--- title: "KSAA-2026 Shared Task on Arabic Speech Dictation with" description: "The KSAA-2026 shared task, held at OSACT7, targets a long-standing problem in Arabic NLP: restoring… 3 references, cited by 4 papers here." authors: ["Asma Ali Al Wazrah", "Waad Alshammari", "Rawan Almatham", "Raghad Al-rasheed", "Afrah Abdulaziz Altamimi", "Rufael Marew", "Sawsan Alqahtani", "Hanan Aldarmaki", "Abdullah I. Alharbi", "Abdulrahman Saeed Alshehri", "Mohamed Assar", "Amal Almazrua", "Abdulrahman Alosaimy"] year: 2026 venue: "The 7th Workshop on Open-Source Arabic Corpora and Processing Tools (OSACT7) with 5 Shared Tasks" source: "https://aclanthology.org/2026.osact-1.28/" doi: "10.63317/33hmmyfpg7mx" licence: "CC BY-NC 4.0 (ELRA, LREC proceedings)" licence_url: "https://creativecommons.org/licenses/by-nc/4.0/" summary_licence: "Elamur Cosmic License" canonical: "https://research.elamur.ai/free/en/papers/wazrah-2026-ksaa-2026-shared-task-arabic/" --- [Elamur Research](https://md.research.elamur.ai/free/en/) · [this page in HTML](https://research.elamur.ai/free/en/papers/wazrah-2026-ksaa-2026-shared-task-arabic/) [home](https://md.research.elamur.ai/free/en/) / [papers](https://md.research.elamur.ai/free/en/papers/) / [2026](https://md.research.elamur.ai/free/en/papers/2026/page/4/) / KSAA-2026 Shared Task on Arabic Speech Dictation with Automatic Diacritization # KSAA-2026 Shared Task on Arabic Speech Dictation with Automatic Diacritization **Authors:** [Asma Ali Al Wazrah](https://md.research.elamur.ai/free/en/authors/asma-al-wazrah/), [Waad Alshammari](https://md.research.elamur.ai/free/en/authors/waad-alshammari/), [Rawan Almatham](https://md.research.elamur.ai/free/en/authors/rawan-almatham/), [Raghad Al-rasheed](https://md.research.elamur.ai/free/en/authors/raghad-al-rasheed/), [Afrah Abdulaziz Altamimi](https://md.research.elamur.ai/free/en/authors/afrah-altamimi/), [Rufael Marew](https://md.research.elamur.ai/free/en/authors/rufael-marew/), [Sawsan Alqahtani](https://md.research.elamur.ai/free/en/authors/sawsan-alqahtani/), [Hanan Aldarmaki](https://md.research.elamur.ai/free/en/authors/hanan-aldarmaki/), [Abdullah I. Alharbi](https://md.research.elamur.ai/free/en/authors/abdullah-i-alharbi/), [Abdulrahman Saeed Alshehri](https://md.research.elamur.ai/free/en/authors/abdulrahman-saeed-alshehri/), Mohamed Assar, [Amal Almazrua](https://md.research.elamur.ai/free/en/authors/amal-almazrua/) and [Abdulrahman Alosaimy](https://md.research.elamur.ai/free/en/authors/abdulrahman-alosaimy/) · **Year:** 2026 · **Venue:** [The 7th Workshop on Open-Source Arabic Corpora and Processing Tools (OSACT7) with 5 Shared Tasks](https://md.research.elamur.ai/free/en/venues/osact/) ([Workshop on Open-Source Arabic Corpora and Processing Tools with Shared Tasks 2026](https://md.research.elamur.ai/free/en/venues/osact/2026/)) · **Publisher:** [Association for Computational Linguistics](https://md.research.elamur.ai/free/en/publishers/association-for-computational-linguistics/) · **Licence:** [CC BY-NC 4.0 (ELRA, LREC proceedings)](https://creativecommons.org/licenses/by-nc/4.0/) **Links:** [Publisher's page](https://aclanthology.org/2026.osact-1.28/) · [PDF](https://aclanthology.org/2026.osact-1.28.pdf) · [DOI 10.63317/33hmmyfpg7mx](https://doi.org/10.63317/33hmmyfpg7mx) · [OpenAlex](https://openalex.org/W7166538427) **Citations:** 0 citations (OpenAlex, 2026-10-14) · [4](https://md.research.elamur.ai/free/en/papers/wazrah-2026-ksaa-2026-shared-task-arabic/cited-by/) in our library, of the 149,439 papers whose bibliographies we read ## Summary The KSAA-2026 shared task, held at OSACT7, targets a long-standing problem in Arabic NLP: restoring full diacritics to text that comes from speech. Most written Arabic omits diacritics, which creates lexical and syntactic ambiguity. Text-only diacritizers also miss phonetic and prosodic cues, and ASR systems seldom produce well-diacritized output. The organizers therefore framed diacritization as a multimodal problem, where systems receive both the audio and its undiacritized transcript. The task had two tracks: - **Data contribution:** volunteers recorded and peer-reviewed diacritized prompts on the VoiceWall platform. - **Diacritization modelling:** teams built systems on a roughly 5-hour corpus of MSA and dialectal speech with fully diacritized references. Systems were scored with DER, WER and SER under settings that include or exclude case endings and undiacritized characters. Four of the five submitting teams beat all three baselines. Both speech input and in-domain fine-tuning clearly helped. Case endings and deciding when a character needs no diacritic remained the hardest parts. The task provides a public benchmark for speech-informed Arabic diacritization, with uses in education, accessibility and speech-driven writing tools. ## Key points - **Dataset:** about 5 hours of speech from male and female speakers of nine nationalities (Saudi, Egyptian, Syrian, Algerian and others). Clips last at most 9 seconds and cover politics, economy, sports, religion and news. The train split has 2,327 files (~4.5 h), dev is ~30 min, and the test set (~40 min, hidden) was kept for evaluation. - **Data contribution track:** VoiceWall gathered 2,160 recordings, with 360 prompts assigned to each participant. Quality control combined automatic checks with cross-team review. - **Participation:** 29 teams registered for the diacritization subtask, and 5 submitted valid runs (Thaka, TantaArabNLP, Abjad AI, Eraserhead, Fine-Tashkeel). Their approaches included: - Abjad AI: grouped speech conditioning; - Eraserhead: ASR consistency filtering combined with speaker-adaptive post-processing. - **Baselines:** three Transformer systems. - Text-only, trained on Tashkeela. - Text + ASR, trained on Tashkeela and CartTTS following Shatnawi et al. (2024). - A fine-tuned version of the text + ASR model, which was the strongest baseline: WER 31.84, DER 9.91. - **Results (primary metric):** the primary metric is WER with case endings, including characters without diacritics. Thaka ranked first with WER 23.26 and DER 6.87. The text-only baseline reached a WER of 49.85, showing a large gain from adding speech information. *Our summary of the paper, in our own words — not its text. The work belongs to its authors; read it at the links above.* ## Institutions - [Mohamed bin Zayed University of Artificial Intelligence](https://md.research.elamur.ai/free/en/universities/mohamed-bin-zayed-university-of-artificial-intelligence/) — University, Abu Dhabi, United Arab Emirates · 124 works · 5,676 citations - [Princess Nourah bint Abdulrahman University](https://md.research.elamur.ai/free/en/universities/princess-nourah-bint-abdulrahman-university/) — University, Riyadh, Saudi Arabia · 4 works · 112 citations 📚 Shelves (4): [🖥️ Computer Science](https://md.research.elamur.ai/free/en/shelves/computer-science/) · 16,667 works · [🤖 Artificial Intelligence](https://md.research.elamur.ai/free/en/shelves/computer-science/artificial-intelligence/) · 16,194 works · [🎭 Arts and Humanities](https://md.research.elamur.ai/free/en/shelves/arts-and-humanities/) · 16,039 works · [🗣️ Language and Linguistics](https://md.research.elamur.ai/free/en/shelves/arts-and-humanities/language-and-linguistics/) · 15,891 works 🧭 Topics (2): [Semitic languages](https://md.research.elamur.ai/free/en/topics/semitic-languages/) · 2,908 works · [🎙️ Speech & spoken language](https://md.research.elamur.ai/free/en/topics/speech/) · 480 works ## Cite Cite as: Asma Ali Al Wazrah, Waad Alshammari, Rawan Almatham, Raghad Al-rasheed, Afrah Abdulaziz Altamimi, Rufael Marew, Sawsan Alqahtani, Hanan Aldarmaki, Abdullah I. Alharbi, Abdulrahman Saeed Alshehri, Mohamed Assar, Amal Almazrua and Abdulrahman Alosaimy. 2026. KSAA-2026 Shared Task on Arabic Speech Dictation with Automatic Diacritization. The 7th Workshop on Open-Source Arabic Corpora and Processing Tools (OSACT7) with 5 Shared Tasks. The paper itself, not this page. BibTeX from the library's record of the work. ```bibtex @inproceedings{wazrah2026ksaa, title = {{KSAA-2026 Shared Task on Arabic Speech Dictation with Automatic Diacritization}}, author = {Asma Ali {Al Wazrah}, Waad Alshammari, Rawan Almatham, Raghad Al-rasheed, Afrah Abdulaziz Altamimi, Rufael Marew, Sawsan Alqahtani, Hanan Aldarmaki, Abdullah I. Alharbi, Abdulrahman Saeed Alshehri, Mohamed Assar, Amal Almazrua and Abdulrahman Alosaimy}, booktitle = {The 7th Workshop on Open-Source Arabic Corpora and Processing Tools (OSACT7) with 5 Shared Tasks}, year = {2026}, doi = {10.63317/33hmmyfpg7mx}, url = {https://doi.org/10.63317/33hmmyfpg7mx} } ``` - [← previous Instructional Agents: Reducing Teaching Faculty Workload through Multi-Agent Instructional Design](https://md.research.elamur.ai/free/en/papers/yao-2026-instructional-agents-reducing-teaching-faculty/) - [next → LAD-RAG: Layout-aware Dynamic RAG for Visually-Rich Document Understanding](https://md.research.elamur.ai/free/en/papers/sourati-2026-lad-rag-layout-aware-dynamic/) - [↑ back to papers of 2026](https://md.research.elamur.ai/free/en/papers/2026/page/4/) ## References 3 references, 2 of them with a card of ours. ↗ leads to the work. 1. Alyafeai, Z. and Ahmad, I. (2023). [Ashaar: Automatic analysis and generation of Arabic poetry using deep learning approaches](https://md.research.elamur.ai/free/en/papers/alyafeai-2023-ashaar-automatic-analysis-generation-arabic/). arXiv:2307.06218. doi:10.48550/arXiv.2307.06218. [↗](https://doi.org/10.48550/arxiv.2307.06218) 2. Elgamal, M., Torki, M., and Hussein, A. (2024). [Arabic diacritics in the wild: Exploiting opportunities for improved diacritization](https://md.research.elamur.ai/free/en/papers/elgamal-2024-arabic-diacritics-wild-exploiting-opportunities/). In Proceedings of the 62nd Annual Meeting of the Association for Computational Linguistics (ACL) . 3. Shatnawi, A., Alqahtani, S., and Aldarmaki, H. (2024). Automatic restoration of diacritics for speech data sets. In Proceedings of the 2024 Conference of the North American Chapter of the Association for Computational Linguistics (NAACL) . [↗](https://doi.org/10.48550/arxiv.2311.10771) *Updated 1 November 2026*