This paper presents the KSAA-2026 Shared Task on Arabic Speech Dictation with Automatic Diacritization, addressing a persistent challenge in Arabic NLP. The task focuses on transforming speech transcripts into fully diacritized Arabic text by leveraging both the speech signal and its undiacritized transcript. Unlike conventional ASR tasks that focus on transcription, this task integrates acoustic and textual information to improve diacritization accuracy. The shared task consists of two subtasks: (1) Data Contribution, where participants recorded and reviewed speech data through the VoiceWall platform, resulting in 2,160 recordings, and (2) Diacritization, where 5 teams developed systems that generate fully diacritized text from speech and undiacritized transcripts. The dataset includes approximately 5 hours of Modern Standard Arabic (MSA) and multi-dialectal speech with fully diacritized references. Experimental results show that several participant systems outperform the provided baselines, and that incorporating speech information and fine-tuning improves performance compared to text-only approaches. KSAA-2026 shared task establishes a benchmark for multimodal Arabic diacritization and supports the development of robust systems for applications in education, accessibility, and speech-driven text generation.

This paper provides an overview of Contemporary Arabic Lexicon (Mu’jam Arriyadh). It is a contemporary and inclusive Arabic dictionary that has been specifically developed to cater to the needs of both native and non-native Arabic speakers. The corpus utilized in this study is derived from the Arabic Contemporary Corpus for Analysis (ACCA), which encompasses a vast collection of 450 million words of Modern Standard Arabic spanning the previous century. Significantly, the lexicon in question prioritizes lemma-based entries over root forms, hence enhancing its user-friendliness and adaptability across different contexts. The resource offers comprehensive linguistic data pertaining to a wide array of Arabic vocabulary, encompassing morphological, morph-syntactic, and semantic aspects. The Lexicon has been developed in accordance with the ISO 24613 standard, which improves its ability to be processed by machines and facilitates the utilization of natural language processing systems. The database encompasses a range of linguistic aspects, such as synonyms, antonyms, and root forms, offering a comprehensive compilation. Mu’jam Arriyadh is a contemporary Arabic lexicon that is designed to be accessible to users, compatible with machine processing, and highly beneficial for anyone studying the language, conducting research, and utilizing natural language processing technologies.