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license: cc-by-nc-2.0 |
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language: |
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- ar |
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- en |
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tags: |
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- Arabic |
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- English |
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- Broadcast |
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- Code-switching |
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- Punctuation |
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pretty_name: 'QASR: QCRI Aljazeera Speech Resource' |
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--- |
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# QASR: QCRI Aljazeera Speech Resource |
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**QASR** is the largest transcribed Arabic speech corpus with around **2,000 hours** of data. |
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It features **multi-layer annotation**, covering **multiple Arabic dialects** and **code-switching** speech. |
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--- |
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## 📘 Overview |
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QASR is a large-scale transcribed Arabic speech corpus collected from **Aljazeera News Channel** broadcasts. |
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The data is **lightly supervised** and **linguistically segmented**, designed to support a wide range of speech and language processing research tasks. |
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### Key Features |
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- ~2,000 hours of transcribed Arabic speech |
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- Multi-dialect and code-switching coverage |
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- Multi-layer linguistic annotations |
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- Lightly supervised transcriptions |
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- Linguistically motivated segmentation |
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--- |
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## 📄 Lisence |
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Non-Commercial Purpose ONLY! |
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--- |
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## 📥 Download |
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You can request or download the dataset using the link below: |
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👉 **[Download QASR Dataset](https://forms.gle/4U34R3Sy9xcmtuRw8)** |
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Please follow the instructions on the linked page to complete the request process and download the data. |
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--- |
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## 🧠 Applications |
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QASR is suitable for training and evaluating: |
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- **Automatic Speech Recognition (ASR)** systems |
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- **Arabic Dialect Identification** (acoustics- and linguistics-based) |
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- **Punctuation Restoration** |
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- **Speaker Identification** and **Speaker Linking** |
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- **Spoken Language Understanding** and other **NLP modules** for spoken data |
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--- |
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## 📊 Data Source |
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The corpus was **crawled from the Aljazeera news channel**, providing rich diversity in topics, speakers, and dialectal variation. |
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--- |
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## 📄 Citation |
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If you use QASR in your research, please cite: |
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```bibtex |
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@inproceedings{mubarak_qasr_2021, |
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title = {{QASR}: {QCRI} {Aljazeera} {Speech} {Resource}. {A} {Large} {Scale} {Annotated} {Arabic} {Speech} {Corpus}}, |
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booktitle = {{Proc. of ACL}}, |
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author = {Mubarak, Hamdy and Hussein, Amir and Chowdhury, Shammur Absar and Ali, Ahmed}, |
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year = {2021}, |
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} |
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