SoapBox Fluency is our reading assessment solution for students of all ages, accents and dialects. It can be used in noisy classroom environments or remotely to accurately assess reading fluency at all stages of the literacy journey.
Independent evaluations of SoapBox Fluency confirm that it delivers over 95% accuracy, a level comparable to that of human assessors.
Computational Linguist Agape Deng shows us how SoapBox Fluency powers accurate and immediate voice-enabled reading assessments for K-12 students, and generates unique data on their individual progress, instruction and intervention needs.
Our voice engine returns the confidence scores with which each word was decoded, as well as the start and end time of each word in the utterance.
If we click on a substitution, for example, our voice engine indicates what word the child said instead, as well as the start and end times of that segment.
Custom Language Models (CLMs) are language models that focus on a specific language domain, as diverse as fairy tales and scientific texts!
SoapBox’s CLMs are trained on kid-centric data to allow them to understand unique words and phrases with exceptional accuracy and ensure the experience of reading remains engaging, educational, and enjoyable for kids.
Voice-enabled reading assessment tools generate an immediate and unique set of valuable data for students, teachers, schools and school districts.
Longitudinally, this data becomes an invaluable benchmarking tool for districts and for edtech companies, who can use it to track the performance of their literacy and language solutions in the market.
Whether you’re building an online, offline or embedded voice experience, the best place to start is our Developer Portal.
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