affectexpect/t9p3c8m1-axr4e6_tran
affectexpect/t9p3c8m1-axr4e6_tran This dataset contains transcribed audio files organized in folders for scalability. Dataset Structure The dataset is organized with: Audio files: Stored in audio_XXXXX/ folders (5000 files per folder) Metadata: Stored in data_XXXXX/ folders as parquet files This organization follows Hugging Face best practices for datasets with millions of files. Statistics Total files: 8,901 Total batches: 5183 Audio folders: 6… See the full description on the dataset page: https://huggingface.co/datasets/affectexpect/t9p3c8m1-axr4e6_tran.
affectexpect/t9p3c8m1-axr4e6_tran
This dataset contains transcribed audio files organized in folders for scalability.
Dataset Structure
The dataset is organized with:
- Audio files: Stored in
audio_XXXXX/folders (5000 files per folder) - Metadata: Stored in
data_XXXXX/folders as parquet files
This organization follows Hugging Face best practices for datasets with millions of files.
Statistics
- Total files: 8,901
- Total batches: 5183
- Audio folders: 6
- Files per folder: max 5000
Loading the Dataset
from datasets import load_dataset
# Load the complete dataset
dataset = load_dataset("affectexpect/t9p3c8m1-axr4e6_tran")
# The 'audio' column contains paths like "audio_00000/0000000001_filename.wav"
# Files are automatically resolved when accessing the datasetFolder Organization
Audio files are distributed across folders to respect HuggingFace storage limits:
audio_00000/: Files 0-4,999audio_00001/: Files 5,000-9,999- etc.
Metadata (parquet files) are grouped by batch ranges:
data_00000/batches_0000000001_to_0000000020.parquet- etc.
