---
license: cc-by-nc-2.0
language:
- ar
- en
tags:
- Arabic
- English
- Broadcast
- Code-switching
- Punctuation
pretty_name: 'QASR: QCRI Aljazeera Speech Resource'
---
# QASR: QCRI Aljazeera Speech Resource

**QASR** is the largest transcribed Arabic speech corpus with around **2,000 hours** of data.  
It features **multi-layer annotation**, covering **multiple Arabic dialects** and **code-switching** speech.

---

## 📘 Overview

QASR is a large-scale transcribed Arabic speech corpus collected from **Aljazeera News Channel** broadcasts.  
The data is **lightly supervised** and **linguistically segmented**, designed to support a wide range of speech and language processing research tasks.

### Key Features
- ~2,000 hours of transcribed Arabic speech  
- Multi-dialect and code-switching coverage  
- Multi-layer linguistic annotations  
- Lightly supervised transcriptions  
- Linguistically motivated segmentation  

---
## 📄 Lisence

Non-Commercial Purpose ONLY!

---

## 📥 Download

You can request or download the dataset using the link below:

👉 **[Download QASR Dataset](https://forms.gle/4U34R3Sy9xcmtuRw8)**  

Please follow the instructions on the linked page to complete the request process and download the data.

---

## 🧠 Applications

QASR is suitable for training and evaluating:

- **Automatic Speech Recognition (ASR)** systems  
- **Arabic Dialect Identification** (acoustics- and linguistics-based)  
- **Punctuation Restoration**  
- **Speaker Identification** and **Speaker Linking**  
- **Spoken Language Understanding** and other **NLP modules** for spoken data  

---

## 📊 Data Source

The corpus was **crawled from the Aljazeera news channel**, providing rich diversity in topics, speakers, and dialectal variation.

---

## 📄 Citation

If you use QASR in your research, please cite:

```bibtex
@inproceedings{mubarak_qasr_2021,
  title     = {{QASR}: {QCRI} {Aljazeera} {Speech} {Resource}. {A} {Large} {Scale} {Annotated} {Arabic} {Speech} {Corpus}},
  booktitle = {{Proc. of ACL}},
  author    = {Mubarak, Hamdy and Hussein, Amir and Chowdhury, Shammur Absar and Ali, Ahmed},
  year      = {2021},
}