Towards a hybrid model of speech prosody

Abstract

Speech is conveyed through a richly detailed acoustic signal, and each spoken instance of a word varies. Yet humans recognize words quickly, with few errors and typically with no conscious effort. Linguists hypothesize that abstract categories aid the process of speech comprehension because complex details can be mapped to a category, after which the detail of an instance can be forgotten. At the same time, research shows acoustic detail guides comprehension in real time and is retained in implicit memory. This dissertation addresses language processing for speech prosody. This study consists of five perception experiments that test the representation of pitch accents in memory, and directly compares memory for pitch accents to memory for phonemes. Results show that (1) explicit memory for prosody is more accurate for categorical differences, rather than equivalently large within-category differences, and (2) that, unlike phoneme categories, listeners are able to explicitly remember within-category detail for pitch accents, but that this memory decays quickly. Based on these results, I propose a hybrid model of comprehension of prosody that involves activating both previously proposed abstract categories and gradient detail

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