title: Statistical properties of infant-directed versus adult-directed speech: insights from speech recognition.
abstract: Previous studies have shown that infant-directed speech ('motherese') exhibits overemphasized acoustic properties which may facilitate the acquisition of phonetic categories by infant learners. It has been suggested that the use of infant-directed data for training automatic speech recognition systems might also enhance the automatic learning and discrimination of phonetic categories. This study investigates the properties of infant-directed vs. adult-directed speech from the point of view of the statistical pattern recognition paradigm underlying automatic speech recognition. Isolated-word speech recognizers were trained on adult-directed vs. infant-directed data sets and were tested on both matched and mismatched data. Results show that recognizers trained on infant-directed speech did not always exhibit better recognition performance; however, their relative loss in performance on mismatched data was significantly less severe than that of recognizers trained on adult-directed speech and presented with infant-directed test data. An analysis of the statistical distributions of a subset of phonetic classes in both data sets showed that this pattern is caused by larger class overlaps in infant-directed speech. This finding has implications for both automatic speech recognition and theories of infant speech perception.
authors.affiliation: Department of Electrical Engineering, Box 352500, University of Washington, Seattle, Washington 98195, USA. katrin@ee.washington.edu
authors.forename: Katrin
authors.initials: K
authors.lastname: Kirchhoff
authors.forename: Steven
authors.initials: S
authors.lastname: Schimmel
mesh_terms: D000328:Adult; D002648:Child; D016002:Discriminant Analysis; D005260:Female; D006801:Humans; D007223:Infant; D007804:Language Development; D016014:Linear Models; D015233:Models, Statistical; D009034:Mother-Child Relations; D010700:Phonetics; D013068:Speech Production Measurement; D049250:Speech Recognition Software; D014705:Verbal Behavior