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import os
import csv
import datasets
from datasets import Audio, BuilderConfig
# BuilderConfig ni aniqlaymiz: bu yerda til qisqartmasi va asosiy data papkasi kiritiladi.
class STTConfig(BuilderConfig):
def __init__(self, language_abbr, data_dir, **kwargs):
"""
Args:
language_abbr (str): Til qisqartmasi, masalan "uz".
data_dir (str): Dataset joylashgan asosiy papka (misol: "Dataset_STT").
**kwargs: Qolgan BuilderConfig parametrlar.
"""
super().__init__(**kwargs)
self.language_abbr = language_abbr
self.data_dir = data_dir
class MySTTDataset(datasets.GeneratorBasedBuilder):
"""
Common Voice uslubidagi minimal STT dataset yuklash skripti:
- 3 ta tar fayl (train, test, validation) ichida .mp3 audio fayllar mavjud.
- Har bir split uchun mos TSV fayl (train.tsv, test.tsv, validation.tsv) transkripsiyalarni o‘z ichiga oladi.
- 'audio' ustuni Audio() tipida bo‘lib, Hugging Face Dataset Viewer’da "play" tugmasi orqali audio eshittirish imkoniyatini beradi.
"""
VERSION = datasets.Version("1.0.0")
# Agar bir nechta konfiguratsiya bo‘lmasa, oddiy qilib bitta config ishlatamiz.
BUILDER_CONFIGS = [
STTConfig(
name="uz",
version=datasets.Version("1.0.0"),
description="Uzbek subset of the STT dataset",
language_abbr="uz",
data_dir="Dataset_STT", # Bu yerga ma'lumotlar joylashgan asosiy papkani kiriting.
)
]
DEFAULT_CONFIG_NAME = "uz"
def _info(self):
"""
Datasetning xususiyatlari (features) aniqlanadi.
Agar 'audio' ustuni Audio() tipida bo‘lsa, Dataset Viewer audio pleyerni ko‘rsatadi.
"""
return datasets.DatasetInfo(
description="Uzbek STT dataset: audio fayllar .tar arxivda saqlanadi, transcriptions esa .tsv faylda.",
features=datasets.Features({
"id": datasets.Value("string"),
"audio": Audio(sampling_rate=None), # sampling_rate=None degani audio fayldan olingan asl sampling rate saqlanadi.
"sentence": datasets.Value("string"),
"duration": datasets.Value("float"),
"age": datasets.Value("string"),
"gender": datasets.Value("string"),
"accents": datasets.Value("string"),
"locale": datasets.Value("string"),
}),
supervised_keys=None,
version=self.VERSION,
)
def _split_generators(self, dl_manager):
"""
Har bir split uchun: tar va tsv fayllar yo‘llarini belgilab, dl_manager orqali ularni yuklab yoki extract qildik.
"""
config = self.config # STTConfig obyekti
base_dir = config.data_dir # Masalan: "Dataset_STT"
lang = config.language_abbr # Masalan: "uz"
# Audio va transkript fayllarining yo‘llarini shakllantiramiz:
train_tar = os.path.join(base_dir, "audio", lang, "train.tar")
train_tsv = os.path.join(base_dir, "transcript", lang, "train.tsv")
test_tar = os.path.join(base_dir, "audio", lang, "test.tar")
test_tsv = os.path.join(base_dir, "transcript", lang, "test.tsv")
val_tar = os.path.join(base_dir, "audio", lang, "validation.tar")
val_tsv = os.path.join(base_dir, "transcript", lang, "validation.tsv")
# Tar fayllarni extract qilamiz (agar lokal bo‘lsa, dl_manager.extract mos yo‘lni qaytaradi)
train_tar_extracted = dl_manager.extract(train_tar)
test_tar_extracted = dl_manager.extract(test_tar)
val_tar_extracted = dl_manager.extract(val_tar)
return [
datasets.SplitGenerator(
name=datasets.Split.TRAIN,
gen_kwargs={
"archive_dir": train_tar_extracted, # Tar fayl extract qilingan papka
"tsv_path": train_tsv,
},
),
datasets.SplitGenerator(
name=datasets.Split.TEST,
gen_kwargs={
"archive_dir": test_tar_extracted,
"tsv_path": test_tsv,
},
),
datasets.SplitGenerator(
name=datasets.Split.VALIDATION,
gen_kwargs={
"archive_dir": val_tar_extracted,
"tsv_path": val_tsv,
},
),
]
def _generate_examples(self, archive_dir, tsv_path):
"""
TSV faylini qatorma-qator o‘qib, metadata lug‘atini yaratadi va
extract qilingan archive papkasidan mos .mp3 faylni topadi.
"""
# TSV faylini ochamiz va DictReader yordamida o‘qiymiz.
with open(tsv_path, "r", encoding="utf-8") as f:
reader = csv.DictReader(f, delimiter="\t")
for idx, row in enumerate(reader):
# TSV faylida kutilayotgan ustunlar: id, sentence, duration, age, gender, accents, locale
audio_id = row["id"]
mp3_file = audio_id + ".mp3"
mp3_path = os.path.join(archive_dir, mp3_file)
# Agar extract qilingan papkada audio fayl mavjud bo‘lsa:
if os.path.isfile(mp3_path):
yield idx, {
"id": audio_id,
"audio": mp3_path, # Audio() tipidagi ustun avtomatik ravishda faylni o‘qiydi va dekodlaydi.
"sentence": row.get("sentence", ""),
"duration": float(row.get("duration", 0.0)),
"age": row.get("age", ""),
"gender": row.get("gender", ""),
"accents": row.get("accents", ""),
"locale": row.get("locale", ""),
}
else:
# Agar audio fayl topilmasa, bu yozuvni o'tkazib yuboramiz yoki xatolik chiqarish mumkin.
continue |