Upload Uyghur.py

Uyghur.py

@@ -0,0 +1,152 @@
+import datasets
+from datasets import DownloadManager, DatasetInfo
+from datasets.tasks import AutomaticSpeechRecognition
+import os
+import csv
+import json
+
+# TODO: Add BibTeX citation
+# Find for instance the citation on arxiv or on the dataset repo/website
+_CITATION = """\
+@InProceedings{huggingface:dataset,
+title = {A great new dataset},
+author={huggingface, Inc.
+},
+year={2022}
+}
+"""
+# TODO: Add description of the dataset here
+# You can copy an official description
+_DESCRIPTION = """\
+This new dataset is from Xinjiang University and to do some ASR in low resource.
+"""
+
+# TODO: Add a link to an official homepage for the dataset here
+_HOMEPAGE = "http://www.openslr.org/22"
+
+# TODO: Add the licence for the dataset here if you can find it
+_LICENSE = ""
+
+# TODO: Add link to the official dataset URLs here
+# The HuggingFace Datasets library doesn't host the datasets but only points to the original files.
+# This can be an arbitrary nested dict/list of URLs (see below in `_split_generators` method)
+
+_URL = "https://huggingface.co/datasets/sunlixu/Uyghur/"
+
+_DL_URLS = {
+    "train":
+        'train.tar.gz',
+    "test":
+        "test.tar.gz",
+    "cv":
+        "cv.tar.gz",
+    "all": {
+        "train":
+            'train.tar.gz',
+        "test":
+            "test.tar.gz",
+        "cv":
+            "cv.tar.gz"
+           },
+}
+
+
+class UyghurASRConfig(datasets.BuilderConfig):
+    def __init__(self, **kwargs):
+        """BuilderConfig for SQUAD.
+        Args:
+          **kwargs: keyword arguments forwarded to super.
+        """
+        super(UyghurASRConfig, self).__init__(**kwargs)
+
+
+class UyghurASR(datasets.GeneratorBasedBuilder):
+    DEFAULT_WRITER_BATCH_SIZE = 256
+    DEFAULT_CONFIG_NAME = "all"
+    BUILDER_CONFIGS = [
+        UyghurASRConfig(name="train", description="'train' speech."),
+        UyghurASRConfig(name="test", description="'test' speech."),
+        UyghurASRConfig(name="cv", description="'cv' speech."),
+        UyghurASRConfig(name="all", description="all"),
+    ]
+
+    def _info(self) -> DatasetInfo:
+        return datasets.DatasetInfo(
+            description="Uyghur_20",
+            features=datasets.Features(
+                {
+                    "file": datasets.Value("string"),
+                    "audio": datasets.features.Audio(sampling_rate=16_000),
+                    "text": datasets.Value("string"),
+                    "speaker_id": datasets.Value("string"),
+                    "id": datasets.Value("string"),
+                }
+            ),
+            supervised_keys=None,
+            homepage='https://huggingface.co/datasets/sunlixu/Uyghur/',
+            citation=_CITATION,
+            task_templates=[AutomaticSpeechRecognition(audio_column="audio", transcription_column="text")],
+        )
+
+    def _split_generators(self, dl_manager: DownloadManager):
+        # print(self.config.name)
+        # archive_path = dl_manager.download_and_extract(_DL_URLS[self.config.name])
+        archive_path = dl_manager.download(_DL_URLS[self.config.name])
+        local_extracted_archive = dl_manager.extract(archive_path) if not dl_manager.is_streaming else {}
+        return [
+            datasets.SplitGenerator(name=datasets.Split.TRAIN,
+                                    gen_kwargs={"local_extracted_archive": archive_path["train"],
+                                                "files": dl_manager.iter_archive(archive_path["train"]),
+                                                },
+                                    ),
+            datasets.SplitGenerator(name=datasets.Split.TEST,
+                                    gen_kwargs={"local_extracted_archive": archive_path['test'],
+                                                "files": dl_manager.iter_archive(archive_path["test"]),
+                                                },
+                                    ),
+            datasets.SplitGenerator(name=datasets.Split.VALIDATION,
+                                    gen_kwargs={"local_extracted_archive": archive_path['cv'],
+                                                "files": dl_manager.iter_archive(archive_path["cv"]),
+                                                },
+                                    )
+        ]
+
+    def _generate_examples(self, files, local_extracted_archive):
+        """Generate examples from a Uyghur archive_path."""
+        key = 0
+        audio_data = {}
+        transcripts = []
+        for path, f in files:
+            if path.endswith(".wav"):
+                id_ = path.split("/")[-1][: -len(".wav")]
+                audio_data[id_] = f.read()
+            elif path.endswith(".txt"):
+                for line in f:
+                    if line:
+                        line = line.decode("utf-8").strip()
+                        id_, transcript = line.split(" ", 1)
+                        audio_file = f"{id_}.wav"
+                        # speaker_id, chapter_id = [int(el) for el in id_.split("-")[:2]]
+                        speaker_id = id_.split('_')[0]
+                        audio_file = (
+                            os.path.join(local_extracted_archive, audio_file)
+                            if local_extracted_archive
+                            else audio_file
+                        )
+                        transcripts.append(
+                            {
+                                "id": id_,
+                                "speaker_id": speaker_id,
+                                # "chapter_id": chapter_id,
+                                "file": audio_file,
+                                "text": transcript,
+                            }
+                        )
+            if audio_data and len(audio_data) == len(transcripts):
+                for transcript in transcripts:
+                    audio = {"path": transcript["file"], "bytes": audio_data[transcript["id"]]}
+                    yield key, {"audio": audio, **transcript}
+                    key += 1
+                audio_data = {}
+                transcripts = []
+