Automatically Learning Measures of Child Language Development
Sam Sahakian, Benjamin Snyder · 2012
We propose a new approach for the creation of child language development metrics. A set of linguistic features is computed on child speech samples and used as input in two age prediction experiments. In the first experiment, we learn a child-specific metric and predicts the ages at which speech samples were produced. We then learn a more general developmental index by applying our method across children, predicting relative temporal orderings of speech samples. In both cases we compare our results with established measures of language development, showing improvements in age prediction performance. 1