init

data/coursera/dev.tar.gz

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+size 1126457579

data/coursera/train.tar.gz

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+version https://git-lfs.github.com/spec/v1
+oid sha256:1750d593e6ddcca90e1184c95b09c42e10aea88327b09524165b730110872f6e
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hebrew_speech_coursera.py

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+import glob
+import os
+from functools import partial
+
+import datasets
+
+DS_NAMES = [
+  "coursera"
+]
+VERSION = datasets.Version("0.0.1")
+
+
+class PublicSpeech(datasets.GeneratorBasedBuilder):
+    """Speech dataset."""
+
+    BUILDER_CONFIGS = [
+        datasets.BuilderConfig(name=data_name, version=VERSION, description=f"Speech {data_name} dataset")
+        for data_name in DS_NAMES
+    ]
+
+    def _info(self):
+        return datasets.DatasetInfo(
+            description="Hebrew speech datasets",
+            features=datasets.Features(
+                {
+                    "audio": datasets.Audio(sampling_rate=16000),
+                    "sentence": datasets.Value("string"),
+                }
+            ),
+            supervised_keys=("audio", "sentence"),
+            homepage="https://huggingface.co/datasets/imvladikon/hebrew_speech",
+            citation="TODO",
+        )
+
+    def _split_generators(self, dl_manager):
+        downloader = partial(
+            lambda split: dl_manager.download_and_extract(f"data/{self.config.name}/{split}.tar.gz"),
+        )
+
+        return [
+            datasets.SplitGenerator(
+                name=datasets.Split.TRAIN,
+                gen_kwargs={"root_path": downloader("train"), "split": "train"},
+            ),
+            datasets.SplitGenerator(
+                name=datasets.Split.VALIDATION,
+                gen_kwargs={"root_path": downloader("dev"), "split": "dev"},
+            ),
+        ]
+
+    def _generate_examples(self, root_path, split):
+        split_path = os.path.join(root_path, split)
+        for wav in glob.glob(split_path + "/*.wav"):
+            uid = os.path.splitext(os.path.basename(wav))[0]
+            with open(os.path.join(split_path, f"{uid}.txt"), encoding="utf-8") as fin:
+                text = fin.read()
+            example = {
+                "audio": wav,
+                "sentence": text,
+            }
+            yield uid, example