--- language: - ar license: cc-by-4.0 size_categories: - 100GB+ pretty_name: SADA - Saudi Audio Dataset for Arabic dataset_info: features: - name: audio dtype: audio - name: ProcessedText dtype: string - name: ShowName dtype: string - name: FullFileLength dtype: string - name: SegmentID dtype: string - name: SegmentLength dtype: string - name: SegmentStart dtype: string - name: SegmentEnd dtype: string - name: SpeakerAge dtype: string - name: SpeakerGender dtype: string - name: SpeakerDialect dtype: string - name: Speaker dtype: string - name: Environment dtype: string - name: Category dtype: string splits: - name: train num_bytes: 114821464462.722 num_examples: 6193 download_size: 5889296061 dataset_size: 114821464462.722 configs: - config_name: default data_files: - split: train path: data/train-* --- # Dataset Card for SADA - Saudi Audio Dataset for Arabic ## Dataset Details ### Dataset Description The **SADA** (Saudi Audio Dataset for Arabic) is a comprehensive dataset consisting of audio recordings from over 57 TV shows aired by the Saudi Broadcasting Authority (SBA). The dataset contains approximately 667 hours of audio data with transcripts, the majority of which are in various Saudi dialects (Najdi, Hijazi, Khaliji, etc.). - **Curated by:** The National Center for Artificial Intelligence at the Saudi Data and Artificial Intelligence Authority (SDAIA) in collaboration with SBA. - **Language(s) (NLP):** Arabic (ar) - **License:** CC BY-NC-SA 4.0 - **Number of audio files:** 4563 ### Dataset Sources - **Repository:** Saudi Broadcasting Authority (SBA) ## Uses ### Direct Use The dataset is intended for use in automatic speech recognition (ASR), text-to-speech (TTS) systems, and dialect identification tasks. It provides rich linguistic diversity across various dialects, making it suitable for training and fine-tuning speech models for the Arabic language. ### Out-of-Scope Use The dataset should not be used for commercial purposes or any misuse involving speech or text processing in harmful or inappropriate contexts. ## Dataset Structure ### Features The dataset contains the following features: - **audio**: The audio files in `.wav` format. - **ProcessedText**: The cleaned and pre-processed transcription of the audio segment. - **ShowName**: The name of the TV show from which the audio is sourced. - **FullFileLength**: Duration of the full audio file in seconds. - **SegmentID**: Unique ID for each audio segment. - **SegmentLength**: Length of each segment in seconds. - **SegmentStart/End**: Start and end times of the segment within the full audio. - **SpeakerAge**: Age group of the speaker (e.g., Adult, Child). - **SpeakerGender**: Gender of the speaker (Male, Female). - **SpeakerDialect**: The dialect spoken by the speaker (e.g., Najdi, Hijazi). - **Environment**: The environment in which the audio was recorded (e.g., Clean, Noisy). - **Category**: The genre of the show (e.g., مسابقات, درامي, وثائقي). ## Dataset Creation ### Curation Rationale The dataset was created to provide a comprehensive resource for developing Arabic speech models, specifically targeting the variety of Saudi dialects and their applications in speech recognition and synthesis. ### Source Data #### Data Collection and Processing The data was collected from TV shows aired by the Saudi Broadcasting Authority. The audio files were segmented and transcribed manually, with a focus on ensuring transcription accuracy and uniformity in formatting. #### Who are the source data producers? The original content comes from the Saudi Broadcasting Authority's shows, curated by SDAIA. ### Personal and Sensitive Information The dataset does not contain sensitive personal information, as the focus is on broadcast TV shows with public speakers. ## Bias, Risks, and Limitations Given the focus on Saudi dialects, the dataset may not fully represent other Arabic dialects or languages. Users should be aware that models trained on this dataset may show biases toward Saudi dialects. ## Citation @inproceedings{SADA2023, title={SADA - SBA & SDAIA Audio Dataset for Arabic}, author={Areeb Alowisheq, Abdullah Alrajeh, Sadeen Alharbi, Abdulmajeed Alrowithi, Aljawharah Bin Tamran, Asma Ibrahim, Raghad Aloraini, Raneem Alnajim, Ranya Alkahtani, Renad Almuasaad, Sara Alrasheed, Shaykhah Alsubaie, Yaser Alonaizan}, booktitle={To be published}, affiliation={NCAI-SDAIA}, year={2023} } ## Contact For any inquiries, please contact the National Center for Artificial Intelligence at SDAIA.