Scopist

Audio transcription is an important task for making content accessible to people who are deaf or hard of hearing. Much of the transcription work is increasingly done by crowd workers, people online who pick up the work as it becomes available often in small bits at a time. Whereas work typically provides a ladder for skill development -- a series of opportunities to acquire new skills that lead to advancement -- crowd transcription work generally does not. To demonstrate how crowd work might create a skill ladder, we created Scopist, a JavaScript application for learning an efficient text-entry method known as stenotype while doing audio transcription tasks. Scopist facilitates on-the-job learning to prepare crowd workers for remote, real-time captioning by supporting both touch-typing and chording. Real-time captioning is a difficult skill to master but is important for making live events accessible. We conducted 3 crowd studies of Scopist focusing on Scopist's performance and support for learning. We show that Scopist can distinguish touch-typing from stenotyping with 94% accuracy. Our research demonstrates a new way for workers on crowd platforms to align their work and skill development with the accessibility domain while they work.