Upload kscg_small_20v50_16k.py with huggingface_hub

kscg_small_20v50_16k.py

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+import datasets
+
+_DATA_URL = "data/kscg_small_20v50_16k.tar.gz"
+
+_PROMPTS_URLS = {
+    "train": "data/prompts-train.txt.gz",
+    "test": "data/prompts-test.txt.gz",
+}
+
+class KscgSmall25(datasets.GeneratorBasedBuilder):
+    """KSCG Small 20v50"""
+
+    def _info(self):
+        features = datasets.Features(
+            {
+                'path': datasets.Value('string'),
+                'audio': datasets.Audio(sampling_rate=16_000),
+                'gender': datasets.ClassLabel(
+                    num_classes=2,
+                    names=[
+                        'M',
+                        'F',
+                    ]
+                ),
+                'age': datasets.ClassLabel(
+                    num_classes=2,
+                    names=[
+                        '20s',
+                        '50s'
+                    ]
+                )
+            }
+        )
+
+        return datasets.DatasetInfo(
+            features=features,
+            supervised_keys=None,
+        )
+    
+    def _split_generators(self, dl_manager):
+        """Returns SplitGenerators."""
+
+        prompts_paths = dl_manager.download_and_extract(_PROMPTS_URLS)
+        archive = dl_manager.download(_DATA_URL)
+        train_dir = "kscg_small_20v50/train"
+        test_dir = "kscg_small_20v50/test"
+
+        return [
+            datasets.SplitGenerator(
+                name=datasets.Split.TRAIN,
+                gen_kwargs={
+                    "prompts_path": prompts_paths["train"],
+                    "path_to_clips": train_dir,
+                    "audio_files": dl_manager.iter_archive(archive)
+                },
+            ),
+            datasets.SplitGenerator(
+                name=datasets.Split.TEST,
+                gen_kwargs={
+                    "prompts_path": prompts_paths["test"],
+                    "path_to_clips": test_dir,
+                    "audio_files": dl_manager.iter_archive(archive)
+                },
+            ),            
+        ]
+    
+    def _generate_examples(self, prompts_path, path_to_clips, audio_files):
+        examples = {}
+        with open(prompts_path, encoding='utf-8') as f:
+            for row in f:
+                data = row.strip().split(",")
+                audio_path = data[0] + ".wav"
+                examples[audio_path] = {
+                    'path': audio_path,
+                    # 'phone_transcription': data[1],
+                    'gender': data[1],
+                    'age': data[2]
+                }
+        inside_clips_dir = False
+        id_ = 0
+        for path, f, in audio_files:
+            if path.startswith(path_to_clips):
+                inside_clips_dir = True
+                if path in examples:
+                    audio = {"path": path, "bytes": f.read()}
+                    yield id_, {**examples[path], "audio": audio}
+                    id_ += 1
+            elif inside_clips_dir:
+                break