# @ hwang258@jh.edu import os import argparse from tqdm import tqdm import pandas as pd def parse_args(): parser = argparse.ArgumentParser(description="encode the librilight dataset using encodec model") parser.add_argument("--dataset_name", type=str, default='English', help='name tag of dataset') parser.add_argument('--dataset_dir', type=str, default=None) parser.add_argument('--save_dir', type=str, default=None, help="path to the manifest, phonemes, and encodec codes dirs") parser.add_argument("--audio_min_length", type=float, default=1, help="in second, drop the audio if length is shorter than this") parser.add_argument("--encodec_sr", type=int, default=50, help="for my encodec that takes 16kHz audio with a downsample rate of 320, the codec sample rate is 50Hz, i.e. 50 codes (x n_codebooks) per second") return parser.parse_args() if __name__ == "__main__": args = parse_args() phn_save_root = os.path.join(args.save_dir, args.dataset_name, "phonemes") codes_save_root = os.path.join(args.save_dir, args.dataset_name, "encodec_16khz_4codebooks") manifest_root = os.path.join(args.save_dir, args.dataset_name, "manifest") os.makedirs(manifest_root, exist_ok=True) splits = ['train', 'validation', 'test'] for split in splits: savelines = [] jsondata = pd.read_json(path_or_buf=os.path.join(args.dataset_dir, 'trans', split+'.json'), lines=True) for key in tqdm(range(len(jsondata))): if os.path.exists(os.path.join(phn_save_root, jsondata['segment_id'][key]+".txt")) and os.path.exists(os.path.join(codes_save_root, jsondata['segment_id'][key]+".txt")): with open(os.path.join(codes_save_root, jsondata['segment_id'][key]+".txt"), 'r') as fi: x = fi.readlines() if len(x[0].split(' ')) > int(args.audio_min_length * args.encodec_sr): savelines.append([jsondata['segment_id'][key], len(x[0].split(' '))]) outputlines = '' for i in range(len(savelines)): outputlines+='0\t'+ savelines[i][0]+'\t'+str(savelines[i][1])+'\n' with open(os.path.join(manifest_root, split+'.txt'), "w") as f: f.write(outputlines)