7-models of word naming
TRANSCRIPT
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Kana
Syllabic script
Sublexical processing
Left hemisphere
Deep dyslexia
Kanji
logographic and
ideographic script
Lexical processing
Right hemisphere
Surface dyslexia
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Ideographic language
2 routes:
1.
Route that associates the symbolwith correct pronunciation
2. One that uses part of the symbol
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1. There are lexical effects for
nonwords and regularity effects for
words.
2. Any model must also be able to
account for the pattern of
dissociations found in acquired
dyslexia.
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1. THREE-ROUTE MODEL (Morton
and Patterson)
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Non-lexical route for assembling
pronunciations from sublexical grapheme-to-
phoneme conversion
The direct route is split into a semantic andnon-semantic direct route.
Surface dyslexia- loss of the direct route
Phonological dyslexia- loss of the indirect
routeDeep dyslexia- remains mysterious
-can only read through the
lexical-semantic route
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Different levels of spelling-
to-sound information
combine in an interactiveactivation network to
determine the final
pronunciation of a word.
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Maintains the
basic
architecture of
the dual routemodel but
makes use of
the cascadingprocess.
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The only direct route is readingthrough the semantics.
How does this model account fornon-semantic reading?
-activation from the sublexicalroute combines (or is summated) with
the activation trickling down from thedamaged direct route to ensure thecorrect pronunciation.
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It is a form of single-route
model that provides an explicit
mechanism for how wepronounce nonwords.
Proposes that we pronouncenonwords and new words by
analogy with other words.
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Example 1.:
gang
activates
hang, rang, sang and bang
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Example 2.:
mave
activatesgave, rave and save
also, it activates its conflicting enemy
haveWhich slows down the pronunciation of mave
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In order to name by analogy, you have to findcandidate words containing appropriateorthographic segments.
Example: mave (-ave)
gave, rave and save
Then, obtain the phonological representationof the segments and assemble the complete
phonology. Example:
gave, rave and save
mave
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First, the models did not make clear how the
input is segmented in an appropriate way.
Second, the models make incorrect
predictions about how nonwords should bepronounced.
Third, it appears to make incorrect
predictions about how long it takes us to
make regularization errors. Finally, it is not clear how analogy models
account for the dissociations found in
acquired dyslexia.
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1. SM MODEL or TRIANGLE MODEL(Seidenberg and McClelland)
Semantic
Orthographic Phonological
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It provides an account of how readers
recognize letter strings as words and
pronounce them.
reading and speech involve three types of
code: orthographic, semantic and
phonological
-connected with feedback connections
There is only one route from orthography to
phonology.
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Semantic
Orthographic Phonological
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3 levels: input, hidden and output
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Weights of connections are learned.This network learns to associate aphonological input with an
orthographic input by being givenrepeated exposure to word-pronunciation pairs.
It learns using an algorithm called
back-propagation.-involves slowly reducing the discrepancy
between the desired and actual outputs of thenetwork by changing the weights ofconnections
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The training corpus comprised all 2987
uninflected monosyllabic words of at least 3
or more letters in English language present in
the Kucera and Francis word corpus.
Each trial consisted of the presentation of a
letter string that was converted into the
appropriate pattern of activation over theorthographic units. This in turn fed forward
to the phonological units by the way of the
hidden units.
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The ease with which a word is learned by the
network, and the effect it has on similar
words, depends to some extent on its
frequency
After training, the network was tested by
presenting letter strings and computing the
orthographic and phonological error scores.
Error score is a measure of the averagedifference between the actual and desired
output of each of the output units across all
pattern.
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Phonological error scores were generated by
applying input to the orthographic units and
measured by the output of the phonological
units. It is interpreted as reflecting
performance on naming task.
Orthographic error scores were generated by
comparing the pattern of activation input to
the orthographic units with the patternproduced through feedback from the hidden
units. It is interpreted as a measure of
reflecting the performance of the model in a
lexical decision task.
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Showed that the model fitted human
data on a wide range of inputs. For
example: regular words such as
gave were pronounced fasterthan exception words like have.
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There is only one set of hidden
units and only one process is used
to name regular, exception and
novel items.
There is no one-to-one
correspondence between hidden
units and lexical items; each wordis represented by a pattern of
activation over the hidden units.
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Lexical memory does not consist ofentries for individual words.Orthographic neighbors do notinfluence the pronunciation of a word
directly at the time of processing;instead regularity effects inpronunciation derive from statisticalregularities in the words of the
training corpus.Lexical processing therefore involves
the activation of information and isnot an all-in-one event.
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Coltheart et al: only showed how skilledreaders read exemption words aloud.
Brener et al: the models performance on
nonwords is impaired from the beginning,its account of surface dyslexia wasproblematic and of phonological dyslexiawas non-existent
Norris: it could not account for the abilityof readers to shift strategically betweenreliance on lexical and sublexicalinformation
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Better information in reading
nonwords and explain the
interaction we observe betweenword consistency and frequency.
This, also provides better
account for dyslexia.
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Patterson, Seidenberg, and McClelland
artificially changed or lesioned the SM
network after the learning phase by
destroying hidden units or connection
weights and then observing the behavior of
the model. Its performance resembled the
reading of a surface dyslexic.
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Patterson et al.: 3 types of lesion
1. Early weights (damage to the connection
between the orthographic input and hidden
units)2. Late weights (damage to the connection
between the hidden units and phonological
input)
3. Damage to the hidden units themselves
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Two consequences:
1. Damage was measured by the
phonological error score
2. Damage was measured by the
reversal rates
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The improvements came about because the
simulations implement both pathways of the
triangle model in order to explain semantic
effects on reading.
People with dementia find exception words
difficult to pronounce and repeat if they
have lost the meaning of words.
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Patterson and Hodges: the integrity of lexicalrepresentations depends on their interactionwith the semantic system: semanticrepresentations bind phonological
representations together with a semanticglue
-semantic glue hypothesis
a semantic system gradually dissolves indementia, so the semantic glue is graduallyreleased and the lexical representations losetheir integrity.
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Patients are therefore forced to rely on a
sublexical or grapheme-phoneme
correspondence reading route leading to
surface dyslexic errors.
Furthermore, they have difficulty in
repeating irregular words for which they
have lost the meaning, but they can repeatlists of words for which the meaning is
intact.
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PMSP showed that a realistic model of
surface dyslexia depends on involving
semantics in reading.
In surface dyslexia, the semantic pathway is
damaged, and the isolated phonological
pathway reveals itself as surface dyslexia.
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Plaut: some patients have substantial
semantic impairments but can read words
accurately
-there are differences in the division oflabor between semantic and phonological
pathways
The revised model takes into account
individual differences between speakers, andshows how small differences in reading
strategies can lead to different consequences
after brain damage.
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Phonological dyslexia arises by impairments
to representations at the phonological level,
rather than to grapheme-phoneme
conversion.
-phonological impairment hypothesis
People with phonological dyslexia can still
read because their weakened phonologicalrepresentations can be accessed through the
semantic level.
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Problem: it is not clear that it would
correctly handle the way in which people
with phonological dyslexia read
pseudohomophones better than other types
of nonwords.
There have also been effects of orthographic
complexity and visual similarity, suggesting
that there is also an orthographic impairmentpresent in phonological dyslexia.
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Howard and Best: Melanie-Jane
gerl
Phocks
There was no effect of visual similarity for
nonwords but Harm and Seidenberg show
that a phonological impairment in a
connectionist model can give rise to sucheffects.
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This model was trained by back-propagation
to associate word pronunciations of a
representation of the meaning of words.
It shows that one type of lesion can give riseto all the symptoms of deep dyslexia
particularly both paralexias and visual errors.
The model was trained to produce an
appropriate output representation given aparticular orthographic input using back-
propagation.
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Lesions resulted in four types of error:
1. Semantic (where an input gave an output
that was semantically but not visually
close to the target)2. Visual (visually but not semantically close
to the target)
3. Mixed (both semantically and visually
close to the target)4. others
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Hinton and Shallice:1. Provides an explicit mechanism whereby
the characteristic can be derived from amodel of normal reading.
2. Shows that the actual site of the lesion isnot primarily important.
3. Shows why symptoms that were previouslyconsidered to be conceptually distinct
necessarily co-occur.4. Revives the importance of syndromes as
neuropsychological concept.
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Plaut & Shallice: the semantic
representations of abstract words contain
fewer semantic features than those of
concrete words; that is the more concrete
the word is, the richer its semantic
representation.
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Simple dual-route model providesan inadequate account of reading,and needs at least an additional
sematic route through imageablesemantics.
Analogy models have someattractive features but theirdetailed workings are vague andthey do not seem able to accountfor all the data.
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Connectionist modelling hasprovided an explicit, single-routethat covers most of the main
findings, but has its problems.It has set the challenge that only
one route is necessary in readingwords and nonwords and thatregularity effects in pronunciationarise out of statistical regularitiesin the words of the language.
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At present, these models are in
relatively early stage of
development, and that it would
be premature to dismiss them
because they cannot yet account
for all the data.
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Thank you!