Digital Harf: A Clinically Integrated Multimodal AI System for Pervasive Arabic Speech and Language Therapy
This work addresses the lack of culturally grounded digital therapy tools for Arabic-speaking children with autism, providing a clinically accepted system that can extend therapy into home settings.
Digital Harf is a multimodal AI platform for Arabic speech and language therapy for children with autism, integrating three therapeutic modules and an agentic synthetic data engine to generate culturally relevant content. Expert evaluation with 13 speech-language pathologists showed a 90.1% clinical acceptance rate for generated content.
Children with Autism Spectrum Disorder in Arabic-speaking countries face compounded barriers to effective speech and language therapy: a shortage of qualified specialists, limited service reach beyond urban centers, and a near-total absence of culturally grounded digital therapy materials. We present Digital Harf, a pervasive, multimodal AI platform that extends clinician-led speech and language therapy into the home. The system integrates three therapeutic modules - language therapy, speech intelligibility, and picture description - within a unified workflow that adapts to each child's performance over time. To address the critical shortage of Arabic therapy content, we introduce an Agentic Synthetic Data Engine (ASDE) that automatically generates culturally relevant images, prompts, and language tasks guided by explicit therapeutic and cultural criteria. Expert evaluation with 13 licensed Speech-Language Pathologists yielded a 90.1% clinical acceptance rate for ASDE-generated content without any manual curation or selection, and strong ratings for cultural and linguistic alignment across the full platform. Digital Harf demonstrates that AI-driven therapeutic systems can be built from the ground up for underrepresented linguistic settings, treating cultural grounding as core infrastructure rather than an adaptation afterthought.