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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}
}
``` |