Award
Portfolio Data
SBIR Phase I: Adaptive Phonetic Analysis for Personalized Dyslexia Reading Support
Award Year: 2025
UEI: M12ZMJTVCBL5
HUBZone Owned: No
Woman Owned: No
Socially and Economically Disadvantaged: No
Congressional District: N/A
Tagged as:
SBIR
Phase I
Awarding Agency
NSF
Total Award Amount: $304,935
Contract Number: 2451062
Agency Tracking Number: 2451062
Solicitation Topic Code: LC
Solicitation Number: NSF 24-579
Abstract
The broader commercial impact of this SBIR Phase I project lies in addressing dyslexia, a condition affecting millions that creates significant educational, economic, and social barriers. Learners with dyslexia often struggle to develop foundational reading skills, leading to disparities in academic achievement and limited opportunities. This project addresses these challenges by developing an innovative, technology-driven solution that enhances decoding ability through customized reading practice. By integrating advanced speech recognition technology with evidence-based teaching methods, the solution provides personalized, scalable, and affordable learning experiences tailored to the needs of dyslexic learners. The technology identifies reading errors with unprecedented granularity, generating adaptive learning content to empower learners to overcome obstacles and build fluency. This initiative has the potential to improve decoding skills for hundreds of thousands of at-risk readers, helping to close educational gaps and create equitable opportunities. Beyond individual benefits, the societal impact includes fostering academic confidence, increasing graduation rates, and enhancing employability, contributing to the well-being of communities. Commercially, this project positions itself as an innovative educational solution, offering tools to help learners and institutions address one of the most pervasive barriers to literacy and lifelong success. This Small Business Innovation Research (SBIR) Phase I project brings reading error identification to an unprecedentedly fine granularity and generates engaging practice contents on an adaptive difficulty level to improve dyslexic readers’ decoding ability. Dyslexia often causes reading errors including insertions, deletions, substitutions in phonemes, which are mostly autocorrected by traditional word-level automatic speech recognition (ASR) technology. Additionally, personalized reading contents for dyslexic readers i
Award Schedule
-
2024
Solicitation Year -
2025
Award Year -
January 21, 2025
Award Start Date -
July 31, 2025
Award End Date
Principal Investigator
Name: Scott Sosso
Phone: 412-877-1177
Email: scott@luca.ai
Business Contact
Name: Scott Sosso
Phone: 412-877-1177
Email: scott@luca.ai
Research Institution
Name: N/A