Upload dataset_stt.py

dataset_stt.py

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+import csv
+import tarfile
+import datasets
+
+_DESCRIPTION = """\
+This dataset is designed for speech-to-text tasks and contains audio files stored in tar archives along with corresponding transcript files in TSV format.
+The dataset is organized by splits (train, test, validation) for the Uzbek language.
+"""
+
+_CITATION = """\
+@inproceedings{yourcitation2025,
+  title={Your Dataset Title},
+  author={Your Name},
+  year={2025},
+  eprint={XXXX.XXXX},
+  archivePrefix={arXiv},
+  primaryClass={cs.CL}
+}
+"""
+
+_LICENSE = "MIT"
+
+class DatasetSTT(datasets.GeneratorBasedBuilder):
+    VERSION = datasets.Version("1.0.0")
+
+    def _info(self):
+        # Belgilangan feature'lar: audio field Audio tipida (sampling_rate ni moslashtiring, masalan 16000)
+        features = datasets.Features({
+            "id": datasets.Value("string"),
+            "audio": datasets.Audio(sampling_rate=16000),
+            "sentence": datasets.Value("string"),
+            "duration": datasets.Value("float"),
+            "age": datasets.Value("string"),
+            "gender": datasets.Value("string"),
+            "accents": datasets.Value("string"),
+            "locale": datasets.Value("string"),
+        })
+        return datasets.DatasetInfo(
+            description=_DESCRIPTION,
+            features=features,
+            supervised_keys=None,
+            homepage="https://huggingface.co/datasets/Elyordev/Dataset_STT",
+            license=_LICENSE,
+            citation=_CITATION,
+        )
+
+    def _split_generators(self, dl_manager):
+        """
+        Biz kutilayotgan fayl strukturasini quyidagicha belgilaymiz:
+        
+        data_files = {
+            "train": {
+                "audio": "audio/uz/train/train.tar",
+                "transcript": "transcript/uz/train/train.tsv"
+            },
+            "test": {
+                "audio": "audio/uz/test/test.tar",
+                "transcript": "transcript/uz/test/test.tsv"
+            },
+            "validation": {
+                "audio": "audio/uz/validation/validation.tar",
+                "transcript": "transcript/uz/validation/validation.tsv"
+            }
+        }
+        """
+        data_files = self.config.data_files
+        return [
+            datasets.SplitGenerator(
+                name=datasets.Split.TRAIN,
+                gen_kwargs={
+                    "audio_archive": data_files["train"]["audio"],
+                    "transcript_file": data_files["train"]["transcript"],
+                },
+            ),
+            datasets.SplitGenerator(
+                name=datasets.Split.TEST,
+                gen_kwargs={
+                    "audio_archive": data_files["test"]["audio"],
+                    "transcript_file": data_files["test"]["transcript"],
+                },
+            ),
+            datasets.SplitGenerator(
+                name=datasets.Split.VALIDATION,
+                gen_kwargs={
+                    "audio_archive": data_files["validation"]["audio"],
+                    "transcript_file": data_files["validation"]["transcript"],
+                },
+            ),
+        ]
+
+    def _generate_examples(self, audio_archive, transcript_file):
+        """
+        Transcript TSV faylini o'qib, har bir yozuv uchun:
+         - tar arxivini ochib, "path" ustuni orqali audio faylni topamiz;
+         - Audio faylni baytlar shaklida o'qib, datasets.Audio feature'iga mos formatda qaytaramiz.
+        """
+        # Tar arxivini ochamiz
+        with tarfile.open(audio_archive, "r:*") as tar:
+            # Tar arxividagi barcha fayllarni indekslaymiz (fayl nomi -> tarinfo)
+            tar_index = {member.name: member for member in tar.getmembers() if member.isfile()}
+
+            # Transcript TSV faylini o'qish (UTF-8 kodlashda)
+            with open(transcript_file, "r", encoding="utf-8") as f:
+                reader = csv.DictReader(f, delimiter="\t")
+                for row in reader:
+                    file_name = row["path"]
+                    # Agar arxivda fayl topilsa:
+                    if file_name in tar_index:
+                        # Faylni o'qib, butun baytlarni olamiz
+                        audio_member = tar.extractfile(tar_index[file_name])
+                        if audio_member is None:
+                            print(f"Warning: Could not extract {file_name} from {audio_archive}.")
+                            continue
+                        audio_bytes = audio_member.read()
+                    else:
+                        # Agar fayl topilmasa, ogohlantirish chiqaramiz va davom etamiz.
+                        print(f"Warning: File {file_name} not found in archive {audio_archive}.")
+                        continue
+
+                    # Yozuvni qaytaramiz, audio maydoni uchun file nomi va baytlarni dictionary ko'rinishida beramiz.
+                    yield row["id"], {
+                        "id": row["id"],
+                        "audio": {"path": file_name, "bytes": audio_bytes},
+                        "sentence": row["sentence"],
+                        "duration": float(row["duration"]),
+                        "age": row["age"],
+                        "gender": row["gender"],
+                        "accents": row["accents"],
+                        "locale": row["locale"],
+                    }