Progress monitoring is used to assess a student's performance during the early stages of literacy development. Computerized progress monitoring systems are capable of scoring some progress monitoring measures automatically. However, other measures, such as those involving writing or sign language, are typically scored manually, which is time-consuming and potentially less reliable than computer scoring. In this project, we designed DeepSign, a deep-learning software tool, to auto-score a sign language-based picture-naming measure. DeepSign generates immediate feedback that can enhance progress monitoring and reduce teacher workload.