Measuring prosodic predictability in children's home language environments
- Kyle MacDonald, Speech and NLU Core Technology, McD Tech Labs, Mountain View, California, United States
- Marisa Casillas, Language Development Department, Max Planck Institute for Psycholinguistics, Nijmegen, Netherlands
- Okko Räsänen, Department of Signal Processing and Acoustics, Aalto University, Espoo, Finland
- Anne Warlaumont, Communications, University of California, Los Angeles, Los Angeles, California, United States
AbstractChildren learn language from the speech in their home environment. Recent work shows that more infant-directed speech (IDS) leads to stronger lexical development. But what makes IDS a particularly useful learning signal? Here, we expand on an attention-based account first proposed by Räsänen et al. (2018): that prosodic modifications make IDS less predictable, and thus more interesting. First, we reproduce the critical finding from Räsänen et al.: that lab-recorded IDS pitch is less predictable compared to adult-directed speech (ADS). Next, we show that this result generalizes to the home language environment, finding that IDS in daylong recordings is also less predictable than ADS but that this pattern is much less robust than for IDS recorded in the lab. These results link experimental work on attention and prosodic modifications of IDS to real-world language-learning environments, highlighting some challenges of scaling up analyses of IDS to larger datasets that better capture children’s actual input.
Return to previous page