---
license: cc-by-4.0
task_categories:
  - audio-to-audio
language:
  - en
size_categories:
  - n<1K
tags:
  - speech-enhancement
  - denoising
  - dns-challenge
pretty_name: DNS Challenge 2020 Dev Test Set (16kHz)
---

# DNS Challenge 2020 Dev Test Set

Preprocessed dev test set from the [Interspeech 2020 DNS Challenge](https://www.microsoft.com/en-us/research/academic-program/deep-noise-suppression-challenge-interspeech-2020/).

## Dataset Structure

| Split | Samples | Clean Reference | Description |
|-------|---------|-----------------|-------------|
| `synthetic_no_reverb` | 150 | ✓ | Anechoic synthetic mixtures |
| `synthetic_with_reverb` | 150 | ✓ | Reverberant synthetic mixtures |
| `real_recordings` | 300 | ✗ | Real-world noisy recordings |

## Usage

```python
from datasets import load_dataset
ds = load_dataset("nkdem/DNS-Challenge-2020-DevTest-16k")

# Access a sample
sample = ds['synthetic_no_reverb'][0]
print(sample.keys())  # ['id', 'fileid', 'noisy', 'clean', 'subset', 'has_reference']
```

## Audio Format

- 16kHz mono WAV
- 10 seconds per clip
- Stored as bytes (use soundfile to decode)

```python
import soundfile as sf
import io

audio, sr = sf.read(io.BytesIO(sample['noisy']['bytes']), dtype='float32')
```

## Source

This dataset is derived from the official DNS Challenge 2020 test set. The original data was downloaded from Microsoft's DNS Challenge repository and repackaged for easier use with HuggingFace datasets.

## Citation

```bibtex
@inproceedings{reddy2020interspeech,
  title={The INTERSPEECH 2020 Deep Noise Suppression Challenge: Datasets, Subjective Testing Framework, and Challenge Results},
  author={Reddy, Chandan KA and Gopal, Vishak and Cutler, Ross and Beeseley, Ebrahim and Aichner, Robert and Braun, Sebastian and Gamper, Hannes and Haas, Sebastian and Kindermans, Pieter-Jan and Loide, Marko and others},
  booktitle={Interspeech},
  year={2020}
}
```