Segmentability Differences Between Child-Directed and Adult-Directed Speech: A Systematic Test With an Ecologically Valid Corpus

Author:

Cristia Alejandrina1ORCID,Dupoux Emmanuel123,Ratner Nan Bernstein4,Soderstrom Melanie5

Affiliation:

1. Dept d’Etudes Cognitives, ENS, PSL University, EHESS, CNRS

2. INRIA

3. FAIR Paris

4. Department of Hearing and Speech Sciences, University of Maryland

5. Department of Psychology, University of Manitoba

Abstract

Previous computational modeling suggests it is much easier to segment words from child-directed speech (CDS) than adult-directed speech (ADS). However, this conclusion is based on data collected in the laboratory, with CDS from play sessions and ADS between a parent and an experimenter, which may not be representative of ecologically collected CDS and ADS. Fully naturalistic ADS and CDS collected with a nonintrusive recording device as the child went about her day were analyzed with a diverse set of algorithms. The difference between registers was small compared to differences between algorithms; it reduced when corpora were matched, and it even reversed under some conditions. These results highlight the interest of studying learnability using naturalistic corpora and diverse algorithmic definitions.

Funder

Agence Nationale de la Recherche

FP7 Ideas: European Research Council

Fondation de France

Ecole de Neurosciences de Paris

Region Ile de France

SSHRC

James S. McDonnell Foundation

Publisher

MIT Press - Journals

Subject

Cognitive Neuroscience,Linguistics and Language,Developmental and Educational Psychology,Experimental and Cognitive Psychology

Reference43 articles.

1. Batchelder, E. O. (1997). Computational evidence for the use of frequency information in discovery of the infant’s first lexicon (Unpublished doctoral dissertation). New York: The City University of New York.

2. Bootstrapping the lexicon: A computational model of infant speech segmentation

3. Mommy is only happy! Dutch mothers’ realisation of speech sounds in infant-directed speech expresses emotion, not didactic intent

4. Bernard, M., Thiolliere, R., Saksida, A., Loukatou, G., Larsen, E., Johnson, M. … Cristia, A. (2018). WordSeg: Standardizing unsupervised word form segmentation from text. Preprint. Retrieved from https://osf.io/5qkm3/

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