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This doctoral dissertation investigated the learning of auditory categories by applying insights from child language learning, visual category learning and phonetic categorization by adults. The experiments in chapter 2 concern supervised learning of multidimensional non-speech categories varying in two dimensions: duration and a non speech analogue of formant frequency. In experiment 1, one dimension of variation determined category membership, variation in the other dimension was irrelevant. Listeners quickly learned to categorize according to this distinction. In experiment 2, both dimensions needed to be combined to categorize correctly. Performance was much lower, but most listeners succeeded in this task. However, in a maintenance phase without feedback or distributional information, listeners reverted to a unidimensional solution. In a maintenance phase with distributional information, listeners did use both dimensions correctly, arguing for the importance of distributional information in (auditory) category acquisition. In chapter 3, the listeners had to classify the same categories, but without feedback. In experiment 1, listeners succeeded to discover the relevant dimension of variation (and ignore the irrelevant one) without feedback. Much of this learning was lost in the maintenance phase, especially for the dimension formant frequency. With two relevant dimensions (Experiment 2), listeners were not able to learn to use both dimensions and reverted to a unidimensional solution. Chapter 4 applied the paradigms of chapter 2 and 3 to the learning of speech categories. Spanish native listeners learned Dutch vowel contrast with one relevant dimension of variation. With feedback, learning was swift, although was not well maintained without feedback or distributional information. Without feedback, Spanish listeners reverted to the dimensions best known in their native phonology, formant frequency, even when distributional information pointed to duration. The results are discussed in chapter 5. The implications for models of speech acquisition are discussed.
