Upload librivox_indonesia.py with huggingface_hub

librivox_indonesia.py

@@ -0,0 +1,212 @@
+# 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.
+
+import os
+from pathlib import Path
+from typing import Dict, List, Tuple
+
+import datasets
+
+from nusacrowd.utils import schemas
+from nusacrowd.utils.configs import NusantaraConfig
+from nusacrowd.utils.constants import Tasks, DEFAULT_SOURCE_VIEW_NAME, DEFAULT_NUSANTARA_VIEW_NAME
+
+import pandas as pd
+
+_CITATION = """\
+@misc{
+   research, 
+   title={indonesian-nlp/librivox-indonesia · datasets at hugging face}, 
+   url={https://huggingface.co/datasets/indonesian-nlp/librivox-indonesia},
+   author={Indonesian-nlp}
+} 
+"""
+
+_DATASETNAME = "librivox_indonesia"
+_DESCRIPTION = """\
+The LibriVox Indonesia dataset consists of MP3 audio and a corresponding text file we generated from the public domain audiobooks LibriVox. 
+We collected only languages in Indonesia for this dataset. 
+The original LibriVox audiobooks or sound files' duration varies from a few minutes to a few hours. 
+Each audio file in the speech dataset now lasts from a few seconds to a maximum of 20 seconds.
+We converted the audiobooks to speech datasets using the forced alignment software we developed. 
+It supports multilingual, including low-resource languages, such as Acehnese, Balinese, or Minangkabau. 
+We can also use it for other languages without additional work to train the model.
+The dataset currently consists of 8 hours in 7 languages from Indonesia. 
+We will add more languages or audio files as we collect them. 
+"""
+
+_HOMEPAGE = "https://huggingface.co/indonesian-nlp/librivox-indonesia"
+
+_LICENSE = "CC0"
+
+_URLS = {
+    _DATASETNAME: "https://huggingface.co/datasets/indonesian-nlp/librivox-indonesia/resolve/main/data",
+}
+_LANGUAGES = {"ind", "sun", "jav", "min", "bug", "ban", "ace"}
+_LANG_CODE = {
+    "ind": ["ind", "indonesian"],
+    "sun": ["sun", "sundanese"],
+    "jav": ["jav", "javanese"],
+    "min": ["min", "minangkabau"],
+    "bug": ["bug", "bugisnese"],
+    "ban": ["bal", "balinese"],
+    "ace": ["ace", "acehnese"]
+}
+_LOCAL = False
+_SUPPORTED_TASKS = [Tasks.SPEECH_RECOGNITION]  # example: [Tasks.TRANSLATION, Tasks.NAMED_ENTITY_RECOGNITION, Tasks.RELATION_EXTRACTION]
+
+_SOURCE_VERSION = "1.0.0"
+_NUSANTARA_VERSION = "1.0.0"
+
+
+class LibrivoxIndonesia(datasets.GeneratorBasedBuilder):
+    """
+    Librivox-indonesia is a speech-to-text dataset in 7 languages available in Indonesia.
+    The default dataloader contains all languages, while the other available dataloaders contain a designated language.
+    """
+
+    SOURCE_VERSION = datasets.Version(_SOURCE_VERSION)
+    NUSANTARA_VERSION = datasets.Version(_NUSANTARA_VERSION)
+
+    BUILDER_CONFIGS = [
+        NusantaraConfig(
+            name="librivox_indonesia_source",
+            version=_SOURCE_VERSION,
+            description="Librivox-Indonesia source schema for all languages",
+            schema="source",
+            subset_id="librivox_indonesia",
+        )] + [
+        NusantaraConfig(
+            name="librivox_indonesia_{lang}_source".format(lang=lang),
+            version=_SOURCE_VERSION,
+            description="Librivox-Indonesia source schema for {lang} languages".format(lang=_LANG_CODE[lang][1]),
+            schema="source",
+            subset_id="librivox_indonesia_{lang}".format(lang=lang),
+        ) for lang in _LANGUAGES] + [
+        NusantaraConfig(
+            name="librivox_indonesia_nusantara_sptext",
+            version=_NUSANTARA_VERSION,
+            description="Librivox-Indonesia Nusantara schema for all languages",
+            schema="nusantara_sptext",
+            subset_id="librivox_indonesia",
+        )] + [
+        NusantaraConfig(
+            name="librivox_indonesia_{lang}_nusantara_sptext".format(lang=lang),
+            version=_NUSANTARA_VERSION,
+            description="Librivox-Indonesia Nusantara schema for {lang} languages".format(lang=_LANG_CODE[lang][1]),
+            schema="nusantara_sptext",
+            subset_id="librivox_indonesia_{lang}".format(lang=lang),
+        )for lang in _LANGUAGES]
+
+    DEFAULT_CONFIG_NAME = "librivox_indonesia_source"
+
+    def _info(self) -> datasets.DatasetInfo:
+        if self.config.schema == "source":
+            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=44100)
+                }
+            )
+        elif self.config.schema == "nusantara_sptext":
+            features = schemas.speech_text_features
+
+        return datasets.DatasetInfo(
+            description=_DESCRIPTION,
+            features=features,
+            homepage=_HOMEPAGE,
+            license=_LICENSE,
+            citation=_CITATION,
+        )
+
+    def _split_generators(self, dl_manager: datasets.DownloadManager) -> List[datasets.SplitGenerator]:
+        urls = _URLS[_DATASETNAME]
+
+        audio_path = {}
+        local_extracted_archive = {}
+        metadata_path = {}
+        splits = ["train", "test"]
+        for split in splits:
+            audio_path[split] = dl_manager.download(os.path.join(urls, "audio_{split}.tgz".format(split=split)))
+            local_extracted_archive[split] = dl_manager.extract(audio_path[split]) if not dl_manager.is_streaming else None
+            metadata_path[split] = dl_manager.download_and_extract(
+                os.path.join(urls, "metadata_{split}.csv.gz".format(split=split))
+            )
+
+        return [
+            datasets.SplitGenerator(
+                name=datasets.Split.TRAIN,
+                # Whatever you put in gen_kwargs will be passed to _generate_examples
+                gen_kwargs={
+                    "local_extracted_archive": local_extracted_archive["train"],
+                    "audio_path": dl_manager.iter_archive(audio_path["train"]),
+                    "metadata_path": metadata_path["train"],
+                    "split": "train",
+                },
+            ),
+            datasets.SplitGenerator(
+                name=datasets.Split.TEST,
+                gen_kwargs={
+                    "local_extracted_archive": local_extracted_archive["test"],
+                    "audio_path": dl_manager.iter_archive(audio_path["test"]),
+                    "metadata_path": metadata_path["test"],
+                    "split": "test",
+                },
+            ),
+        ]
+
+    def _generate_examples(self, local_extracted_archive: Path, audio_path, metadata_path: Path, split: str) -> Tuple[int, Dict]:
+        df = pd.read_csv(
+            metadata_path,
+            encoding="utf-8"
+        )
+        lang = self.config.subset_id.split("_")[-1]
+        if lang != "indonesia":
+            lang = _LANG_CODE[lang][0]
+        path_to_audio = "librivox-indonesia"
+        metadata = {}
+        for id, row in df.iterrows():
+            if lang == row["language"] or lang == "indonesia":
+                path = os.path.join(path_to_audio, row["path"])
+                metadata[path] = row
+                metadata[path]["id"] = id
+
+        for path, f in audio_path:
+            if path in metadata:
+                row = metadata[path]
+                path = os.path.join(local_extracted_archive, path) if local_extracted_archive else path
+                if self.config.schema == "source":
+                    yield row["id"], {
+                        "path": path,
+                        "language": row["language"],
+                        "reader": row["reader"],
+                        "sentence": row["sentence"],
+                        "audio": path,
+                    }
+                elif self.config.schema == "nusantara_sptext":
+                    yield row["id"], {
+                        "id": row["id"],
+                        "speaker_id": row["reader"],
+                        "path": path,
+                        "audio": path,
+                        "text": row["sentence"],
+                        "metadata": {
+                            "speaker_age": None,
+                            "speaker_gender": None,
+                        }
+                    }