README.md

---
pretty_name: DEAF
language:
- en
license: cc-by-4.0
size_categories:
- n<1K
task_categories:
- audio-classification
- automatic-speech-recognition
tags:
- audio
- speech
- benchmark
- evaluation
- text-to-speech
- acoustics
configs:
  - config_name: BSC
    data_files:
      - split: test
        path: Data/metadata/BSC.csv

  - config_name: SIC
    data_files:
      - split: test
        path: Data/metadata/SIC.csv
---

# DEAF

DEAF is a collection of audio data, aligned text metadata, and data-generation scripts accompanying the paper [DEAF: A Benchmark for Diagnostic Evaluation of Acoustic Faithfulness in Audio Language Models](https://arxiv.org/abs/2603.18048).

This repository is organized as a Hugging Face dataset repository and contains the locally hosted resources used in the paper: BSC audio, SIC audio, paired text metadata, and the scripts used to generate the speech-related subsets.

## Repository structure

| Path | Description |
|------|-------------|
| `Data/Audio/BSC/` | 84 BSC audio files. |
| `Data/Audio/SIC/` | 248 SIC audio files. |
| `Data/metadata/BSC.csv` | Text metadata for the BSC subset. |
| `Data/metadata/SIC.csv` | Text metadata for the SIC subset. |
| `Code For Speech Generation/` | Scripts used to generate and process the BSC and SIC data. |

## Data overview

- `BSC.csv` contains 84 rows with two columns: `code` and `sentence`.
- `Data/Audio/BSC/` contains 84 corresponding `.wav` files.
- `SIC.csv` contains 82 rows with two columns: `code` and `sentence`.
- `Data/Audio/SIC/` contains 248 `.wav` files.


## Intended use

DEAF is intended for research use, especially:

- benchmarking acoustic faithfulness in audio language models,
- studying robustness of speech generation and speech understanding systems,
- analyzing how textual prompts map to generated or synthesized speech under different acoustic conditions.

## Data fields

Both metadata files use the same schema:

- `code`: sample identifier used to align metadata with audio filenames or prompt templates,
- `sentence`: the text content associated with the audio sample.

Examples:

```text
code,sentence
DKITCHEN_E01,"I'm cooking dinner in the kitchen, preparing food slowly while enjoying the quiet routine."
GDR_EX_F_01,"As a mother of three, I have learned to balance work, family, and personal responsibilities while always trying to set a good example for my children."
```

## Audio format

- Audio files are stored as `.wav`.
- The speech-generation scripts indicate a workflow targeting 16 kHz WAV output for generated assets.
- Users should verify any subset-specific preprocessing assumptions directly from the scripts before large-scale reuse.

## Included code

The repository includes the scripts used to build parts of the dataset:

- `Code For Speech Generation/BSC/edgeTTS.py`: speech synthesis for the BSC pipeline.
- `Code For Speech Generation/BSC/mp3_to_wav.py`: conversion of generated and source audio into WAV format.
- `Code For Speech Generation/BSC/addNoise.py`: noise augmentation and mixing for BSC samples.
- `Code For Speech Generation/SIC/SIC_audio_generation.py`: end-to-end generation script for the SIC subset.

## Not included

ESC data referenced in the paper are not hosted in this repository. Please obtain them from the source described in [arXiv:2510.25054](https://arxiv.org/abs/2510.25054).

## Citation

If you use this repository or the associated paper, please cite:

```bibtex
@misc{xiong2026deaf,
  title         = {DEAF: A Benchmark for Diagnostic Evaluation of Acoustic Faithfulness in Audio Language Models},
  author        = {Jiaqi Xiong and Yunjia Qi and Qi Cao and Yu Zheng and Yutong Zhang and Ziteng Wang and Ruofan Liao and Weisheng Xu and Sichen Liu},
  year          = {2026},
  eprint        = {2603.18048},
  archivePrefix = {arXiv},
  primaryClass  = {cs.AI},
  url           = {https://arxiv.org/abs/2603.18048}
}
```

## License

This dataset is released under the Creative Commons Attribution 4.0 International (CC BY 4.0) license.

Parts of the dataset are generated using text-to-speech (TTS) systems. In addition, environmental noise from the DEMAND dataset is incorporated into the audio samples. Users of this dataset must comply with the original licenses of all third-party resources.

The authors do not claim ownership over third-party components. All such components are redistributed in accordance with their respective licenses and are used for research purposes only.


## Third-Party Data

This dataset incorporates environmental noise from the DEMAND dataset. If you use this dataset, please also cite:

```bibtex
@article{thiemann2013demand,
  title   = {The Diverse Environments Multi-Channel Acoustic Noise Database (DEMAND): A database of multichannel environmental noise recordings},
  author  = {Thiemann, Joachim and Ito, Nobutaka and Vincent, Emmanuel},
  journal = {The Journal of the Acoustical Society of America},
  year    = {2013},
  volume  = {133},
  number  = {5},
  pages   = {3591}
}
```