(data_root) | |
| if __name__ == '__main__': | |
| main() | |