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Modeling language discrimination in infants using i-vector representations
Abstract
Experimental research suggests that at birth infants can dis-criminate two languages if they belong to different rhythmicclasses, and by 4 months of age they can discriminate two lan-guages within the same class provided they have been previ-ously exposed to at least one of them. In this paper, we presenta novel application of speech technology tools to model lan-guage discrimination, which may help to understand how in-fants achieve high performance on this task. By combininga Gaussian Mixture Model of the acoustic space and low-dimensional representations of novel utterances with a modelof a habituation paradigm, we show that brief exposure toFrench does not allow to discriminate between two previouslyunheard languages with similar phonological properties, butfacilitates discrimination of two phonologically distant lan-guages. The implications of these findings are discussed.
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