Access to higher education of students who are deaf is below the national average. Recently, there has been a growing number of applications for the automatic transcription of speech, which claim to make everyday speech more accessible to people who are Deaf or Hard-of-Hearing. However, these systems require a good command of the written language, and a significant proportion of the deaf public has low literacy skills. Moreover, we have very little data on how these audiences actually deal with captions. In this paper, we describe the MANES project, whose long-term goal is to assess the usefulness of captioning for the accessibility of lectures by students who are deaf. We present the first technical results of a real-time system to make course captioning suitable for the target audience.