Quantifying Talker Variability in North-American Infants' Daily Input.

Journal Article (Journal Article)

Words sound slightly different each time they are said, both by the same talker and across talkers. Rather than hurting learning, lab studies suggest that talker variability helps infants learn similar sounding words. However, very little is known about how much variability infants hear within a single talker or across talkers in naturalistic input. Here, we quantified these types of talker variability for highly frequent words spoken to 44 infants, from naturalistic recordings sampled longitudinally over a year of life (from 6 to 17 months). We used non-contrastive acoustic measurements (e.g., mean pitch, duration, harmonics-to-noise ratio) and holistic measures of sound similarity (normalized acoustic distance) to quantify acoustic variability. We find three key results. First, pitch-based variability was generally lower for infants' top talkers than across their other talkers, but overall acoustic distance is higher for tokens from the top talker versus the others. Second, the amount of acoustic variability infants heard could not be predicted from, and thus was not redundant with, other properties of the input such as the number of talkers or tokens, or proportion of speech from particular sources (e.g., women, children, electronics). Finally, we find that patterns of pitch-based acoustic variability heard in naturalistic input were similar to those found with in-lab stimuli that facilitated word learning. This large-scale quantification of talker variability in infants' everyday input sets the stage for linking naturally occurring variability "in the wild" to early word learning.

Full Text

Duke Authors

Cited Authors

  • Bulgarelli, F; Mielke, J; Bergelson, E

Published Date

  • January 2021

Published In

Volume / Issue

  • 46 / 1

Start / End Page

  • e13075 -

PubMed ID

  • 34971003

Electronic International Standard Serial Number (EISSN)

  • 1551-6709

International Standard Serial Number (ISSN)

  • 0364-0213

Digital Object Identifier (DOI)

  • 10.1111/cogs.13075

Language

  • eng