Initial commit with custom tsvs and modified huggingface dataset for Bengali speech
Browse files- .gitattributes +2 -0
- bengali_ai_tsv/eval.tsv +3 -0
- bengali_ai_tsv/test.tsv +3 -0
- bengali_ai_tsv/train.tsv +3 -0
- common_voice_bn.py +280 -0
- languages.py +1 -0
- release_stats.py +1 -0
.gitattributes
CHANGED
@@ -35,3 +35,5 @@ saved_model/**/* filter=lfs diff=lfs merge=lfs -text
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*.mp3 filter=lfs diff=lfs merge=lfs -text
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*.ogg filter=lfs diff=lfs merge=lfs -text
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*.wav filter=lfs diff=lfs merge=lfs -text
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*.mp3 filter=lfs diff=lfs merge=lfs -text
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*.ogg filter=lfs diff=lfs merge=lfs -text
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*.wav filter=lfs diff=lfs merge=lfs -text
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#CSV and TSV Files
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*.tsv filter=lfs diff=lfs merge=lfs -text
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bengali_ai_tsv/eval.tsv
ADDED
@@ -0,0 +1,3 @@
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version https://git-lfs.github.com/spec/v1
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oid sha256:ae93e04ad63bdb935f8d55731ee8f5e28a0f662d6defc1133540f2e6f166a3ba
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size 1917465
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bengali_ai_tsv/test.tsv
ADDED
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version https://git-lfs.github.com/spec/v1
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oid sha256:e75627620263ca6943e75cbd495e945baf802b94cfa0e4ee09f2d2a8a18b796b
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size 1903839
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bengali_ai_tsv/train.tsv
ADDED
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version https://git-lfs.github.com/spec/v1
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+
oid sha256:b3da36a57475267b99609db6c9406dd453711ec4dbb9423bc9728e0fbdd7ac81
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size 47056490
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common_voice_bn.py
ADDED
@@ -0,0 +1,280 @@
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import csv
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import os
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import urllib
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import datasets
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from datasets.utils.py_utils import size_str
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import datasets
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import requests
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from datasets.utils.py_utils import size_str
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from huggingface_hub import HfApi, HfFolder
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# from .languages import LANGUAGES
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#Used to get tar.gz file from mozilla website
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from .release_stats import STATS
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#Hard Links
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_HOMEPAGE = "https://commonvoice.mozilla.org/en/datasets"
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_LICENSE = "https://creativecommons.org/publicdomain/zero/1.0/"
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_API_URL = "https://commonvoice.mozilla.org/api/v1"
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class CommonVoiceConfig(datasets.BuilderConfig):
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"""BuilderConfig for CommonVoice."""
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+
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def __init__(self, name, version, **kwargs):
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self.language = "bn" # kwargs.pop("language", None)
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self.release_date = "2022-04-27" # kwargs.pop("release_date", None)
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self.num_clips = 231120 # kwargs.pop("num_clips", None)
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self.num_speakers = 19863 # kwargs.pop("num_speakers", None)
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self.validated_hr = 56.61 # kwargs.pop("validated_hr", None)
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self.total_hr = 399.47 # kwargs.pop("total_hr", None)
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self.size_bytes = 8262390506 # kwargs.pop("size_bytes", None)
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self.size_human = size_str(self.size_bytes)
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description = (
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f"Common Voice speech to text dataset in {self.language} released on {self.release_date}. "
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f"The dataset comprises {self.validated_hr} hours of validated transcribed speech data "
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f"out of {self.total_hr} hours in total from {self.num_speakers} speakers. "
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f"The dataset contains {self.num_clips} audio clips and has a size of {self.size_human}."
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)
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super(CommonVoiceConfig, self).__init__(
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name=name,
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version=datasets.Version(version),
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description=description,
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**kwargs,
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)
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|
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class CommonVoice(datasets.GeneratorBasedBuilder):
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#DEFAULT_CONFIG_NAME = "en"
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DEFAULT_CONFIG_NAME = "bn"
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DEFAULT_WRITER_BATCH_SIZE = 1000
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|
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BUILDER_CONFIGS = [
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CommonVoiceConfig(
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name="bn"#lang,
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version= '9.0.0' #STATS["version"],
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language= "Bengali" #LANGUAGES[lang],
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release_date= "2022-04-27" #STATS["date"],
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num_clips= 231120 #lang_stats["clips"],
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num_speakers= 19863 #lang_stats["users"],
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validated_hr= float(56.61) #float(lang_stats["validHrs"]),
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total_hr= float(399.47) #float(lang_stats["totalHrs"]),
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size_bytes= int(8262390506) #int(lang_stats["size"]),
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)
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#for lang, lang_stats in STATS["locales"].items()
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]
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78 |
+
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def _info(self):
|
80 |
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# total_languages = len(STATS["locales"])
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81 |
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# total_valid_hours = STATS["totalValidHrs"]
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82 |
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total_languages = 1 #len(STATS["locales"])
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83 |
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total_valid_hours = float(399.47) #STATS["totalValidHrs"]
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description = (
|
85 |
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"Common Voice Bangla is bengali AI's initiative to help teach machines how real people speak in Bangla. "
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f"The dataset is for initial training of a general speech recognition model for Bangla."
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)
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features = datasets.Features(
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{
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"client_id": datasets.Value("string"),
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"path": datasets.Value("string"),
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"audio": datasets.features.Audio(sampling_rate=48_000),
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"sentence": datasets.Value("string"),
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"up_votes": datasets.Value("int64"),
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"down_votes": datasets.Value("int64"),
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"age": datasets.Value("string"),
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"gender": datasets.Value("string"),
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"accent": datasets.Value("string"),
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"locale": datasets.Value("string"),
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"segment": datasets.Value("string"),
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}
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)
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return datasets.DatasetInfo(
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description=description,
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features=features,
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supervised_keys=None,
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+
# homepage=_HOMEPAGE,
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license=_LICENSE,
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# citation=_CITATION,
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version=self.config.version,
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# task_templates=[
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# AutomaticSpeechRecognition(audio_file_path_column="path", transcription_column="sentence")
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# ],
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)
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116 |
+
|
117 |
+
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118 |
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def _get_bundle_url(self, locale, url_template):
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# path = encodeURIComponent(path)
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120 |
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path = url_template.replace("{locale}", locale)
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path = urllib.parse.quote(path.encode("utf-8"), safe="~()*!.'")
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122 |
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# use_cdn = self.config.size_bytes < 20 * 1024 * 1024 * 1024
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# response = requests.get(f"{_API_URL}/bucket/dataset/{path}/{use_cdn}", timeout=10.0).json()
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response = requests.get(
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f"{_API_URL}/bucket/dataset/{path}", timeout=10.0
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).json()
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return response["url"]
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+
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129 |
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def _log_download(self, locale, bundle_version, auth_token):
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if isinstance(auth_token, bool):
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auth_token = HfFolder().get_token()
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132 |
+
whoami = HfApi().whoami(auth_token)
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133 |
+
email = whoami["email"] if "email" in whoami else ""
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+
payload = {"email": email, "locale": locale, "dataset": bundle_version}
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requests.post(f"{_API_URL}/{locale}/downloaders", json=payload).json()
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+
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def _split_generators(self, dl_manager):
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"""Returns SplitGenerators."""
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139 |
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hf_auth_token = dl_manager.download_config.use_auth_token
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140 |
+
if hf_auth_token is None:
|
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raise ConnectionError(
|
142 |
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"Please set use_auth_token=True or use_auth_token='<TOKEN>' to download this dataset"
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)
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144 |
+
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bundle_url_template = STATS["bundleURLTemplate"]
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bundle_version = bundle_url_template.split("/")[0]
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dl_manager.download_config.ignore_url_params = True
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148 |
+
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149 |
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self._log_download(self.config.name, bundle_version, hf_auth_token)
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150 |
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archive_path = dl_manager.download(
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self._get_bundle_url(self.config.name, bundle_url_template)
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)
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local_extracted_archive = (
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dl_manager.extract(archive_path) if not dl_manager.is_streaming else None
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)
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156 |
+
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if self.config.version < datasets.Version("5.0.0"):
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path_to_data = ""
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else:
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path_to_data = "/".join([bundle_version, self.config.name])
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path_to_clips = "/".join([path_to_data, "clips"]) if path_to_data else "clips"
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+
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#we provide our custom csvs with the huggingface repo so,
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path_to_tsvs = "/" + "bengali_ai_tsv" + "/"
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return [
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datasets.SplitGenerator(
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name=datasets.Split.TRAIN,
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+
gen_kwargs={
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"local_extracted_archive": local_extracted_archive,
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"archive_iterator": dl_manager.iter_archive(archive_path),
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#"metadata_filepath": "/".join([path_to_data, "train.tsv"])
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# if path_to_data
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# else "train.tsv",
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#custom train.tsv
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"metadata_filepath": "/".join([path_to_tsvs, "train.tsv"]),
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"path_to_clips": path_to_clips,
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},
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),
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180 |
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datasets.SplitGenerator(
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name=datasets.Split.TEST,
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gen_kwargs={
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183 |
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"local_extracted_archive": local_extracted_archive,
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"archive_iterator": dl_manager.iter_archive(archive_path),
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#"metadata_filepath": "/".join([path_to_data, "test.tsv"])
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# if path_to_data
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# else "test.tsv",
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#custom test.tsv
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"metadata_filepath": "/".join([path_to_tsvs, "test.tsv"]),
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190 |
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"path_to_clips": path_to_clips,
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},
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),
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datasets.SplitGenerator(
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name=datasets.Split.VALIDATION,
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gen_kwargs={
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196 |
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"local_extracted_archive": local_extracted_archive,
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197 |
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"archive_iterator": dl_manager.iter_archive(archive_path),
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198 |
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# "metadata_filepath": "/".join([path_to_data, "dev.tsv"])
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# if path_to_data
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# else "dev.tsv",
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#custom test.tsv
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"metadata_filepath": "/".join([path_to_tsvs, "eval.tsv"]),
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203 |
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"path_to_clips": path_to_clips,
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},
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),
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]
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def _generate_examples(
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self,
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local_extracted_archive,
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213 |
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archive_iterator,
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214 |
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metadata_filepath,
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215 |
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path_to_clips,
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):
|
217 |
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"""Yields examples."""
|
218 |
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data_fields = list(self._info().features.keys())
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219 |
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metadata = {}
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220 |
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metadata_found = False
|
221 |
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for path, f in archive_iterator:
|
222 |
+
if path == metadata_filepath:
|
223 |
+
metadata_found = True
|
224 |
+
lines = (line.decode("utf-8") for line in f)
|
225 |
+
reader = csv.DictReader(lines, delimiter="\t", quoting=csv.QUOTE_NONE)
|
226 |
+
for row in reader:
|
227 |
+
# set absolute path for mp3 audio file
|
228 |
+
if not row["path"].endswith(".mp3"):
|
229 |
+
row["path"] += ".mp3"
|
230 |
+
row["path"] = os.path.join(path_to_clips, row["path"])
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231 |
+
# accent -> accents in CV 8.0
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232 |
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if "accents" in row:
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233 |
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row["accent"] = row["accents"]
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234 |
+
del row["accents"]
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235 |
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# if data is incomplete, fill with empty values
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+
for field in data_fields:
|
237 |
+
if field not in row:
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238 |
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row[field] = ""
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239 |
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metadata[row["path"]] = row
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240 |
+
elif path.startswith(path_to_clips):
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241 |
+
assert metadata_found, "Found audio clips before the metadata TSV file."
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242 |
+
if not metadata:
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243 |
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break
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244 |
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if path in metadata:
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245 |
+
result = metadata[path]
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246 |
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# set the audio feature and the path to the extracted file
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path = (
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os.path.join(local_extracted_archive, path)
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249 |
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if local_extracted_archive
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250 |
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else path
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251 |
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)
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252 |
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result["audio"] = {"path": path, "bytes": f.read()}
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253 |
+
# set path to None if the audio file doesn't exist locally (i.e. in streaming mode)
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254 |
+
result["path"] = path if local_extracted_archive else None
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yield path, result
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275 |
+
# 'bn': {'duration': 1438112808, 'reportedSentences': 693, 'buckets': {'dev': 7748, 'invalidated': 5844, 'other': 192522,
|
276 |
+
# 'reported': 717, 'test': 7748, 'train': 14503, 'validated': 32754}, 'clips': 231120, 'splits': {'accent': {'': 1},
|
277 |
+
# 'age': {'thirties': 0.02, 'twenties': 0.22, '': 0.72, 'teens': 0.04, 'fourties': 0},
|
278 |
+
# 'gender': {'male': 0.24, '': 0.72, 'female': 0.04, 'other': 0}}, 'users': 19863, 'size': 8262390506,
|
279 |
+
# 'checksum': '599a5f7c9e55a297928da390345a19180b279a1f013081e7255a657fc99f98d5', 'avgDurationSecs': 6.222,
|
280 |
+
# 'validDurationSecs': 203807.316, 'totalHrs': 399.47, 'validHrs': 56.61},
|
languages.py
ADDED
@@ -0,0 +1 @@
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|
|
|
|
1 |
+
LANGUAGES = {"bn": "Bengali"}
|
release_stats.py
ADDED
@@ -0,0 +1 @@
|
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|
1 |
+
STATS = {'bundleURLTemplate': 'cv-corpus-9.0-2022-04-27/cv-corpus-9.0-2022-04-27-{locale}.tar.gz', 'date': '2022-04-27', 'name': 'Common Voice Corpus 9.0', 'multilingual': True, 'locales': {'en': {'duration': 10632910099, 'buckets': {'dev': 16335, 'invalidated': 242945, 'other': 267228, 'reported': 3903, 'test': 16335, 'train': 890116, 'validated': 1556254}, 'reportedSentences': 3842, 'clips': 2066427, 'splits': {'accent': {'': 1}, 'age': {'': 0.37, 'twenties': 0.24, 'sixties': 0.04, 'thirties': 0.13, 'teens': 0.06, 'seventies': 0.01, 'fourties': 0.1, 'fifties': 0.05, 'eighties': 0, 'nineties': 0}, 'gender': {'': 0.37, 'male': 0.46, 'female': 0.15, 'other': 0.02}}, 'users': 81085, 'size': 76768058135, 'checksum': '7c789a325e1d9f16137c1aeab9f45a1fde049a39b8fbf49e9ef4a8827ae67eae', 'avgDurationSecs': 5.146, 'validDurationSecs': 8007787.777, 'totalHrs': 2953.58, 'validHrs': 2224.38}, 'eu': {'reportedSentences': 44, 'buckets': {'dev': 6558, 'invalidated': 5785, 'other': 26668, 'reported': 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'users': 1264, 'size': 1608944247, 'checksum': '7064e9f756fb93b4d0c1b0dae619280d3470c5e95cb7e5406953ac4888dbd8d7', 'avgDurationSecs': 3.694, 'validDurationSecs': 244067.383, 'totalHrs': 71.29, 'validHrs': 67.79}, 'ar': {'reportedSentences': 2033, 'buckets': {'dev': 10220, 'invalidated': 14873, 'other': 30302, 'reported': 2040, 'test': 10421, 'train': 28139, 'validated': 75322}, 'duration': 502349703, 'clips': 120497, 'splits': {'accent': {'': 1}, 'age': {'thirties': 0.12, '': 0.58, 'twenties': 0.26, 'fourties': 0.01, 'teens': 0.03, 'fifties': 0, 'sixties': 0, 'nineties': 0}, 'gender': {'female': 0.17, '': 0.57, 'male': 0.25, 'other': 0}}, 'users': 1237, 'size': 2995697303, 'checksum': 'd29c81a1801ba01af97b7a90548dfd0409b9efa9b9d1291e28deee90267a746b', 'avgDurationSecs': 4.169, 'validDurationSecs': 314017, 'totalHrs': 139.54, 'validHrs': 87.23}, 'zh-TW': {'reportedSentences': 139, 'buckets': {'dev': 4618, 'invalidated': 4482, 'other': 37593, 'reported': 138, 'test': 4618, 'train': 6393, 'validated': 74894}, 'duration': 380039242, 'clips': 116969, 'splits': {'accent': {'': 1}, 'age': {'thirties': 0.2, 'twenties': 0.33, 'teens': 0.05, '': 0.28, 'fifties': 0.04, 'seventies': 0, 'fourties': 0.1, 'sixties': 0}, 'gender': {'male': 0.46, '': 0.27, 'female': 0.25, 'other': 0.02}}, 'users': 2002, 'size': 2719746719, 'checksum': 'b40023ca8f5113a3766ba2d0844c3e846ff48eb1d4408d9ae912d4f9caa183eb', 'avgDurationSecs': 3.249, 'validDurationSecs': 243335.063, 'totalHrs': 105.56, 'validHrs': 67.59}, 'br': {'duration': 71324827, 'reportedSentences': 183, 'buckets': {'dev': 2161, 'invalidated': 756, 'other': 11283, 'reported': 182, 'test': 2150, 'train': 2561, 'validated': 11152}, 'clips': 23191, 'splits': {'accent': {'': 1}, 'age': {'twenties': 0.25, '': 0.33, 'fifties': 0.06, 'fourties': 0.07, 'thirties': 0.08, 'sixties': 0.18, 'seventies': 0.02, 'teens': 0.01}, 'gender': {'male': 0.65, '': 0.34, 'female': 0.02}}, 'users': 172, 'size': 525880271, 'checksum': '7a49666d12df795d95c5d64e827970e40863f26dfb87ceae61d14819788e6cfa', 'avgDurationSecs': 3.076, 'validDurationSecs': 34298.412, 'totalHrs': 19.81, 'validHrs': 9.52}, 'pt': {'duration': 484853047, 'reportedSentences': 2305, 'buckets': {'dev': 8528, 'invalidated': 4416, 'other': 11900, 'reported': 2310, 'test': 8539, 'train': 17559, 'validated': 99173}, 'clips': 115489, 'splits': {'accent': {'': 1}, 'age': {'': 0.2, 'twenties': 0.42, 'teens': 0.03, 'thirties': 0.22, 'fourties': 0.1, 'sixties': 0, 'fifties': 0.03, 'seventies': 0}, 'gender': {'': 0.2, 'male': 0.74, 'female': 0.04, 'other': 0.02}}, 'users': 2453, 'size': 3187978215, 'checksum': '1a748f21ba194d57ecd6418cce9692a198eeabcb44ba6e2b7a34435efc6625a4', 'avgDurationSecs': 4.198, 'validDurationSecs': 416354.209, 'totalHrs': 134.68, 'validHrs': 115.65}, 'eo': {'duration': 6712729612, 'reportedSentences': 2113, 'buckets': {'dev': 14911, 'invalidated': 127285, 'other': 130550, 'reported': 2115, 'test': 14915, 'train': 143973, 'validated': 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