1 code-switching in a network richard hudson bangor february 2008
TRANSCRIPT
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Code-switching in a network
Richard Hudson
Bangor February 2008
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Linguists and psycholinguists
linguists psycho-linguists
Different worlds, no
shared models
We need a bridge.
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Lingualism
• Monolingualism– even monolinguals know about other
languages
• Bilingualism• Multilingualism
– World record for societal multilingualism =
• Hyperpolyglottism– World record for individual multilingualism =
?
?
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72?
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Theory
• How do monolinguals record knowledge about languages?– e.g. ‘Latin is dead’
• How do linguals keep their languages separate?– e.g. ‘Dog is English, ci is Welsh’
• How do these facts relate to language-structure?
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Languages in the mind
• Each named language is a concept.
• It’s part of general knowledge.
• General knowledge is a network of concepts.
• So each named language is a node.
• And its properties are links to other nodes.
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‘Latin is dead’
Latin
languagespoken by
community
0‘isa’
exception
default
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Word Grammar
• Language competence is a network too.– not a network of lexical items or constructions– nodes have no internal structure.
• It’s just our (ordinary) knowledge of words.
• So (1) it has no boundary.
• So (2) activation spreads freely between language and non-language.
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Spreading activation
• Language must be a network because it carries spreading activation.
• Evidence:– Priming: word 1 primes word 2 if they are
network neighbours.– Speech errors: the substituted word is
activated by accident from the target or context.
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A priming experiment
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On the screen: no priming
WordNon-word
lorryfonnurse
Delay: 0.90.80.8
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Nurse primes doctor.
WordNon-word
doctorfonnurse
Delay: 0.90.80.6
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nurse
doctor
lorry
Why?
nurse
doctor
lorry
nurse
doctor
lorry
nurse
doctor
lorry
nurse
doctor
lorry
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Priming at all levels
Words prime network neighbours in:• Phonology: verse primes nurse (but only
briefly)• Morphology: hedges primes hedge for longer
than pledge does.• Syntax: Vlad brought a book to Boris primes
other V + DO + PP sentences• Semantics: nurse primes doctor.
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How activation spreads
• Blindly – hence errors.
• In any direction, depending on the target.– Speaking or listening or analysing or …
• Randomly, so weak activation has a weak effect (rather than no effect)– because activation converges from many
directions.
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No boundaries
• Activation flows freely between language and non-language
• Even speech errors may have non-linguistic causes– E.g. (By a computer) Do you have a
• Choice of language is another example.
computer?screwdriver?
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Languages in a network
• Each word has (‘belongs to’) a language.
• Each language has a prototypical ‘word’.
• Prototypical words are the domain of phonology.
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Welsh and English
Welsh English
language
Welsh-word English-word
language language
ci diolch dog thanks
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A language isn’t a box.
Welsh English
ci diolch dog thanks
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Pro network, con boxes
• Translation equivalents in different languages prime one another.– e.g. ci primes dog.
• So they must share meaning.
• Likewise for phonological or graphological priming.– e.g. ci primes key or cipher.
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Cross-language links in a network
ci dog
Welsh-word English-wordnoun
keymeaning
meaning /ki:/
sound
sound
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Moreover, L1 and L2 are unequal
• Often, L2 was learned via L1– e.g. ‘Ci means dog’
• So some L2 words are linked directly to L1 words by a ‘translation’ relation, but not vice versa.
• This explains why L2 > L1 translation is faster and easier than L1 > L2 (Kroll & Dussias 2004).
• But in time L2 becomes independent of L1.
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The asymmetry of L1 and L2
ci dog
L2-word L1-word
translation
meaning
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Language choice
• Activation from meaning activates words in both languages.
• So how does a bilingual stick to one language when ‘in monolingual mode’?
• Two suggestions so far (Costa 2004): Non-target language activation is:– inhibited.– ignored.
• Both assume an external controller.
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Code-switching with external control
ci dog
Welsh-word English-word
meaning
meaning/ki:/
sound
/dg/
sound
winner?
suppress or ignore
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External control?
• Who is the external controller?– a ‘homunculus’?– problem: infinite regress.
• What does ‘he’ control?– just language use?
• If possible, avoid special external controls.
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Code-switching with internal control
ci dog
Welsh-word English-word
meaning
meaning/ki:/
sound
/dg/
sound
winner?
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Two kinds of code-switching
• Situational or intra-sentential.
• Bilingual speakers can stick to one language when the situation requires it– e.g. when speaking to a monolingual
• How do they do it?
• The situation keeps the ‘required language’ node active.
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Speaking to a Welsh speaker
Welsh English
language
Welsh-word English-word
language-of language-of
ci dog
spoken by
Welsh speakers
current interaction
•
addressee
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Intra-sentential code-mixing
• Used only when speaking to bilinguals.
• Bilinguals belong to both communities.
• So the situation activates both languages.
• e.g. (Eppler 2004)– und heuer fahren wir nach Harrogate for a
long-es weekend – die do-'nt mind aber I do .
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Speaking to a Welsh-English bilingual
Welsh English
Welsh-word English-word
language-of language-of
ci dog
spoken by
Welsh speakers
current interaction
•
addressee
English speakers
spoken by
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Random choice
• Suppose each language is equally active.
• So for each word each language is equally likely:– like tossing a coin, where each toss is
independent of the previous one:– A A B A B B A A A B B A B B
• But that’s not how code-mixing works.
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Inertia prevails
• Words tend strongly to be in the same language if they are:– adjacent or– linked by a syntactic dependency.
• Why does adjacency matter? – the previous language is still most active
• Why does dependency matter?– the dependency link carries activation.
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Why does the language tend to stay the same?
Lang A Lang B
word 1 word 2 word 3
language
dependent or head
a concept
meaning
? ?
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Conclusion
• Language choice is governed by activation of:– a ‘required language’ node to match the
addressee’s social category– the previous word– a syntactically related word
• Language is integrated into the network of general knowledge.
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The bridge is growing
linguistics psycho-linguistics
Computer model with numbers
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Diolch yn fawr
• For this slide show:www.phon.ucl.ac.uk/home/dick/talks.htm#bangor
• For more about hyperpolyglots etc:…dick/polyglotism/home.htm
• For more about Word Grammar:…dick/wg.htm