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data/files.zip

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+version https://git-lfs.github.com/spec/v1
+oid sha256:6281031e0f9f76fb5847ebef612ab4c3f9687e65a97b987f0ffe250218011223
+size 9725534568

data/metadata.zip

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+version https://git-lfs.github.com/spec/v1
+oid sha256:b7d9d270b058df94ec7fd2b9f27234245452eced9132db9e4ee14c3d3dc6a00d
+size 893113

saudi-trans.py

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+import os
+import datasets
+import pandas as pd 
+
+_DESCRIPTION = """\
+This Saudi dataset is intended for speech translation from Saudi Arabic into English.
+"""
+
+_CITATION = "Some citation"
+
+_data_dir = "data"
+
+class SaudiTranslation(datasets.GeneratorBasedBuilder):
+   
+    def _info(self):
+        return datasets.DatasetInfo(
+            description=_DESCRIPTION,
+            features=datasets.Features(
+                {
+                    "path": datasets.Value("string"),
+                    "audio": datasets.Audio(sampling_rate=16_000),
+                    "sentence": datasets.Value("string"),
+                }
+            ),
+            supervised_keys=None,
+            citation=_CITATION,
+        )
+
+    def _split_generators(self, dl_manager):
+        download_dir = dl_manager.download_and_extract(
+            {
+                "files": os.path.join(_data_dir, "files.zip"),
+                "metadata": os.path.join(_data_dir, "metadata.zip")
+            }
+        )
+
+        return [
+            datasets.SplitGenerator(
+                name=datasets.Split.TRAIN,
+                gen_kwargs={
+                    "split": datasets.Split.TRAIN,
+                    "data_dir": os.path.join(download_dir["files"], "files"),
+                    "metapath": os.path.join(download_dir["metadata"], "metadata", "train.csv"),
+                    
+                },
+            ),
+            datasets.SplitGenerator(
+                name=datasets.Split.TEST,
+                gen_kwargs={
+                    "split": datasets.Split.TEST,
+                    "data_dir": os.path.join(download_dir["files"], "files"),
+                    "metapath": os.path.join(download_dir["metadata"], "metadata", "test.csv"),
+                    
+                },
+            ),
+        ]
+
+    def _generate_examples(self, data_dir, metapath, split):
+        metadata = pd.read_csv(metapath)
+        for key, row in metadata.iterrows():
+            audio_path = os.path.join(data_dir, row["audio"])
+            yield key, {
+                "audio": audio_path,
+                "sentence": row["text"],
+                "path": audio_path,
+            }