def METHOD_NAME(data_json_path, tgt_dict):
    """
    Parse data json and create dataset.
    See scripts/asr_prep_json.py which pack json from raw files
    Json example:
    {
    "utts": {
        "4771-29403-0025": {
            "input": {
                "length_ms": 170,
                "path": "/tmp/file1.flac"
            },
            "output": {
                "text": "HELLO \n",
                "token": "HE LLO",
                "tokenid": "4815, 861"
            }
        },
        "1564-142299-0096": {
            ...
        }
    }
    """
    if not os.path.isfile(data_json_path):
        raise FileNotFoundError("Dataset not found: {}".format(data_json_path))
    with open(data_json_path, "rb") as f:
        data_samples = json.load(f)["utts"]
        assert len(data_samples) != 0
        sorted_samples = sorted(
            data_samples.items(),
            key=lambda sample: int(sample[1]["input"]["length_ms"]),
            reverse=True,
        )
        aud_paths = [s[1]["input"]["path"] for s in sorted_samples]
        ids = [s[0] for s in sorted_samples]
        speakers = []
        for s in sorted_samples:
            m = re.search("(.+?)-(.+?)-(.+?)", s[0])
            speakers.append(m.group(1) + "_" + m.group(2))
        frame_sizes = [s[1]["input"]["length_ms"] for s in sorted_samples]
        tgt = [
            [int(i) for i in s[1]["output"]["tokenid"].split(", ")]
            for s in sorted_samples
        ]
        # append eos
        tgt = [[*t, tgt_dict.eos()] for t in tgt]
        return AsrDataset(aud_paths, frame_sizes, tgt, tgt_dict, ids, speakers)