Who Said What? An Automated Approach to Analyzing Speech in Preschool Classrooms

arXiv:2401.07342v2 Announce Type: replace-cross
Abstract: Young children spend substantial portions of their waking hours in noisy preschool classrooms. In these environments, children's vocal interactions with teachers are critical contributors to their language outcomes, but manually transcribing these interactions is prohibitive. Using audio from child- and teacher-worn recorders, we propose an automated framework that uses open source software both to classify speakers (ALICE) and to transcribe their utterances (Whisper). We compare results from our framework to those from a human expert …

abstract arxiv audio automated child children contributors cs.lg eess.as environments interactions language preschool speech spend teachers type young