README.md

---
language:
- zho
- eng
- fra
- jpn
- kor
- rus
- spa
- yue
license: cc-by-nc-sa-4.0
task_categories:
- question-answering
- audio-text-to-text
pretty_name: CCFQA
library_name: datasets
tags:
- factuality
- evaluation
---

# CCFQA
CCFQA is a speech and text factuality evaluation benchmark that measures language models’ ability to answer short, fact-seeking questions and assess their cross-lingual and cross-modal consistency. It consists of speech and text in 8 languages, containing 1,800 n-way parallel sentences and a total of 14,400 speech samples.
- **Language**: Mandarin Chinese, English, French, Japanese, Korean, Russian, Spanish, Cantonese(HK)
- **ISO-3 Code**: cmn, eng, fra, jpn, kor, rus, spa, yue
- **Data Size**: 14,400 sample 
- **Data Split**: Test
- **Data Source**: Native speakers  (6 males and 6 females)
- **Domain**: Factuality Evaluation
- **Task**: Spoken Question Answering(SQA)
- **License**: CC BY-NC-SA-4.0

📄Paper：[https://arxiv.org/abs/2508.07295](https://arxiv.org/abs/2508.07295)

## How to use
```python
from datasets import load_dataset

ccfqa = load_dataset("yxdu/ccfqa")
print(ccfqa)
```

## ⚖️ Evals

please visit [github page](https://github.com/yxduir/ccfqa).


# 🖊Citation

```
@misc{du2025ccfqabenchmarkcrosslingualcrossmodal,
      title={{CCFQA}: A Benchmark for Cross-Lingual and Cross-Modal Speech and Text Factuality Evaluation}, 
      author={Yexing Du and Kaiyuan Liu and Youcheng Pan and Zheng Chu and Bo Yang and Xiaocheng Feng and Ming Liu and Yang Xiang},
      year={2025},
      eprint={2508.07295},
      archivePrefix={arXiv},
      primaryClass={cs.CL},
      url={https://arxiv.org/abs/2508.07295}, 
}
```