sujalappa/speech-brain-noise-evaluation-dataset

Speech Brain Noise Evaluation Dataset

Dataset Description

This dataset contains 2,000 samples organized across multiple splits and 20 subsets. The dataset includes audio data.

Dataset Structure

Subsets

This dataset includes the following subsets:

• noisy-bg-snr-10: 100 samples
  • test: 100 samples
• noisy-bg-snr-30: 100 samples
  • test: 100 samples
• noisy-bg-snr-50: 100 samples
  • test: 100 samples
• denoised-bg-snr-10: 100 samples
  • test: 100 samples
• denoised-bg-snr-30: 100 samples
  • test: 100 samples
• denoised-bg-snr-50: 100 samples
  • test: 100 samples
• noisy-short-snr-10: 100 samples
  • test: 100 samples
• noisy-short-snr-30: 100 samples
  • test: 100 samples
• noisy-short-snr-50: 100 samples
  • test: 100 samples
• denoised-short-snr-10: 100 samples
  • test: 100 samples
• denoised-short-snr-30: 100 samples
  • test: 100 samples
• denoised-short-snr-50: 100 samples
  • test: 100 samples
• noisy-gauss-amp-0.001: 100 samples
  • test: 100 samples
• noisy-gauss-amp-0.009: 100 samples
  • test: 100 samples
• noisy-gauss-amp-0.017: 100 samples
  • test: 100 samples
• denoised-gauss-amp-0.001: 100 samples
  • test: 100 samples
• denoised-gauss-amp-0.009: 100 samples
  • test: 100 samples
• denoised-gauss-amp-0.017: 100 samples
  • test: 100 samples
• original: 100 samples
  • test: 100 samples
• denoised-original: 100 samples
  • test: 100 samples

Usage

Load specific subset and split:

from datasets import load_dataset

# Load specific subset and split
dataset = load_dataset('sujalappa/speech-brain-noise-evaluation-dataset', 'noisy-bg-snr-10', split='train')

# Load all splits from a subset
dataset = load_dataset('sujalappa/speech-brain-noise-evaluation-dataset', 'noisy-bg-snr-10')

# Load everything
dataset = load_dataset('sujalappa/speech-brain-noise-evaluation-dataset')

Dataset Creation

This dataset was created using StreamableDatasetManager on 2025-10-03T17:50:29.410615.

Data Fields

The dataset includes the following columns:

• md5_text: String data
• file_name: String data
• md5_audio: String data
• duration: Float32 data
• text: String data
• audio_language: String data
• text_language: String data
• session_id: String data
• speaker: String data
• type_concept: String data
• recording_context: String data
• medical_entities: String data
• filename: String data
• original_path: Audio data (16kHz sampling rate)
• audio: Audio data (16kHz sampling rate)

Technical Details

• Total samples: 2,000
• Shard length: 100
• Number of subsets: 20
• Number of splits: 2
• Audio format: 16kHz sampling rate