thucdangvan020999/singaporean_district_noise_snr_5_10

Singaporean district with noise

Dataset Description

Singaporean district speech dataset with controlled noise augmentation for ASR training

Dataset Summary

• Language: EN
• Task: Automatic Speech Recognition
• Total Samples: 252
• Audio Sample Rate: 16kHz
• Base Dataset: Custom dataset
• Processing: Noise-augmented

Dataset Structure

Data Fields

• audio: Audio file (16kHz WAV format)
• text: Transcription text
• noise_type: Type of background noise added
• actual_snr_db: Measured Signal-to-Noise Ratio in dB
• target_snr_db: Target SNR used for augmentation
• sample_index: Original sample index from base dataset

Data Splits

The dataset contains 252 samples in the training split.

Noise Augmentation Details

• Noise Types and Distribution:
  • station: 134
  • bus: 118
• SNR Statistics:
  • Min SNR: 5.0 dB
  • Max SNR: 10.0 dB
  • Average SNR: 7.4 dB
  • SNR Standard Deviation: 1.4 dB

Usage

Loading the Dataset

from datasets import load_dataset

# Load the dataset
dataset = load_dataset("thucdangvan020999/singaporean_district_noise_snr_5_10")

# Access the data
for sample in dataset['train']:
    audio_array = sample['audio']['array']
    sampling_rate = sample['audio']['sampling_rate'] 
    text = sample['text']
    
    # Your processing code here
    print(f"Audio shape: {audio_array.shape}")
    print(f"Text: {text}")

Example Usage with Transformers

from datasets import load_dataset
from transformers import WhisperProcessor, WhisperForConditionalGeneration

# Load dataset and model
dataset = load_dataset("thucdangvan020999/singaporean_district_noise_snr_5_10")
processor = WhisperProcessor.from_pretrained("openai/whisper-small")
model = WhisperForConditionalGeneration.from_pretrained("openai/whisper-small")

# Process a sample
sample = dataset['train'][0]
inputs = processor(
    sample['audio']['array'], 
    sampling_rate=sample['audio']['sampling_rate'], 
    return_tensors="pt"
)

# Generate transcription
with torch.no_grad():
    predicted_ids = model.generate(inputs["input_features"])
    transcription = processor.batch_decode(predicted_ids, skip_special_tokens=True)

Dataset Creation

This dataset was created using the Universal ASR Processor with the following configuration:

• Base Dataset: Custom source
• Processing Method: Noise augmentation with SNR control
• Sample Rate: 16kHz
• Quality Control: SNR-based noise mixing

Processing Details

The dataset was processed to ensure:

• Consistent audio quality and format
• Proper noise mixing with controlled SNR levels
• Metadata preservation for reproducibility
• Quality validation and statistics

Licensing and Usage

This dataset is released under the cc-by-4.0 license.

Citation

If you use this dataset in your research, please cite:

@dataset{thucdangvan020999_singaporean_district_noise_snr_5_10_dataset,
  title={Singaporean district with noise},
  author={Dataset Creator},
  url={https://huggingface.co/datasets/thucdangvan020999/singaporean_district_noise_snr_5_10},
  year={2024}
}

Contact

For questions or issues regarding this dataset, please open an issue in the dataset repository.

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This dataset card was automatically generated using the Universal ASR Processor.