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Who Said What? An Automated Approach to Analyzing Speech in Preschool Classrooms
March 7, 2024, 5:43 a.m. | Anchen Sun, Juan J Londono, Batya Elbaum, Luis Estrada, Roberto Jose Lazo, Laura Vitale, Hugo Gonzalez Villasanti, Riccardo Fusaroli, Lynn K Perry, Da
cs.LG updates on arXiv.org arxiv.org
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
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