import os import time import random import datasets import requests _GAMES = {"Genshin": "原神", "StarRail": "星穹铁道"} _LANGS = {"zh": "中文", "jp": "日语", "en": "英语", "kr": "韩语"} _URL = "https://res.ai-lab.top/api/acgnailib/models" _HOME = f"https://www.modelscope.cn/datasets/Genius-Society/{os.path.basename(__file__)[:-3]}" class hoyoTTS(datasets.GeneratorBasedBuilder): def _info(self): if self.config.name == "default": self.config.name = "众人" return datasets.DatasetInfo( features=datasets.Features( { "audio": datasets.Audio(sampling_rate=44_100), "text": datasets.Value("string"), } ), supervised_keys=("audio", "text"), license="CC-BY-NC-ND", version="0.0.1", homepage=_HOME, ) def _get_txt(self, audio_path: str): txt_path = audio_path.replace(".wav", ".lab") with open(txt_path, "r", encoding="utf-8") as file: content = file.read() return content.strip() def _parse_url(self, game: str, lang: str): try: response = requests.post( _URL, json={ "category": _GAMES[game], "repo": f"datasets/aihobbyist/{game}_Dataset", "root_path": "/datasets", "subcategory": _LANGS[lang], }, headers={ "user-agent": "Mozilla/5.0 (Windows NT 10.0; Win64; x64) AppleWebKit/537.36 (KHTML, like Gecko) Chrome/141.0.0.0 Safari/537.36 Edg/141.0.0.0" }, ) response.raise_for_status() data = response.json() for item in data: if item["dataname"] == self.config.name: return item["dl_link"] return None except Exception as e: print(f"{e}, retrying...") time.sleep(random.randint(3, 5)) return self._parse_url(game, lang) def _download_and_extract(self, dl_manager: datasets.DownloadManager, lnk: str): try: return dl_manager.download_and_extract( requests.head(lnk, allow_redirects=True).url ) except Exception as e: print(f"{e}, retrying...") return self._download_and_extract(dl_manager, lnk) def _split_generators(self, dl_manager): data_splits = [] for game in _GAMES: for lang in _LANGS: url = self._parse_url(game, lang) if not url: continue files = [] split_name = f"{game}_{lang}" data_files = self._download_and_extract(dl_manager, url) for fpath in dl_manager.iter_files([data_files]): if os.path.basename(fpath).endswith(".wav"): files.append({"audio": fpath, "text": self._get_txt(fpath)}) random.shuffle(files) data_splits.append( datasets.SplitGenerator( name=split_name, gen_kwargs={"files": files}, ) ) return data_splits def _generate_examples(self, files): for i, fpath in enumerate(files): yield i, fpath