Speech Accessibility Project Challenge 2

With the rise of multimodal AI systems and real-time conversational agents, speech is emerging as a natural entry point to modern AI, where ASR latency and accuracy critically determine usability. Yet a substantial accessibility gap persists: as of late 2024, offline ASR achieved 1.4\% WER on non-disabled speech but 17.8\% on dysarthric speech. The first Speech Accessibility Project Challenge (SAPC1, Interspeech 2025) cut the latter to 8.1\% within six months, but this progress has not transferred to streaming ASR, where systems face stricter latency and compute constraints. Building on the expanded scope of the Speech Accessibility Project (SAP)—now covering Parkinson's disease, cerebral palsy, Down syndrome, ALS, and stroke—we propose SAPC2 to advance speech recognition for all speech abilities under realistic deployment constraints. SAPC2 introduces, to the best of our knowledge, three firsts in this area: the largest free-use dysarthric speech corpus (850 hours from 999 speakers, currently available to 117 organizations under the SAP data use agreement), the first streaming track for dysarthric ASR, and the first open-source PyTorch toolkit for real-time ASR latency evaluation. Launched on March 1, 2026, SAPC2 has already drawn 40 registered teams, with data distributed to 25 by mid-May. A \$10,000 prize pool for Pareto-frontier submissions across accuracy and latency further incentivizes high-quality entries, advancing inclusive, real-time conversational AI for users with diverse speech patterns.