Upload wwTTS.py

wwTTS.py

@@ -0,0 +1,74 @@
+import os
+import random
+import datasets
+
+
+_DOMAIN = "https://pan.ai-hobbyist.com/d/Wuthering Waves Datasets"
+
+_URLS = {
+    "zh": "中文 - Chinese",
+    "jp": "日语 - Japanese",
+    "en": "英语 - English",
+    "kr": "韩语 - Korean",
+}
+
+
+class wwTTS(datasets.GeneratorBasedBuilder):
+    def _info(self):
+        if self.config.name == "default":
+            self.config.name = "椿"
+
+        return datasets.DatasetInfo(
+            features=datasets.Features(
+                {
+                    "speech": datasets.Audio(sampling_rate=44_100),
+                    "text": datasets.Value("string"),
+                }
+            ),
+            supervised_keys=("speech", "text"),
+            homepage=f"https://www.modelscope.cn/datasets/Genius-Society/{os.path.basename(__file__)[:-3]}",
+            license="CC-BY-NC-ND",
+            version="0.0.1",
+        )
+
+    def _get_txt(self, file_path: str):
+        lab_path = file_path.replace(".wav", ".lab")
+        with open(lab_path, "r", encoding="utf-8") as file:
+            content = file.read()
+
+        return content.strip()
+
+    def _split_generators(self, dl_manager):
+        datasplits = []
+        for region in _URLS:
+            url = f"{_DOMAIN}/{_URLS[region]}/{self.config.name}.7z"
+            try:
+                data_files = dl_manager.download_and_extract(url)
+            except Exception as e:
+                print(f"{e}, retrying...")
+                data_files = dl_manager.download_and_extract(url)
+
+            if os.path.isdir(data_files):
+                files = []
+                for path in dl_manager.iter_files([data_files]):
+                    if os.path.basename(path).endswith(".wav"):
+                        files.append(
+                            {
+                                "speech": path,
+                                "text": self._get_txt(path),
+                            }
+                        )
+
+                random.shuffle(files)
+                datasplits.append(
+                    datasets.SplitGenerator(
+                        name=region,
+                        gen_kwargs={"files": files},
+                    )
+                )
+
+        return datasplits
+
+    def _generate_examples(self, files):
+        for i, path in enumerate(files):
+            yield i, path