Книга Cognitive Models of Speech Processing Gerry T. M. Altmann

Cognitive Models of Speech Processing

Автор: Gerry T. M. Altmann
Език: Английски език
Корици: С меки корици
Издател: Taylor & Francis Ltd
Наличност: 50% вероятност
Ще претърсим света
69.85 136.61 лв
This collection of papers and abstracts stems from the third meeting in the series of Sperlonga work...

Информация за книгата

Автор
Език
Английски език
Корици
Книга - С меки корици
Издадена
2018
страници
396
EAN
9781138883116
ISBN
9781138883116
Enbook ID
10059773
Издател
Теглоt
734
Размери
246 x 174 x 27

Пълно описание

This collection of papers and abstracts stems from the third meeting in the series of Sperlonga workshops on Cognitive Models of Speech Processing. It presents current research on the structure and organization of the mental lexicon, and on the processes that access that lexicon. The volume starts with discussion of issues in acquisition and consideration of questions such as, ''What is the relationship between vocabulary growth and the acquisition of syntax?'', and, ''How does prosodic information, concerning the melodies and rhythms of the language, influence the processes of lexical and syntactic acquisition?''. From acquisition, the papers move on to consider the manner in which contemporary models of spoken word recognition and production can map onto neural models of the recognition and production processes. The issue of exactly what is recognised, and when, is dealt with next - the empirical findings suggest that the function of something to which a word refers is accessed with a different time-course to the form of that something. This has considerable implications for the nature, and content, of lexical representations. Equally important are the findings from the studies of disordered lexical processing, and two papers in this volume address the implications of these disorders for models of lexical representation and process (borrowing from both empirical data and computational modelling). The final paper explores whether neural networks can successfully model certain lexical phenomena that have elsewhere been assumed to require rule-based processes.

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