def extract_utt_acoustic_features_parallel(metadata, dataset_output, cfg, n_workers=1):
    """Extract acoustic features from utterances using muliprocess

    Args:
        metadata (dict): dictionary that stores data in train.json and test.json files
        dataset_output (str): directory to store acoustic features
        cfg (dict): dictionary that stores configurations
        n_workers (int, optional): num of processes to extract features in parallel. Defaults to 1.

    Returns:
        list: acoustic features
    """
    for utt in tqdm(metadata):
        if cfg.task_type == "tts":
            extract_utt_acoustic_features_tts(dataset_output, cfg, utt)
        if cfg.task_type == "svc":
            extract_utt_acoustic_features_svc(dataset_output, cfg, utt)
        if cfg.task_type == "vocoder":
            extract_utt_acoustic_features_vocoder(dataset_output, cfg, utt)
        if cfg.task_type == "tta":
            extract_utt_acoustic_features_tta(dataset_output, cfg, utt)
Extract acoustic features from utterances using muliprocess

Args:
metadata (dict): dictionary that stores data in train.json and test.json files
dataset_output (str): directory to store acoustic features
cfg (dict): dictionary that stores configurations
n_workers (int, optional): num of processes to extract features in parallel. Defaults to 1.

Returns:
list: acoustic features
processors/acoustic_extractor.py