def preprocess(args, input_folders, out_dir, hparams): mel_dir = os.path.join(out_dir, 'mels') wav_dir = os.path.join(out_dir, 'audio') linear_dir = os.path.join(out_dir, 'linear') os.makedirs(mel_dir, exist_ok=True) os.makedirs(wav_dir, exist_ok=True) os.makedirs(linear_dir, exist_ok=True) if args.dataset.startswith('liepa'): metadata = preprocessor_liepa.build_from_path(hparams, input_folders, None, mel_dir, linear_dir, wav_dir, args.n_jobs, tqdm=tqdm) else: metadata = preprocessor.build_from_path(hparams, input_folders, mel_dir, linear_dir, wav_dir, args.n_jobs, tqdm=tqdm) write_metadata(metadata, out_dir)
def preprocess(args, input_folders, output_dir, hparams): mel_frames, timesteps = 0, 0 max_text_lens, max_mel_lens, max_timestep_lens = [], [], [] for input_dir in input_folders: wav_dir = os.path.join(output_dir, input_dir.split('/')[-1], 'audio') mel_dir = os.path.join(output_dir, input_dir.split('/')[-1], 'mels') os.makedirs(wav_dir, exist_ok=True) os.makedirs(mel_dir, exist_ok=True) metadata = preprocessor.build_from_path(hparams, input_dir, wav_dir, mel_dir, args.n_jobs, tqdm=tqdm) with open( os.path.join(output_dir, input_dir.split('/')[-1], 'train.txt'), 'w') as f: for m in metadata: f.write('|'.join([str(x) for x in m]) + '\n') max_text_lens.append(max(len(m[3]) for m in metadata)) max_mel_lens.append(max(int(m[2]) for m in metadata)) max_timestep_lens.append(max(m[1] for m in metadata)) mel_frames += sum([int(m[2]) for m in metadata]) timesteps += sum([int(m[1]) for m in metadata]) hours = timesteps / hparams.sample_rate / 3600 print( f'Write {len(metadata)} utterances, {mel_frames} mel frames, {timesteps} audio timesteps, ({hours:.2f} hours)' ) print(f'Max input length (text chars): {max(max_text_lens)}') print(f'Max mel frames length: {max(max_mel_lens)}') print(f'Max audio timesteps length: {max(max_timestep_lens)}')
def preprocess(args, input_folders, out_dir): input_dir = os.path.join(out_dir, 'inputs') label_dir = os.path.join(out_dir, 'labels') os.makedirs(input_dir, exist_ok=True) os.makedirs(label_dir, exist_ok=True) metadata = preprocessor.build_from_path(input_folders, input_dir, label_dir, args, tqdm=tqdm) write_metadata(metadata, out_dir, args)
def preprocess(args, input_folder, out_dir, hparams): os.makedirs(out_dir, exist_ok=True) metadata = preprocessor.build_from_path(hparams, input_folder, out_dir, args.n_jobs, tqdm=tqdm) write_metadata(metadata, out_dir)
def preprocess(args): in_dir = os.path.join(args.base_dir, args.input) out_dir = os.path.join(args.base_dir, args.output) os.makedirs(out_dir, exist_ok=True) metadata = preprocessor.build_from_path(in_dir, out_dir, args.n_jobs, tqdm=tqdm) write_metadata(metadata, out_dir)
def preprocess(args, input_folders, out_dir, hparams): mel_dir = os.path.join(out_dir, 'mels') os.makedirs(mel_dir, exist_ok=True) metadata = preprocessor.build_from_path(hparams, input_folders, mel_dir, args.n_jobs, tqdm=tqdm) write_metadata(metadata, out_dir, hparams)
def preprocess(args, input_folders, out_dir, hparams): mel_dir = os.path.join(out_dir, 'mels') wav_dir = os.path.join(out_dir, 'audio') linear_dir = os.path.join(out_dir, 'linear') os.makedirs(mel_dir, exist_ok=True) os.makedirs(wav_dir, exist_ok=True) os.makedirs(linear_dir, exist_ok=True) metadata = preprocessor.build_from_path(hparams, input_folders, mel_dir, linear_dir, wav_dir, args.n_jobs, tqdm=tqdm) write_metadata(metadata, out_dir)
def preprocess(args, input_folders, out_dir): mel_dir = os.path.join(out_dir, 'mels') wav_dir = os.path.join(out_dir, 'audio') linear_dir = os.path.join(out_dir, 'linear') os.makedirs(mel_dir, exist_ok=True) os.makedirs(wav_dir, exist_ok=True) os.makedirs(linear_dir, exist_ok=True) metadata = preprocessor.build_from_path(input_folders, mel_dir, linear_dir, wav_dir, args.n_jobs, tqdm=tqdm) write_metadata(metadata, out_dir)
def preprocess(args, input_folder, out_dir, hparams): cmp_dir = os.path.join(out_dir, 'cmp') linear_dir = os.path.join(out_dir, 'linear') for d in [cmp_dir, linear_dir]: #if(os.path.exists(d)): # shutil.rmtree(d) os.makedirs(d, exist_ok=True) metadata = preprocessor.build_from_path(hparams, input_folder, cmp_dir, linear_dir, args.n_jobs, tqdm=tqdm) write_metadata(metadata, out_dir)
def preprocess(args, input_folders, out_dir, hparams): mel_dir = os.path.join(out_dir, 'mels') wav_dir = os.path.join(out_dir, 'audio') linear_dir = os.path.join(out_dir, 'linear') os.makedirs(mel_dir, exist_ok=True) os.makedirs(wav_dir, exist_ok=True) os.makedirs(linear_dir, exist_ok=True) speaker_wavs = get_LibriTTS_wavs() metadata = preprocessor.build_from_path(hparams, input_folders, mel_dir, linear_dir, wav_dir, args.n_jobs, speaker_wavs, tqdm=tqdm) write_metadata(metadata, out_dir)
def preprocess(args, input_folders, out_dir, hparams): mel_dir = os.path.join(out_dir, 'mels') wav_dir = os.path.join(out_dir, 'audio') linear_dir = os.path.join(out_dir, 'linear') if not os.path.exists(mel_dir): os.makedirs(mel_dir) if not os.path.exists(wav_dir): os.makedirs(wav_dir) if not os.path.exists(linear_dir): os.makedirs(linear_dir) metadata = preprocessor.build_from_path(hparams, input_folders, mel_dir, linear_dir, wav_dir, args.n_jobs, tqdm=tqdm) write_metadata(metadata, out_dir)
def preprocess(args, hparams): input_dir = norm_data(args) output_dir = os.path.join(args.base_dir, 'training_data') mel_dir = os.path.join(output_dir, 'mels') wav_dir = os.path.join(output_dir, 'audio') linear_dir = os.path.join(output_dir, 'linear') os.makedirs(mel_dir, exist_ok=True) os.makedirs(wav_dir, exist_ok=True) os.makedirs(linear_dir, exist_ok=True) metadata = preprocessor.build_from_path(hparams, input_dir, mel_dir, linear_dir, wav_dir, args.n_jobs, tqdm=tqdm) write_metadata(metadata, output_dir)
def preprocess(args, wav_folder, out_dir, hparams): in_dir = os.path.join(args.folder_wav_dir, wav_folder) mel_dir = os.path.join(out_dir, 'mels') audio_dir = os.path.join(out_dir, 'audio') linear_dir = os.path.join(out_dir, 'linear') spk_emb_dir = os.path.join(out_dir, 'spkemb') os.makedirs(mel_dir, exist_ok=True) os.makedirs(audio_dir, exist_ok=True) os.makedirs(linear_dir, exist_ok=True) os.makedirs(spk_emb_dir, exist_ok=True) # metadata = preprocessor.build_from_path(hparams, mel_dir, linear_dir, wav_dir, args.n_jobs, tqdm=tqdm) metadata = preprocessor.build_from_path(hparams, args, in_dir, mel_dir, linear_dir, audio_dir, spk_emb_dir, args.n_jobs, tqdm=tqdm) write_metadata(metadata, out_dir)
def preprocess(args, input_folders, out_dir, hparams): mel_dir = os.path.join(out_dir, 'mels') wav_dir = os.path.join(out_dir, 'audio') linear_dir = os.path.join(out_dir, 'linear') os.makedirs(mel_dir, exist_ok=True) os.makedirs(wav_dir, exist_ok=True) os.makedirs(linear_dir, exist_ok=True) if args.dataset.startswith("VCTK"): metadata, speaker_dict = preprocessor_VCTK.build_from_path( hparams, input_folders, mel_dir, linear_dir, wav_dir, args.n_jobs, tqdm=tqdm) pickle.dump(speaker_dict, open(os.path.join(out_dir, "speaker_dict.pkl"), "wb")) elif args.dataset.startswith("SynPaFlex"): metadata, speaker_dict = preprocessor_SynPaFlex.build_from_path( hparams, input_folders, mel_dir, linear_dir, wav_dir, args.n_jobs, tqdm=tqdm) pickle.dump(speaker_dict, open(os.path.join(out_dir, "speaker_dict.pkl"), "wb")) else: metadata = preprocessor.build_from_path(hparams, input_folders, mel_dir, linear_dir, wav_dir, args.n_jobs, tqdm=tqdm) write_metadata(metadata, out_dir)
def preprocess(args, input_folders, out_dir, hparams): mel_dir = os.path.join(out_dir, 'mels') wav_dir = os.path.join(out_dir, 'audio') linear_dir = os.path.join(out_dir, 'linear') os.makedirs(mel_dir, exist_ok=True) os.makedirs(wav_dir, exist_ok=True) os.makedirs(linear_dir, exist_ok=True) if args.dataset == 'KRSPEECH': metadata = krspeech.build_from_path(hparams, input_folders, mel_dir, linear_dir, wav_dir, args.n_jobs, tqdm=tqdm) else: metadata = preprocessor.build_from_path(hparams, input_folders, mel_dir, linear_dir, wav_dir, args.n_jobs, tqdm=tqdm) write_metadata(metadata, out_dir)