The research reported in this thesis examines issues of word recognition in human speech perception. The main aim of the research is to assess the effect of regular variation in speech on lexical access. In particular, the effect of a type of neutralising phonological variation, assimilation of place of articulation, is examined. This variation occurs regressively across word boundaries in connected speech, altering the sUlface phonetic form of the underlying words. Two methods of investigation are used to explore this issue. Firstly, experiments using cross-modal priming and phoneme monitOling techniques are used to examine the effect of variation on the matching process between speech input and lexical form. Secondly, simulated experiments are performed using two computational models of speech recognition: TRACE (McClelland & Elman, 1986) and a simple recun-ent network. The priming experiments show that the mismatching effects of a phonological change on the word-recognition process depend on their viability, as defmed by phonological constraints. This implies that speech perception involves a process of contextdependent inference, that recovers the abstract underlying representation of speech. Simulations of these and other experiments are then reported using a simple recurrent network model of speech perception. The model accommodates the results of the priming studies and predicts that similar phonological context effects will occur in nonwords. Two phoneme monitOling studies support this prediction, but also show interaction between lexical status and viability, implying that phonological inference relies on both lexical and phonological constraints. A revision of the network model is proposed which leams the mapping from the surface form of speech to semantic and phonological representations.
| Identifer | oai:union.ndltd.org:bl.uk/oai:ethos.bl.uk:361055 |
| Date | January 1994 |
| Creators | Gaskell, Mark Gareth |
| Publisher | Birkbeck (University of London) |
| Source Sets | Ethos UK |
| Detected Language | English |
| Type | Electronic Thesis or Dissertation |
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