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---
dataset_info:
features:
- name: audio
dtype: audio
- name: text
dtype: string
- name: cleaned_text
dtype: string
- name: environment_type
dtype: string
- name: speaker_id
dtype: string
- name: speaker_gender
dtype: string
splits:
- name: test
num_bytes: 2702664819.072
num_examples: 3296
download_size: 2564183776
dataset_size: 2702664819.072
configs:
- config_name: default
data_files:
- split: test
path: data/test-*
task_categories:
- automatic-speech-recognition
- text-to-speech
language:
- ar
pretty_name: SCC 2022
size_categories:
- 1K<n<10K
license: cc-by-nc-sa-4.0
---
<center>
<img src="https://cdn-uploads.huggingface.co/production/uploads/6116d0584ef9fdfbf45dc4d9/5g0ERAppFLxQhXU2Haj_X.png"/>
</center>
# Dataset Card for Saudilang Code-Switch Corpus (SCC)
## Dataset Summary
The **Saudilang Code-Switch Corpus (SCC)** is a **5-hour** transcribed audio dataset featuring informal Saudi Arabic speech with **code-switching to English**, sourced from the **"Thmanyah" YouTube podcast**. It was created for evaluating models in multilingual and dialectal speech settings, such as **ASR**, **language identification**, and **code-switch detection**.
## Supported Tasks and Leaderboards
This dataset is suitable for testing models in:
* **Automatic Speech Recognition (ASR)**
* **Text-to-Speech (TTS)**
* **Speaker Diarization**
* **Language Identification**
* **Dialect Detection**
* **Code-Switching Detection**
## Languages
* **Arabic (ar)** – primarily Saudi dialect
* **English (en)** – code-switched within Arabic speech
## Dataset Structure
### Data Fields
* `audio`: The raw audio recording (e.g., `.wav`)
* `text`: The original transcription including both Arabic and English content
* `cleaned_text`: A normalized version of the transcription
* `environment_type`: Acoustic environment in which the speech was recorded (Clean, Music, or Noisy)
* `speaker_id`: An anonymized identifier for the speaker
* `speaker_gender`: Gender of the speaker (all of them are Male)
### Splits
* **Test Set Only**: \~5 hours of annotated, transcribed speech
*(This dataset is designed primarily for evaluation purposes.)*
## Dataset Creation
### Source and Curation
The dataset was curated from naturally occurring podcast conversations and **transcribed by the National Center for Artificial Intelligence at SDAIA**.
### Motivation
Given the scarcity of high-quality Arabic-English code-switching resources, this dataset was developed to address that gap and enable progress in speech technologies for bilingual Arabic users. Publishing SCC demonstrates a commitment to enriching Arabic digital resources and enabling the development of AI models that are more linguistically inclusive and reflective of real-world usage.
## Licensing
This dataset is licensed under the **Creative Commons Attribution-NonCommercial-ShareAlike 4.0 International (CC BY-NC-SA 4.0)** license.
More details: [https://creativecommons.org/licenses/by-nc-sa/4.0/](https://creativecommons.org/licenses/by-nc-sa/4.0/)
## Citation
```
@misc{SCC2025,
title={Saudilang Code-Switch Corpus (SCC)},
author={SDAIA},
year={2022},
howpublished={\url{https://www.kaggle.com/datasets/sdaiancai/saudilang-code-switch-corpus-scc}},
note={CC BY-NC-SA 4.0}
}
```
## Contributions
Dataset curated by **SDAIA**. Dataset card written by the open-source community. |