Computational language acquisition by statistical bottom-up processing

Statistical learning of patterns from perceptual input is an increasingly central topic in cognitive processing including human language acquisition. We present an unsupervised computational method for statistical word learning by analysis of transitional probabilities of subsequent phone pairs. Results indicate that word differentiation is possible with this type of approach and are in line with previous behavioral findings. Index Terms: computational language acquisition, speech segmentation, speech clustering, statistical learning

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