Update hausa_2_eng_2.py

hausa_2_eng_2.py

@@ -13,59 +13,21 @@ from .languages import LANGUAGES
 from .release_stats import STATS
 
 
-_CITATION = """\
-@inproceedings{commonvoice:2020,
-  author = {Ardila, R. and Branson, M. and Davis, K. and Henretty, M. and Kohler, M. and Meyer, J. and Morais, R. and Saunders, L. and Tyers, F. M. and Weber, G.},
-  title = {Common Voice: A Massively-Multilingual Speech Corpus},
-  booktitle = {Proceedings of the 12th Conference on Language Resources and Evaluation (LREC 2020)},
-  pages = {4211--4215},
-  year = 2020
-}
-"""
 
 
 
 
-_HOMEPAGE = "https://commonvoice.mozilla.org/en/datasets"
 
 _BASE_URL = "https://huggingface.co/datasets/Seon25/hausa_2_eng_2/resolve/main"
 
-_AUDIO_URL = _BASE_URL + "audio/{lang}/{split}/{lang}_{split}_{shard_idx}.tar"
+_AUDIO_URL = _BASE_URL + "audio/ha/{split}/ha_{split}_0.tar"
 
-_TRANSCRIPT_URL = _BASE_URL + "transcript/{lang}/{split}.tsv"
-
-_N_SHARDS_URL = _BASE_URL + "n_shards.json"
-
-
-class Hausa2EngConfig(datasets.BuilderConfig):
-    """BuilderConfig for CommonVoice."""
-
-    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 = (
-            f"Common Voice speech to text dataset in {self.language} released on {self.release_date}. "
-            f"The dataset comprises {self.validated_hr} hours of validated transcribed speech data "
-            f"out of {self.total_hr} hours in total from {self.num_speakers} speakers. "
-            f"The dataset contains {self.num_clips} audio clips and has a size of {self.size_human}."
-        )
-        super(Hausa2EngConfig, self).__init__(
-            name=name,
-            version=datasets.Version(version),
-            description=description,
-            **kwargs,
-        )
+_TRANSCRIPT_URL = _BASE_URL + "transcript/ha/{split}.tsv"
+_N_SHARDS_URL ="n_shards.json"
 
 
 
 class Hausa2Eng(datasets.GeneratorBasedBuilder):
-    DEFAULT_WRITER_BATCH_SIZE = 1000
 
     BUILDER_CONFIGS = [
         Hausa2EngConfig(
@@ -83,12 +45,12 @@ class Hausa2Eng(datasets.GeneratorBasedBuilder):
     ]
 
     def _info(self):
-        total_languages = len(STATS["locales"])
+        
         total_valid_hours = STATS["totalValidHrs"]
         description = (
             "Common Voice is Mozilla's initiative to help teach machines how real people speak. "
-            f"The dataset currently consists of {total_valid_hours} validated hours of speech "
-            f" in {total_languages} languages, but more voices and languages are always added."
+            f"The dataset currently consists of validated hours of speech "
+            f" in  languages, but more voices and languages are always added."
         )
         features = datasets.Features(
             {
@@ -111,14 +73,11 @@ class Hausa2Eng(datasets.GeneratorBasedBuilder):
             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
+        lang = "ha"
         n_shards_path = dl_manager.download_and_extract(_N_SHARDS_URL)
         with open(n_shards_path, encoding="utf-8") as f:
             n_shards = json.load(f)
@@ -127,12 +86,12 @@ class Hausa2Eng(datasets.GeneratorBasedBuilder):
         splits = ("train", "dev", "test", "other", "invalidated")
         for split in splits:
             audio_urls[split] = [
-                _AUDIO_URL.format(lang=lang, split=split, shard_idx=i) for i in range(n_shards[lang][split])
+                _AUDIO_URL.format(lang="ha", split=split, 0) 
             ]
         archive_paths = dl_manager.download(audio_urls)
         local_extracted_archive_paths = dl_manager.extract(archive_paths) if not dl_manager.is_streaming else {}
 
-        meta_urls = {split: _TRANSCRIPT_URL.format(lang=lang, split=split) for split in splits}
+        meta_urls = {split: _TRANSCRIPT_URL.format(lang="ha", split=split) for split in splits}
         meta_paths = dl_manager.download_and_extract(meta_urls)
 
         split_generators = []