---
license: mit
dataset_info:
  features:
  - name: audio
    dtype: string
  - name: file_name
    dtype: string
  - name: folder
    dtype: string
  - name: transcription
    dtype: string
  - name: confidence
    dtype: string
  - name: trim_start_seconds
    dtype: float64
  - name: trim_end_seconds
    dtype: float64
  - name: reason_start
    dtype: string
  - name: reason_end
    dtype: string
  - name: has_incomplete_words
    dtype: bool
  - name: notes
    dtype: string
  - name: original_path
    dtype: string
  - name: batch_index
    dtype: int64
  - name: global_index
    dtype: int64
  splits:
  - name: train
    num_bytes: 12442238
    num_examples: 24369
  download_size: 3217525
  dataset_size: 12442238
configs:
- config_name: default
  data_files:
  - split: train
    path: data/train-*
---

# Sam04/BlueLionEcho_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: 6,456
- Total batches: 2525
- Audio folders: 3
- Files per folder: max 5000

## Loading the Dataset
```python
from datasets import load_dataset

# Load the complete dataset
dataset = load_dataset("Sam04/BlueLionEcho_tran")

# The 'audio' column contains paths like "audio_00000/0000000001_filename.wav"
# Files are automatically resolved when accessing the dataset
```

## Folder Organization

Audio files are distributed across folders to respect HuggingFace storage limits:
- `audio_00000/`: Files 0-4,999
- `audio_00001/`: Files 5,000-9,999
- etc.

Metadata (parquet files) are grouped by batch ranges:
- `data_00000/batches_0000000001_to_0000000020.parquet`
- etc.