Enhancing learning accessibility through fully automatic captioning

Abstract

The simple act of listening or of taking notes while attending a lesson may represent an insuperable burden for millions of people with some form of disabilities (e.g., hearing impaired, dyslexic and ESL students). In this paper, we propose an architecture that aims at automatically creating captions for video lessons by exploiting advances in speech recognition technologies. Our approach couples the usage of off-the-shelf ASR (Automatic Speech Recognition) software with a novel caption alignment mechanism that smartly introduces unique audio markups into the audio stream before giving it to the ASR and transforms the plain transcript produced by the ASR into a timecoded transcript.

Cite this work

No public copy is stored for this record, so only the metadata is cited.

Stored only when both papers are in the corpus — 47 citations exist upstream.

Papers that cite the same references — the relational fallback while embeddings are still backfilling.