Datasets:
Tasks:
Automatic Speech Recognition
Formats:
parquet
Size:
10K - 100K
Tags:
speech-recognition
License:
Update pangloss.py
Browse files- pangloss.py +18 -16
pangloss.py
CHANGED
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@@ -17,6 +17,7 @@ import csv
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import json
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import os
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import datasets
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_CITATION = {
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"yong1288": """
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@@ -52,16 +53,22 @@ url = {https://doi.org/10.5281/zenodo.5521112}
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}
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_DESCRIPTION = """\
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These datasets are extracts from the Pangloss collection and have
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"""
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_HOMEPAGE = "https://pangloss.cnrs.fr/"
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_LICENSE = "https://creativecommons.org/licenses/by-nc-sa/4.0/fr/legalcode"
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_LANGUAGES = {
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"yong1288": {
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"url": "https://mycore.core-cloud.net/index.php/s/
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"homepage": "https://zenodo.org/record/5336698",
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"description": "Yongning Na dataset",
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"translations": ["fr", "en", "zh"]
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@@ -86,14 +93,6 @@ class PanglossDataset(datasets.GeneratorBasedBuilder):
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"traduction:zh": "translation:zh"
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}
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VERSION = datasets.Version("1.2.0")
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# TODO: Name of the dataset usually matches the script name with CamelCase instead of snake_case
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class NewDataset(datasets.GeneratorBasedBuilder):
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"""TODO: Short description of my dataset."""
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# This is an example of a dataset with multiple configurations.
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# If you don't want/need to define several sub-sets in your dataset,
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# just remove the BUILDER_CONFIG_CLASS and the BUILDER_CONFIGS attributes.
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@@ -106,24 +105,25 @@ class NewDataset(datasets.GeneratorBasedBuilder):
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# data = datasets.load_dataset('my_dataset', 'first_domain')
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# data = datasets.load_dataset('my_dataset', 'second_domain')
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BUILDER_CONFIGS = [
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datasets.BuilderConfig(name=language_name, version=
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for language_name, language_data in _LANGUAGES.items()
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]
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#DEFAULT_CONFIG_NAME = "" # It's not mandatory to have a default configuration. Just use one if it make sense.
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def _info(self):
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# TODO: This method specifies the datasets.DatasetInfo object which contains informations and typings for the dataset
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features = datasets.Features(
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{
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"path": datasets.Value("string"),
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"audio": datasets.Audio(sampling_rate=16_000),
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"sentence": datasets.Value("string"),
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"doctype": datasets.Value("string"),
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"speaker": datasets.Value("string"),
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**{f"translation:{language_code}": datasets.Value("string") for language_code in _LANGUAGES[self.config.name]["translations"]}
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}
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)
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return datasets.DatasetInfo(
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# This is the description that will appear on the datasets page.
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description=_DESCRIPTION,
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license=_LICENSE,
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# Citation for the dataset
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citation=_CITATION,
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)
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def _split_generators(self, dl_manager):
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yield key, data
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-
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#
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-
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# datasets-cli test datasets/pangloss --save_infos --all_configs
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# datasets-cli dummy_data datasets/pangloss --auto_generate
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import json
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import os
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import datasets
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from datasets.tasks import AutomaticSpeechRecognition
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_CITATION = {
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"yong1288": """
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}
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_DESCRIPTION = """\
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These datasets are extracts from the Pangloss collection and have
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been preprocessed for ASR experiments in Na and Japhug.
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"""
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_HOMEPAGE = "https://pangloss.cnrs.fr/"
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_LICENSE = "https://creativecommons.org/licenses/by-nc-sa/4.0/fr/legalcode"
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# The HuggingFace Datasets library doesn't host the datasets but only points to the original files.
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# This can be an arbitrary nested dict/list of URLs (see below in `_split_generators` method)
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_VERSION = datasets.Version("1.0.0")
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_LANGUAGES = {
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"yong1288": {
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"url": "https://mycore.core-cloud.net/index.php/s/vaGMeRf4Iij8MWR/download",
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"homepage": "https://zenodo.org/record/5336698",
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"description": "Yongning Na dataset",
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"translations": ["fr", "en", "zh"]
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"traduction:zh": "translation:zh"
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}
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# This is an example of a dataset with multiple configurations.
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# If you don't want/need to define several sub-sets in your dataset,
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# just remove the BUILDER_CONFIG_CLASS and the BUILDER_CONFIGS attributes.
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# data = datasets.load_dataset('my_dataset', 'first_domain')
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# data = datasets.load_dataset('my_dataset', 'second_domain')
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BUILDER_CONFIGS = [
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datasets.BuilderConfig(name=language_name, version=_VERSION, description=language_data["description"])
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for language_name, language_data in _LANGUAGES.items()
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]
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#DEFAULT_CONFIG_NAME = "na" # It's not mandatory to have a default configuration. Just use one if it make sense.
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def _info(self):
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# TODO: This method specifies the datasets.DatasetInfo object which contains informations and typings for the dataset
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features = datasets.Features(
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{
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"path": datasets.Value("string"),
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"audio": datasets.features.Audio(sampling_rate=16_000),
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"sentence": datasets.Value("string"),
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"doctype": datasets.Value("string"),
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"speaker": datasets.Value("string"),
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**{f"translation:{language_code}": datasets.Value("string") for language_code in _LANGUAGES[self.config.name]["translations"]}
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}
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)
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return datasets.DatasetInfo(
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# This is the description that will appear on the datasets page.
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description=_DESCRIPTION,
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license=_LICENSE,
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# Citation for the dataset
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citation=_CITATION,
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task_templates=[AutomaticSpeechRecognition(audio_column="audio", transcription_column="forme")],
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)
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def _split_generators(self, dl_manager):
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yield key, data
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if __name__ == "__main__":
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# for language in _LANGUAGES.keys():
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datasets.load_dataset("datasets/pangloss/pangloss.py", "japh1234")
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# datasets-cli test datasets/pangloss --save_infos --all_configs
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# datasets-cli dummy_data datasets/pangloss --auto_generate
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