Initial release

.gitattributes

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README.md

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+---
+license: cc0-1.0
+task_categories:
+- automatic-speech-recognition
+language:
+- es
+- eu
+pretty_name: Basque Parliament Corpus 1.0
+---

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basque_parliament_1.py

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+# Copyright 2023 GTTS (http://gtts.ehu.eus)
+#
+# 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.
+
+# Lint as: python3
+"""Basque Parliament dataset"""
+
+
+import datasets
+from datasets.utils.py_utils import size_str
+import os
+import csv
+from tqdm import tqdm
+
+from .languages import LANGUAGES
+from .release_stats import STATS
+
+
+_CITATION = """\
+"""
+
+_HOMEPAGE = "https://huggingface.co/datasets/gttsehu/basque_parliament_1"
+
+_LICENSE = "https://creativecommons.org/publicdomain/zero/1.0/"
+
+_DESCRIPTION = (
+    f"Basque Parliament dataset blah blah blah..."
+    f"blah blah blah..."
+    f"blah blah blah..."
+)
+
+_BASE_URL = "https://huggingface.co/datasets/gttsehu/basque_parliament_1/resolve/main/"
+
+_AUDIO_URL = _BASE_URL + "audio/{split}_{shard_idx}.tar"
+_METADATA_URL =  _BASE_URL + "metadata/{split}.tsv"
+
+class BasqueParliamentConfig(datasets.BuilderConfig):
+    """BuilderConfig for BasqueParliament."""
+
+    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 = _DESCRIPTION
+
+        super(BasqueParliamentConfig, self).__init__(
+            name = name,
+            version = datasets.Version(version),
+            description = _DESCRIPTION,
+            **kwargs,
+        )
+
+
+class BasqueParliament(datasets.GeneratorBasedBuilder):
+    """Basque Parliament is a free Basque-Spanish speech corpus."""
+
+    DEFAULT_CONFIG_NAME = "all"
+    
+    BUILDER_CONFIGS = [
+        BasqueParliamentConfig(
+            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):
+        description = (
+            f"Basque Parliament dataset blah blah blah..."
+            f"blah blah blah..."
+            f"blah blah blah..."
+        )
+        features = datasets.Features(
+            {
+                "path": datasets.Value("string"),
+                "audio": datasets.features.Audio(sampling_rate=16_000),
+                "sentence": datasets.Value("string"),
+                "speaker_id": datasets.Value("string"),
+                "language": datasets.Value("string"),
+                "PRR": datasets.Value("float32"),
+                "length": datasets.Value("float32"),
+            }
+        )
+
+        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):
+        lang = self.config.name
+        
+        audio_urls = {}
+        splits = ("train", "train_clean", "dev", "test")
+        for split in splits:
+            if split == "train_clean": continue
+            audio_urls[split] = [
+                _AUDIO_URL.format(split=split, shard_idx=i) for i in range(STATS["n_shards"][split])
+            ]
+        audio_urls["train_clean"]=audio_urls["train"]
+        archive_paths = dl_manager.download(audio_urls)
+        local_extracted_archive_paths = dl_manager.extract(archive_paths) if not dl_manager.is_streaming else {}
+
+        metadata_urls = {split: _METADATA_URL.format(lang=lang, split=split) for split in splits}
+        metadata_paths = dl_manager.download_and_extract(metadata_urls)
+
+        split_generators = []
+        split_names = {
+            "train": datasets.Split.TRAIN,
+            "dev": datasets.Split.VALIDATION,
+            "test": datasets.Split.TEST,
+        }
+        for split in splits:
+            split_generators.append(
+                datasets.SplitGenerator(
+                    name=split_names.get(split, split),
+                    gen_kwargs={
+                        "local_extracted_archive_paths": local_extracted_archive_paths.get(split),
+                        "archives": [dl_manager.iter_archive(path) for path in archive_paths.get(split)],
+                        "metadata_path": metadata_paths[split],
+                    },
+                ),
+            )
+
+        return split_generators
+
+    def _generate_examples(self, local_extracted_archive_paths, archives, metadata_path):
+        lang = self.config.name
+        data_fields = list(self._info().features.keys())
+        metadata = {}
+        with open(metadata_path, encoding="utf-8") as f:
+            reader = csv.DictReader(f, delimiter="\t", quoting=csv.QUOTE_NONE)
+            metadata = { row["path"]:row for row in tqdm(reader, desc="Reading metadata...") }
+
+        excluded = 0
+        for i, audio_archive in enumerate(archives):
+            for path, file in audio_archive:
+                if path not in metadata :
+                    excluded += 1
+                    continue
+                result = dict(metadata[path])
+                if lang == "all" or lang == result["language"] :
+                    # set the audio feature and the path to the extracted file
+                    path = os.path.join(local_extracted_archive_paths[i], path) if local_extracted_archive_paths else path
+                    result["audio"] = {"path": path, "bytes": file.read()}
+                    result["path"] = path
+                    yield path, result
+        print(excluded,'audio files not found in metadata')
+

languages.py

@@ -0,0 +1,6 @@
+LANGUAGES = {
+    'eu': 'Basque (Euskara)' ,
+    'es': 'Spanish (Español)' ,
+    'bi': 'Mixed Basque + Spanish (Euskara + Español)' ,
+    'all': 'All' ,
+}

metadata/dev.tsv

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release_stats.py

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+STATS = {
+    "name": "BasqueParliament",
+    "version": "1.0.0",
+    "date": "2023-12-29",
+    "years": (2013,2014,2015,2016,2017,2018,2019,2020,2021,2022),
+    "locales": {
+        "es":   {'reportedSentences': 149, 'duration': 1, 'clips': 1, 'users': 416, 'size': 1, 'avgDurationSecs': 1, 'totalHrs': 1},
+        "eu":   {'reportedSentences': 175, 'duration': 1, 'clips': 1, 'users': 416, 'size': 1, 'avgDurationSecs': 1, 'totalHrs': 1},
+        "bi": {'reportedSentences': 142, 'duration': 1, 'clips': 1, 'users': 416, 'size': 1, 'avgDurationSecs': 1, 'totalHrs': 1},
+        "all":  {'reportedSentences': 142, 'duration': 1, 'clips': 1, 'users': 416, 'size': 1, 'avgDurationSecs': 1, 'totalHrs': 1},
+    },
+    "n_shards" : {
+        "train" : 11 ,
+        "dev" :   1,
+        "test" :  1
+        },
+    'totalDuration': 1, 
+    'totalHrs': 1
+}