With the use of computer-assisted teaching and learning programs the speech therapy of children with dysphasia can be planned more effectively, than with the traditional, so-called prompted-image method employed by logopaedists. Our aim is the creation of a semantic network dictionary - on the basis of a huge quantity empirical database -, which predicts what other concepts will link to a concept in the STM of 4—7 year old children, i.e. what other concepts can the most easily be associated with an already existing one by the therapeut.  Furthermore, the semantic network dictionary will enable the already literate child - on the basis of the idea of András Kocsor - to take a virtual tour through the connected words of the network dictionary by merely saying words into a microphone. Hence the software will help children develop and maintain semantic structures

Bácsi, János

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Bácsi János

University of Szeged

Szeged, 2003 december 10-11 123A Semantic Network Dictionary for Dysphasia TherapyBácsi János bacsi@jgytf.u-szeged.huKeywords: delayed speech development, frequency dictionary, network theories, semantic structure, machine-aided speech therapyThe purpose o f  this project is to compile a network dictionary running on computers to help the conscious planning o f the speech therapy o f 4 -8  year-old-children suffering from expressive language disorder. The children will be able to take a. virtual tour through the connected words o f the network dictionary only by saying words into a microphone, by which the program will help in the development and maintenance o f semantic structures.Our basic psychological assumption, reinforced by our test results, is that a call word that enters the STM (short-term memory) will retrieve about 2-5 concepts from die LTM (long-term memory) and its association with them produces the semantic structure o f the call word.One o f our linguistic achievements is that we have compiled a frequency dictionary based on thirteen primers. It contains 27,293 grapheme sequences o f which 12,226 present content words. The goal o f  die dictionary is to find out which are die words that a six-year-old child are most likely to come across during learning the written language. The empirical database o f the network dictionary will be drawn by asking 5000 children aged 4 -7  to teU us what comes into their minds when they hear the 200 most frequendy used nouns o f the frequency dictionary. W e have done half o f that work so far. The five more frequent associations prompted by die word anya ‘mother,’ which is among the words that have been completely processed, are szeret ‘she loves me’ 1588, szülő ‘parent’ 1501, szeretet ‘love’ (noun) 1127, szeretem ‘I love her’ 875. The number o f die distinct associations prompted by ‘mother’ is 741. We also have a large database o f segmented and annotated recordings o f children’s voice, which contains 250,000 items.The computational task to produce a program for the network dictionary that uses speech recognition has already been accomplished. The other task is to create a network dictionary that demonstrates all o f the possible associations based on the empirical material that has accumulated 400,000 words so far.The expected result makes it predictable what are die most like associations evoked by certain concepts among children aged 4-7, which makes the therapy of delayed speech development plannable using the words that the children have already learnt.

A semantic network dictionary for dysphasia therapy

http://acta.bibl.u-szeged.hu/12744/1/Bacsi_2004_ActaCybernetica.pdf

A semantic network dictionary for dysphasia therapy

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University of Szeged

University of Szeged