add the dataset

languages.py

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+LANGUAGES = {
+    'ace': 'Acehnese',
+    'bal': 'Balinese',
+    'bug': 'Bugisnese',
+    'id': 'Indonesian',
+    'min': 'Minangkabau',
+    'jav': 'Javanese',
+    'sun': 'Sundanese',
+    'all': 'All'
+}

librivox-indonesia.py

@@ -0,0 +1,157 @@
+# coding=utf-8
+# Copyright 2022 The HuggingFace Datasets Authors and the current dataset script contributor.
+#
+# Licensed under the Apache License, Version 2.0 (the "License");
+# you may not use this file except in compliance with the License.
+# You may obtain a copy of the License at
+#
+#     http://www.apache.org/licenses/LICENSE-2.0
+#
+# Unless required by applicable law or agreed to in writing, software
+# distributed under the License is distributed on an "AS IS" BASIS,
+# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+# See the License for the specific language governing permissions and
+# limitations under the License.
+""" LibriVox-Indonesia Dataset"""
+
+
+import csv
+import os
+
+import datasets
+from datasets.utils.py_utils import size_str
+
+from languages import LANGUAGES
+from release_stats import STATS
+
+_CITATION = """\
+"""
+
+_HOMEPAGE = "https://huggingface.co/indonesian-nlp/librivox-indonesia"
+
+_LICENSE = "https://creativecommons.org/publicdomain/zero/1.0/"
+
+_AUDIO_URL = "https://huggingface.co/datasets/cahya/librivox-indonesia/resolve/main/audio.tgz"
+
+
+class LibriVoxIndonesiaConfig(datasets.BuilderConfig):
+    """BuilderConfig for LibriVoxIndonesia."""
+
+    def __init__(self, name, version, **kwargs):
+        self.language = kwargs.pop("language", None)
+        self.release_date = kwargs.pop("release_date", None)
+        self.num_clips = kwargs.pop("num_clips", None)
+        self.num_speakers = kwargs.pop("num_speakers", None)
+        self.validated_hr = kwargs.pop("validated_hr", None)
+        self.total_hr = kwargs.pop("total_hr", None)
+        self.size_bytes = kwargs.pop("size_bytes", None)
+        self.size_human = size_str(self.size_bytes)
+        description = (
+            f"LibriVox-Indonesia speech to text dataset in {self.language} released on {self.release_date}. "
+            f"The dataset comprises {self.validated_hr} hours of transcribed speech data"
+        )
+        super(LibriVoxIndonesiaConfig, self).__init__(
+            name=name,
+            version=datasets.Version(version),
+            description=description,
+            **kwargs,
+        )
+
+
+class LibriVoxIndonesia(datasets.GeneratorBasedBuilder):
+    DEFAULT_CONFIG_NAME = "all"
+
+    BUILDER_CONFIGS = [
+        LibriVoxIndonesiaConfig(
+            name=lang,
+            version=STATS["version"],
+            language=LANGUAGES[lang],
+            release_date=STATS["date"],
+            num_clips=lang_stats["clips"],
+            num_speakers=lang_stats["users"],
+            total_hr=float(lang_stats["totalHrs"]) if lang_stats["totalHrs"] else None,
+            size_bytes=int(lang_stats["size"]) if lang_stats["size"] else None,
+        )
+        for lang, lang_stats in STATS["locales"].items()
+    ]
+
+    def _info(self):
+        total_languages = len(STATS["locales"])
+        total_hours = self.config.total_hr
+        description = (
+            "LibriVox-Indonesia is a speech dataset generated from LibriVox with only languages from Indonesia."
+            f"The dataset currently consists of {total_hours} hours of speech "
+            f" in {total_languages} languages, but more voices and languages are always added."
+        )
+        features = datasets.Features(
+            {
+                "path": datasets.Value("string"),
+                "language": datasets.Value("string"),
+                "reader": datasets.Value("string"),
+                "sentence": datasets.Value("string"),
+                "audio": datasets.features.Audio(sampling_rate=48_000)
+            }
+        )
+
+        return datasets.DatasetInfo(
+            description=description,
+            features=features,
+            supervised_keys=None,
+            homepage=_HOMEPAGE,
+            license=_LICENSE,
+            citation=_CITATION,
+            version=self.config.version,
+        )
+
+    def _split_generators(self, dl_manager):
+        """Returns SplitGenerators."""
+        dl_manager.download_config.ignore_url_params = True
+
+        archive_path = dl_manager.download(_AUDIO_URL)
+        local_extracted_archive = dl_manager.extract(archive_path) if not dl_manager.is_streaming else None
+        path_to_clips = "audio"
+
+        return [
+            datasets.SplitGenerator(
+                name=datasets.Split.TRAIN,
+                gen_kwargs={
+                    "local_extracted_archive": local_extracted_archive,
+                    "archive_iterator": dl_manager.iter_archive(archive_path),
+                    "metadata_filepath": "audio_transcription.csv",
+                    "path_to_clips": path_to_clips,
+                },
+            ),
+        ]
+
+    def _generate_examples(
+        self,
+        local_extracted_archive,
+        archive_iterator,
+        metadata_filepath,
+        path_to_clips,
+    ):
+        """Yields examples."""
+        data_fields = list(self._info().features.keys())
+        metadata = {}
+        filepath = local_extracted_archive + "/audio/audio_transcription.csv"
+        with open(filepath, "r") as f:
+            lines = (line for line in f)
+            utterances = csv.DictReader(lines)
+            for row in utterances:
+                if self.config.name == "all" or self.config.name == row["language"]:
+                    row["path"] = os.path.join(path_to_clips, row["path"])
+                    # if data is incomplete, fill with empty values
+                    for field in data_fields:
+                        if field not in row:
+                            row[field] = ""
+                    metadata[row["path"]] = row
+        for path, f in archive_iterator:
+            if path in metadata:
+                result = dict(metadata[path])
+                # set the audio feature and the path to the extracted file
+                path = os.path.join(local_extracted_archive, path) if local_extracted_archive else path
+                result["audio"] = {"path": path, "bytes": f.read()}
+                # set path to None if the audio file doesn't exist locally (i.e. in streaming mode)
+                result["path"] = path if local_extracted_archive else None
+
+                yield path, result

librivox-indonesia.tgz

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+version https://git-lfs.github.com/spec/v1
+oid sha256:fb20e579f5813b019c871064e10b0cc0781848283f90f243a29c2f6f7ffba1a3
+size 321049598

release_stats.py

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+STATS = {
+    "name": "Librivox-Indonesia",
+    "bundleURLTemplate": "https://huggingface.co/datasets/cahya/test01/resolve/main/audio.tgz",
+    "version": "1.0.0",
+    "date": "",
+    "locales": {
+        "ace": {'reportedSentences': 1, 'duration': 1, 'clips': 1, 'users': 416, 'size': 1, 'avgDurationSecs': 1, 'totalHrs': 1},
+        "bal": {'reportedSentences': 1, 'duration': 1, 'clips': 1, 'users': 416, 'size': 1, 'avgDurationSecs': 1, 'totalHrs': 1},
+        "bug": {'reportedSentences': 1, 'duration': 1, 'clips': 1, 'users': 416, 'size': 1, 'avgDurationSecs': 1, 'totalHrs': 1},
+        "id": {'reportedSentences': 1, 'duration': 1, 'clips': 1, 'users': 416, 'size': 1, 'avgDurationSecs': 1, 'totalHrs': 1},
+        "min": {'reportedSentences': 1, 'duration': 1, 'clips': 1, 'users': 416, 'size': 1, 'avgDurationSecs': 1, 'totalHrs': 1},
+        "jav": {'reportedSentences': 1, 'duration': 1, 'clips': 1, 'users': 416, 'size': 1, 'avgDurationSecs': 1, 'totalHrs': 1},
+        "sun": {'reportedSentences': 1, 'duration': 1, 'clips': 1, 'users': 416, 'size': 1, 'avgDurationSecs': 1, 'totalHrs': 1},
+        "all": {'reportedSentences': 1, 'duration': 1, 'clips': 1, 'users': 416, 'size': 1, 'avgDurationSecs': 1, 'totalHrs': 1},
+    },
+    'totalDuration': 1, 'totalHrs': 1
+}
+