Add code files

kathbath.py

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+""" Kathbath 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 = """\
+@misc{https://doi.org/10.48550/arxiv.2208.11761,
+  doi = {10.48550/ARXIV.2208.11761},
+  url = {https://arxiv.org/abs/2208.11761},
+  author = {Javed, Tahir and Bhogale, Kaushal Santosh and Raman, Abhigyan and Kunchukuttan, Anoop and Kumar, Pratyush and Khapra, Mitesh M.},
+  title = {IndicSUPERB: A Speech Processing Universal Performance Benchmark for Indian languages},
+  publisher = {arXiv},
+  year = {2022},
+  copyright = {arXiv.org perpetual, non-exclusive license}
+}
+"""
+
+_HOMEPAGE = "https://ai4bharat.iitm.ac.in/indic-superb/"
+
+_LICENSE = "https://creativecommons.org/publicdomain/zero/1.0/"
+
+_DATA_URL = "https://huggingface.co/datasets/ai4bharat/kathbath/resolve/main/data"
+
+
+class KathbathConfig(datasets.BuilderConfig):
+    """BuilderConfig for Kathbath."""
+
+    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.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"Kathbath speech to text dataset in {self.language} released on {self.release_date}. "
+            f"The dataset comprises {self.total_hr} hours of transcribed speech data"
+        )
+        super(KathbathConfig, self).__init__(
+            name=name,
+            version=datasets.Version(version),
+            description=description,
+            **kwargs,
+        )
+
+
+class Kathbath(datasets.GeneratorBasedBuilder):
+    DEFAULT_CONFIG_NAME = "_all_"
+
+    BUILDER_CONFIGS = [
+        KathbathConfig(
+            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"),
+                "speaker": datasets.Value("string"),
+                "sentence": datasets.Value("string"),
+                "audio": datasets.features.Audio(sampling_rate=16000)
+            }
+        )
+
+        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
+        audio_path = {}
+        local_extracted_archive = {}
+        metadata_path = {}
+        split_type = {"train": datasets.Split.TRAIN, "valid": datasets.Split.VALIDATION, "test_unknown": datasets.Split.TEST, "test_known": datasets.Split.TEST}
+        for split in split_type:
+            audio_path[split] = dl_manager.download(f"{_DATA_URL}/audio_{split}.tar")
+            local_extracted_archive[split] = dl_manager.extract(audio_path[split]) if not dl_manager.is_streaming else None
+            metadata_path[split] = dl_manager.download(f"{_DATA_URL}/metadata_{split}.tsv")
+        path_to_clips = "kb_data_clean_m4a"
+
+        return [
+            datasets.SplitGenerator(
+                name=split_type[split],
+                gen_kwargs={
+                    "local_extracted_archive": local_extracted_archive[split],
+                    "audio_files": dl_manager.iter_archive(audio_path[split]),
+                    "metadata_path": metadata_path[split],
+                    "path_to_clips": path_to_clips,
+                },
+            ) for split in split_type
+        ]
+
+    def _generate_examples(
+        self,
+        local_extracted_archive,
+        audio_files,
+        metadata_path,
+        path_to_clips,
+    ):
+        """Yields examples."""
+        data_fields = list(self._info().features.keys())
+        metadata = {}
+        with open(metadata_path, "r", encoding="utf-8") as f:
+            reader = csv.DictReader(f, delimiter="\t")
+            for row in reader:
+                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
+        id_ = 0
+        for path, f in audio_files:
+            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()}
+                result["path"] = path
+                yield id_, result
+                id_ += 1

languages.py

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+LANGUAGES = {
+    "bn": "Bengali",
+    "gu": "Gujarati",
+    "hi": "Hindi",
+    "kn": "Kannada",
+    "ml": "Malayalam",
+    "mr": "Marathi",
+    "or": "Odia",
+    "pa": "Punjabi",
+    "sa": "Sanskrit",
+    "ta": "Tamil",
+    "te": "Telugu",
+    "ur": "Urdu"
+}

release_stats.py

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+STATS = {
+    "name": "Kathbath",
+    "version": "1.0.0",
+    "date": "2022-08-24",
+    "locales": {
+        "bn": {'totalHrs': 115.8},
+        "gu": {'totalHrs': 129.3},
+        "hi": {'totalHrs': 150.2},
+        "kn": {'totalHrs': 65.8},
+        "ml": {'totalHrs': 147.3},
+        "mr": {'totalHrs': 185.2},
+        "or": {'totalHrs': 111.6},
+        "pa": {'totalHrs': 136.9},
+        "sa": {'totalHrs': 115.5},
+        "ta": {'totalHrs': 185.5},
+        "te": {'totalHrs': 154.9},
+        "ur": {'totalHrs': 86.7},
+        "_all_": {'totalHrs': 1},
+    },
+    'totalDuration': 1, 'totalHrs': 1
+}
+