upload

audio.zip

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+version https://git-lfs.github.com/spec/v1
+oid sha256:aee2ef74a325c60955ceea02ebf95b48c7acb6d9134e7a3407d01fef3df2d235
+size 1900343

datasets.py

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+# coding=utf-8
+
+import csv
+import os
+import datasets
+
+logger = datasets.logging.get_logger(__name__)
+
+
+""" Self-use Dataset"""
+
+_CITATION = """\
+@article{nothing,
+  title={Self-use DataSets},
+  author={Stan}
+  journal={},
+  year={2023}
+}
+"""
+
+_DESCRIPTION = """\
+Self-use DataSets
+"""
+
+
+class Minds14Config(datasets.BuilderConfig):
+    """BuilderConfig for xtreme-s"""
+
+    def __init__(
+        self, name, description, homepage, data_url
+    ):
+        super(Minds14Config, self).__init__(
+            name=self.name,
+            version=datasets.Version("1.0.0", ""),
+            description=self.description,
+        )
+        self.name = name
+        self.description = description
+        self.homepage = homepage
+        self.data_url = data_url
+
+
+class Minds14(datasets.GeneratorBasedBuilder):
+
+    DEFAULT_WRITER_BATCH_SIZE = 1000
+
+    def _info(self):
+        task_templates = None
+        features = datasets.Features(
+            {
+                "path": datasets.Value("string"),
+                "audio": datasets.Audio(sampling_rate=8_000),
+                "transcription": datasets.Value("string"),                
+            }
+        )
+
+        return datasets.DatasetInfo(
+            description=_DESCRIPTION,
+            features=features,
+            supervised_keys=("audio", "transcription"),
+            homepage='',
+            citation=_CITATION,
+            task_templates=task_templates,
+        )
+
+    def _split_generators(self, dl_manager):
+        archive_path = dl_manager.download_and_extract(self.config.data_url)
+        audio_path = dl_manager.extract(
+            os.path.join(archive_path, "DataSets-0", "audio.zip")
+        )
+        text_path = dl_manager.extract(
+            os.path.join(archive_path, "DataSets-0", "text.zip")
+        )
+
+        text_path ={'demo': os.path.join(text_path, f"demo.csv")}
+
+        return [
+            datasets.SplitGenerator(
+                name=datasets.Split.TRAIN,
+                gen_kwargs={
+                    "audio_path": audio_path,
+                    "text_paths": text_path,
+                },
+            )
+        ]
+
+    def _generate_examples(self, audio_path, text_paths):
+            key = 0
+            for lang in text_paths.keys():
+                text_path = text_paths[lang]
+                with open(text_path, encoding="utf-8") as csv_file:
+                    csv_reader = csv.reader(csv_file, delimiter=",", skipinitialspace=True)
+                    next(csv_reader)
+                    for row in csv_reader:
+                        filepath, refrence = row
+                        filepath = os.path.join(audio_path, *filepath.split("/"))
+                        yield key, {
+                            "path": filepath,
+                            "audio": filepath,
+                            "transcription": refrence,
+                        }
+                        key += 1

text.zip

@@ -0,0 +1,3 @@
+version https://git-lfs.github.com/spec/v1
+oid sha256:91490053b1102c7f7376a5ae35565b07dec9df90406dc0770ecf30cdeb71dfbe
+size 1556