Update parquet files

LICENSE

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README.md

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----
-license: cc0-1.0
-task_categories:
-- automatic-speech-recognition
-language:
-- cy
-size_categories:
-- 10K<n<100K
----
-# Dataset Card for Banc Trawsgrifiadau Bangor
-
-This dataset is a bank of 20 hours 6 minutes and 49 seconds of segments of natural speech from over 50 contributors in mp3 file format, together with corresponding 'verbatim' transcripts of the speech in .tsv file format. The majority of the speech is spontaneous, natural speech. The dataset was distributed by Canolfan Bedwyr under a CC0 open license. The original dataset can be found here: [link](https://git.techiaith.bangor.ac.uk/data-porth-technolegau-iaith/banc-trawsgrifiadau-bangor).
-
-## Data Fields
-
-`audio_filename` (`string`): The name of the audio file within the 'clips' folder
-
-`audio_filesize` (`int64`): The size of the file
-
-`audio` (`dict`): A dictionary containing the path to the downloaded audio file, the decoded audio array, and the sampling rate. Note that when accessing the audio column: `dataset[0]["audio"]` the audio file is automatically decoded and resampled to `dataset.features["audio"].sampling_rate`. Decoding and resampling of a large number of audio files might take a significant amount of time. Thus it is important to first query the sample index before the `"audio"` column, *i.e.* `dataset[0]["audio"]` should **always** be preferred over `dataset["audio"][0]`.
-
-`transcript` (`string`): The transcript of the audio clip
-
-`duration` (`duration[ms]`): Duration of the clip in milliseconds
-
-
-## Licensing Information
-
-The dataset was created by Canolfan Bedwyr, partly funded by the Welsh Government, and released under
-[Creative Commons Zero v.1.0 Universal](https://git.techiaith.bangor.ac.uk/data-porth-technolegau-iaith/banc-trawsgrifiadau-bangor/-/blob/master/LICENSE)

banc-trawsgrifiadau-bangor.py

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-"""Huggingface Dataset version of Banc Trawsgrifiadau Bangor"""
-
-
-import os
-import datasets
-
-
-# TODO: Add BibTeX citation
-_CITATION = """\
-}
-"""
-_DESCRIPTION = """Huggingface Dataset version of Banc Trawsgrifiadau Bangor"""
-_HOMEPAGE = "https://git.techiaith.bangor.ac.uk/data-porth-technolegau-iaith/banc-trawsgrifiadau-bangor"
-_LICENSE = "Creative Commons Zero v1.0 Universal"
-_URL = "https://huggingface.co/datasets/prvInSpace/banc-trawsgrifiadau-bangor/resolve/main"
-
-# TODO: Name of the dataset usually matches the script name with CamelCase instead of snake_case
-
-
-class BancTrawsgrifiadauBangor(datasets.GeneratorBasedBuilder):
-    """Huggingface Dataset version of Banc Trawsgrifiadau Bangor"""
-
-    VERSION = datasets.Version("1.0.0")
-
-    def _info(self):
-        features = datasets.Features(
-            {
-                "audio_filename": datasets.Value("string"),
-                "audio_filesize": datasets.Value("int64"),
-                "transcript": datasets.Value("string"),
-                "duration": datasets.Value("int64"),
-                "audio": datasets.features.Audio(sampling_rate=16_000)
-                # These are the features of your dataset like images, labels ...
-            }
-        )
-        return datasets.DatasetInfo(
-            # This is the description that will appear on the datasets page.
-            description=_DESCRIPTION,
-            # This defines the different columns of the dataset and their types
-            # Here we define them above because they are different between the two configurations
-            features=features,
-            # If there's a common (input, target) tuple from the features, uncomment supervised_keys line below and
-            # specify them. They'll be used if as_supervised=True in builder.as_dataset.
-            # supervised_keys=("sentence", "label"),
-            # Homepage of the dataset for documentation
-            homepage=_HOMEPAGE,
-            # License for the dataset if available
-            license=_LICENSE,
-            # Citation for the dataset
-            citation=_CITATION,
-        )
-
-    def _split_generators(self, dl_manager):
-
-        # Download the clips
-        data_dir = dl_manager.download_and_extract(
-            f"{_URL}/clips.zip")
-
-        # Generate the splits
-        return [
-            datasets.SplitGenerator(
-                name="clips",
-                # These kwargs will be passed to _generate_examples
-                gen_kwargs={
-                    "filepath": dl_manager.download(f"{_URL}/clips.tsv"),
-                    "path_to_clips": os.path.join(data_dir, "clips")
-                },
-            ),
-            datasets.SplitGenerator(
-                name=datasets.Split.TRAIN,
-                # These kwargs will be passed to _generate_examples
-                gen_kwargs={
-                    "filepath": dl_manager.download(f"{_URL}/train.tsv"),
-                    "path_to_clips": os.path.join(data_dir, "clips")
-                },
-            ),
-            datasets.SplitGenerator(
-                name=datasets.Split.TEST,
-                # These kwargs will be passed to _generate_examples
-                gen_kwargs={
-                    "filepath": dl_manager.download(f"{_URL}/test.tsv"),
-                    "path_to_clips": os.path.join(data_dir, "clips")
-                },
-            ),
-        ]
-
-    # method parameters are unpacked from `gen_kwargs` as given in `_split_generators`
-    def _generate_examples(self, filepath, path_to_clips):
-        print(path_to_clips)
-        import csv
-        # TODO: This method handles input defined in _split_generators to yield (key, example) tuples from the dataset.
-        # The `key` is for legacy reasons (tfds) and is not important in itself, but must be unique for each example.
-        with open(filepath, encoding="utf-8") as f:
-            reader = csv.DictReader(f, delimiter="\t")
-            for row in reader:
-                path = f'{path_to_clips}/{row["audio_filename"]}'
-
-                # Add the audio data
-                with open(path, "rb") as file:
-                    row['audio'] = {
-                        'path': path, 'bytes': file.read()
-                    }
-                yield path, row

clips.zip → default/banc-trawsgrifiadau-bangor-clips.parquet

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default/banc-trawsgrifiadau-bangor-test.parquet

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default/banc-trawsgrifiadau-bangor-train.parquet

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