Proceedings of the Annual Meeting of the Cognitive Science Society

While naturalistic daylong audio recordings of children’s auditory environments have the potential to reveal key insights about the input children receive and inform our theories of language development, it also presents various methodological hurdles. In the present work, we used three fully transcribed daylong audio recordings to investigate the challenge of manually extrapolating aggregate statistics and quantify the kinds of sampling choices daylong researchers can make. Our findings highlight sampling choices that maximize sampling from the full distribution of the day and potential tradeoffs between human effort and obtaining accuracy.