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A network model of processing in morphology Dick Hudson UCL www.phon.ucl.ac.uk/home/dick/home.htm
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Plan The theoretical framework: Word Grammar A tiny challenge – find a word A small challenge – take account of context A theory of processing A modest challenge – do morphology A fair challenge – plan a word A research strategy
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Word Grammar The whole of language is a network. Links as well as nodes are classified by ‘is-a’ links. Is-a links allow default inheritance. For example, the word CAT
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A tiny challenge How do we work out that a word pronounced /kat/ means ‘Cat’? –I.e. how do we use a network to connect /kat/ to ‘Cat’? An uncontroversial answer: by spreading activation Spreading activation explains: –Priming (e.g. doctor primes nurse) –Speech errors (e.g. doctor replaces nurse)
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From /kat/ to ‘Cat’ Activation spreads blindly from /kat/ via CAT to ‘Cat’ Like this:
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…and back?
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The research questions Q1. Are comprehension and production different processes? Q2. Is lexical processing different from morphology (and syntax and …)? Q3. Exactly how does spreading activation help? Q4. How does context contribute?
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Q4. Context: a small challenge How do we work out that /bat/ means ‘winged mouse’ when we’re thinking of winged mice? The winged-mouse concept is already active, so it becomes more active than ‘cricket-bat’.
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What kind of bat?
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So what? A model of processing must be –Interactive, allowing information to interact freely –NOT modular, limiting flow of information A model of knowledge must be –Integrated, with many links between language and general knowledge contextual knowledge
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Q3. How spreading activation helps Spreading activation is necessary. But not sufficient. Processing also requires: Creation of new nodes. Guidance – provided by the new nodes.
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New nodes for tokens Every token needs a new node because: It’s a distinct concept which we monitor and may remember. It may even be deviant, e.g. mispronounced. So we create a new node for each token. E.g. we hear /kat/ and create X.
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What we know about tokens A token is partially known. E.g. For X we know: X has /k/ /a/ /t/ as its parts. X is-a Y (not known). Y is-a form. The known properties are the source of the processing. They’re highly active because recent.
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What we don’t know about tokens We don’t know some properties. Hearing: we don’t know unobservable properties (meaning, etc). Speaking: we don’t know observables. We want to know some of these properties. So these nodes are also highly active. These properties are the target.
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Activation is guided Therefore activation always spreads from at least two nodes. The source: –already enriched and active. The target: –Needs enrichment. These two nodes guide activation intrinsically. –So we don’t need ‘extrinsic’ control.
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How to get rich. Impoverished nodes need to become rich. How? By ‘marrying’ a rich node. This is ‘binding’: poor node = rich node An active token variable binds to its most active ‘sister’. For example, Y binds to {cat}.
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From /kat/ to {cat}
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The best fit principle An impoverished node binds to its most active sister. NB spreading activation is global, –activation may come from any part of the network This guarantees the best global fit. So context can override form –We recognise as a wrong.
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Inheritance Active token nodes: Bind to the most active sister(s). Inherit from their ‘mother(s)’ So:
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After the wedding ….
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The inheritance!
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An algorithm for processing Add active nodes for tokens. Spread activation. Bind active token variables to constants. Inherit to active tokens. And do it all again.
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So what? Spreading activation has to interact with node-creation –not found in most other models. Processing in a network changes the network nodes –Not just their activity levels
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Selective binding When we hear a word, we look for –its sense –NOT its etymology or its French translation … Unless we’re discussing etymology. Why? Because the ‘sense’ link is usually more active. Why?
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Why not etymology?
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Links between links Every link is-a some more general link. So activation can flow from link to link. So some links start more active than others. So we concentrate processing resources on ‘interesting’ properties.
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Q2. How about morphology (etc)? How do we recognise /kats/? Just the same procedure. But the processor activates two models: –CAT, via /kat/ and {cat} –Plural, via /s/ and {s} This requires multiple default inheritance.
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So what? Complex combinatory patterns can be: inherited. bound. If it works for morphology, maybe it will work for syntax too?
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Q1. Is production the same? Yes. But the target and source are reversed. E.g. –Source: ‘Cat’ –Target: ? (= /kat/) The direction of processing is decided by the choice of target, not by the structure of the system.
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A research strategy How to go beyond hopes, promises and faith? Build a computer model of a processor. Add a database for a linguistic network. See if it works.
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Meet WGNet++
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The team The programmer: Geoff Williams –The consultant: Sean Wallis The linguist: Jasper Holmes The sponsor: ESRC
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Morphology
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Inheritance
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Conclusion Maybe all mental interaction with the world follows the same principles: Spreading activation. Default inheritance. Binding according to the Best Fit principle.
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www.phon.ucl.ac.uk/home/dick/home.htm Thank you
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