Transcript Words and Meanings

Words and Meanings
Words and meanings,
are they the same things?
Onomatopoeia
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A type of word that sounds like the thing it is
describing.
English examples:
beep, wow, buzz, pop, bang, mumble, quack
Chinese examples:
噓、哈啾、咕嚕、滴答滴答、叮噹叮噹、批瀝啪啦
English examples:
fl- cluster is often (but of course not always)
associated with rapid movement: flame, flap, flare,
flash, flicker, flurry, flutter
But…
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Cross-language variation in onomatopoeia
DOG
English bow wow French
gnaf gnaf
Albanian ham ham Japanese wan wan
Chinese wang wang Indonesian gong gong
Shakespeare said…
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“A rose by any other name would smell as
sweet.”
Words and meanings are related but
separate entities…
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Translation argument
--meanings for which there are no single words. eg., Yiddish schlep “to
move a heavy and usually bulky item from place to place”
--a word for which we don’t know the meaning. eg., adagio
Imperfect mapping argument
--one word can have more than one meaning (ambiguity)
eg., bug, ring
--one meaning can have more than one word (synonymy)
eg., sofa/couch, pail/bucket
Elasticity argument:
--a word can have different meanings depending on the context in
which it occurs. eg., “strong” coffee, “light” class load
Questions:
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How do words relate to meanings? Is it a one-to-one
relationship?
How are words organized and accessed in our
minds?
How are meanings represented in our minds?
How do children learn the mappings of words and
meanings?
How are two languages (or more) represented in
bilingual minds?
The Study of Words
Questions:
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What is the smallest form in which a word is
stored in our mental lexicon?
What are the most important factors that
influence lexical access and organization?
Word primitives
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“Words” (or lexemes) are primitives.
-- eg., book, books, bookish, bookshelf
-- save processing time but take up more
memory space
“Morphemes” are primitives.
--eg., book, -s, -ish, shelf
--same memory space but take more
processing time
Research method
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Lexical decision task
table
vanue
daughter
tasp
coref
hunter
Reaction time:
How much time it takes to decide whether a given
words is a real word or not.
Evidence supporting “morpheme” as
word primitive
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It takes longer to process multimorphemic words than words
composed of a single morpheme.
(eg., indecision, deciding)
Pseudo-multimorphemic words take longer time to recognize
than real prefixed words or unprefixed words.
(eg., result, interest vs. recall, interchange vs. table)
Speech errors from normal healthy people.
(eg., she washed uped the dishes; the dog bited the cat.)
Aphasic speech
The evidence suggests that…
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People store morphologically complex words
as individual morphemes, which are
combined in speech production, or stripped
in comprehension.
But note…
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Inflectional morphemes and derivational morphemes
may be processed in different ways.
Derivational morphemes are more firmly attached to
root morphemes
Inflectional morphemes are more likely to be added
on as we speak.
Frequently occurring multimorphemic words
(disagree, impossible) often have separate lexical
entries from their root morphemes.
What about compound words?
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Gingerbread, butterfly?
Whether compound words are processed as
one single lexical entry or multiple lexical
entries depend on how transparent the
meanings of composite morphemes are.
Semantically transparent: teaspoon, buttonhole
Semantically opaque: butterfly, mushroom
How do we know?
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Semantic priming task
pea primes beanpole
bread does not prime butterfly
How are words organized and
accessed in our mental lexicon?
Factors influencing word access and
organization
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Frequency
(lexical decision task, naming task)
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Imageability and concreteness and abstractness (recall task)
Semantics (meanings)
(word association, category naming, semantic priming, aphasia)
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Grammatical class
(word association, speech errors, frequency effect for open-class
words but not for close-class words, Broca’s aphasia)
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Phonology
(tip of tongue, speech errors)
What did we learn in the previous class?
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What’s the relationship between words and
meanings?
What questions do we ask about the mental lexicon?
What is the primitive form of word that is represented
in our mental lexicon?
How do we know?
How are words organized in our mental lexicon?
How do we know?
Models of lexical access
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Serial Search Models
Words are searched one at a time.
Parallel Access (or Direct Access) Models
--Perceptual input about a word can activate
a lexical item directly
--Multiple lexical entries are activated in
parallel
Forster’s autonomous search model
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Three access files: orthographic, phonological,
semantic/syntactic
The orthographic and phonological access files mostly contain
information about the beginning parts of words—the first few
letters of their spelling or first few sounds with which they begin.
When an access file directs the search to the appropriate
lexical bin, entries are searched one by one until an exact
match to the perceptual representation is found.
When the relevant lexical entry is retrieved, it is checked
against the input in a post-access check.
Evidence supporting the model:
It takes more time to reject non-words than to accept real words.
Logogen Model (Morton)
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Words are accessed by being activated to a certain threshold.
Each word has its own “logogen” which tabulating the number
of features that a lexical entry shares with a perceptual stimulus.
Each logogen has its individual threshold, which is the amount
of “energy” that will be needed to access that lexical entry.
Any logogen is accessed when the total activation reaches a
pre-designated threshold.
Many types of information are used to access the target word.
If several entries are activated to threshold, the one with the
highest count wins and is “recognized”. It then slowly returns to
its resting level.
This model can account for frequency and priming effects.
There is counter-evidence for the model.
Connectionist Models
(McClelland & Rumelhart)
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The models use the analogy of the brain and neurons to develop
models of cognition.
In the models, lexical access is instituted in “neural nets” composed of
nodes and connections between these nodes.
Nodes are of three types: input, output, and hidden nodes.
Each functional level of the hidden nodes represents different aspects
of words—eg., their visual, orthographic, phonological and semantic
natures, etc.
Connections between layers, and between nodes in the same layer,
can be either excitatory or inhibitory.
The models also emphasize direct access to lexical entries,
simultaneous activation of multiple candidates, and the use of many
types of information to access a target word.
The models can account for frequency and priming effects.
Cohort Model (Marslen-Wilson)
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The model was designed to account only for auditory word
recognition.
When we hear a word, all of its phonological neighbors get
activated. This set of words is known as the “word initial
cohort”.
The list of word candidates is narrowed as the auditory input
proceeds serially.
Initially, the cohort model depended heavily on an exact match
between a spoken word and its phonological representation in
the lexicon. But now the model is revised: the system chooses
the best match to fit an incoming word.
The model can account for frequency and priming effects.
Which model (serial or parallel
processing) accounts for word access
and organization better?
Parallel Processing
Model
The Study of Meanings
When we know the meaning of a word,
what do we know?
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Bachelor
Unmarried male
Is Pope a bachelor?
Eligible, unmarried male
A divorced man?
Despite having a lifelong relationship with
Simone de Beauvoir, Jean-Paul Sartre died a
bachelor?
What does “meaning” mean?
Philosophical theories of meaning
 Reference Theory
--The meaning of a word is the object to which that word refers to in
the real world (that is, its referent)
--Problems: it doesn’t account for words that do not name things (such
as function words), nor does it account for abstract terms such as
“freedom” or unreal objects such as “unicorns”
 Ideational Theory
--Words denote ideas rather than things.
--Problems??
 Alternative Theories
--Words have no meaning independently but are based on their
connection to other words and sentences within the language.
Conceptual primitives
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What are the smallest units of meaning?
Are concepts defined in a rule-like fashion,
with clear conceptual boundaries?
Is it sufficient to represent a concept as a list
of features?
Theories of conceptual structure
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Feature Theories
Knowledge-based Approaches
Feature Theories
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The smallest unit of meaning is feature.
Features can be perceptual (gray, large, tall),
functional (used to transport people),
microstructural (composed of hydrogen and
oxygen molecules), or societal/conventional
(supreme ruler).
The Classical View
The Family Resemblance View
Define “triangle”
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Is a closed figure
Has three sides
Has angles that add up to 180 degrees.
The Classical View
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Any concept has necessary and jointly
sufficient features that all instances of that
concept share. Eg., “triangles”
All triangles are considered to be equally
good triangles.
Concepts are defined in a rule-like fashion,
with clear boundaries.
Define “bird”
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Can fly
Lays eggs
Has feathers
Builds nests
Is small
Has bones
The Family Resemblance View
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For any concept, there are no necessary and sufficient features, but
there are characteristic features — attributes common to many
exemplars of a category.
Instances of a concept may overlap in some traits but not in others,
and they do not share a single set of features.
Some instances of a category or concept are more representative
than others. Categories are said to have a graded structure.
The best example of a concept or category is known as the prototype,
which has the most characteristic features for the category.
People use the prototype of a concept as a reference point to make
category judgements.
Fuzzy boundaries— some instances of one category can overlap
significantly with other categories
An interesting experiment showing
that many categories have a graded
structure…
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Armstrong, Gleitman, and Gleitman (1983)
Task: subjects had to rate category exemplars on a 1 (best) to 7
(worst) scale
Results:
-- apple (1.3), olive (6.5)
-- 13 was a better odd number than was 57!
More task: semantic verification task
Results:
-- subjects were quicker to respond to prototypical items of a category
than to peripheral items.
-- subjects were quicker to respond to “13 is an odd number” than to
“57 is an odd number”!
-- subjects were quicker to respond to “A mother is a female” than to “A
waitress is a female.” !
Conclusions from the study…
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Categories have a graded structure.
People may represent even concepts with
necessary and jointly sufficient features in a
graded way.
Differences between the classical view
and family resemblance view
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The classical view:
--Conceptual boundaries are well defined.
--It is sufficient to represent a concept as a list of features.
The family resemblance view:
--Conceptual boundaries are not well defined (fuzzy boundaries)
--Concepts are graded as to typicality within a category.
--A list of the most characteristic features of a category is
sufficient to represent the meaning of the concept.
Criticism of the Feature Theories
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Features themselves are not well defined.
The choice and weighting of features is
context and task dependent.
We know much more about the intension of a
concept than a list of features suggests.
What does the following things have in
common?
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children, jewelry, portable TV set, photograph
album, manuscripts, oil paintings
Things to take out of the home during a fire.
Knowledge-based Approaches
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Concepts must be represented and organized
according to people’s theories about the world.
Psychological Essentialism (Medin)
People believe that things have underlying essences
that make them what they are.
Psychological Contextualism
Items can be categorized by the context in which
they are found.
Psychological Contextualism
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What do women, fire, dangerous have in
common?
In the Dyirbal language spoken in Australia,
the three words are preceded by the same
marker balan
Knowledge-based Approaches
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What are the smallest units of meaning?
Concepts have relevant features, but these features do not
define the category.
Are concepts defined in a rule-like fashion, with clear
conceptual boundaries?
Concepts are not defined in a rule-like way, with clear
conceptual boundaries. Rather, concepts are constructed as
needed for different contexts or goals.
Is it sufficient to represent a concept as a list of features?
No. Deeper knowledge about conceptual coherence is
necessary to make accurate and adult-level categorizations.
How are concepts organized in
our mental lexicon?
How do we know?
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Semantic verification task
“A robin is a bird.”
“A robin is an animal.”
“An ostrich has feathers.”
“An ostrich has skin.”
Semantic priming task
Models of Semantic Representation
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Hierarchical Network Model
Feature Comparison Model
Spreading Activation Network Model
Hierarchical Network Model
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By Collins and Quillian (1969)
Individual concepts are represented
by nodes that are organized in our
minds like pyramids.
The features would only be stored
at the higher-level concept.
Problems with the model:
-- may only work for taxonomic
categories, but not for more
abstract concepts such as virtue,
good
--can’t explain frequency effects of
features.
--can’t explain typicality effects
Feature Comparison Model
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By Smith, Shoben, Rips (1974)
Concepts are represented as lists
defining features and characteristic
features.
All features are assumed to be
stored under all relevant concepts.
Semantic verification tasks are
performed by comparing the
number of overlapping features of
two or more concepts.
Problems with the model:
--features are not well defined.
--some features correlate more
highly than others.
Spreading Activation Network Model
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By Collins, Collins, Quillian
(1969, 1970)
Concepts are represented
as nodes connected to
related nodes.
When a single concept is
activated, the “electricity”
spreads to connected
concepts.
Closely connected concepts
are activated more quickly
and more strongly than
distantly related concepts.
What about ambiguous words?
How do people process ambiguous
words in context?
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“The men started to drill before they were
ordered to do so.”
“The carpenter ordered the men to drill
before they were ready.”
Selective Access View
Exhaustive Access View
Multiple meanings of an ambiguous
word are activated even when the word
is embedded in a biasing context.
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Swinney (1979): cross-model priming study
Task: subjects listened to sentences containing
ambiguous words and simultaneously participated in
a visual lexical decision task.
Example: “The man was surprised when he found
several spiders, roaches and other bugs in the
corner of his room.”
On the computer screen, subjects saw “ant” “spy”
and “sew”
Dominance is a major factor in early lexical
access; dominant meanings are immediately
activated even when the context is biased
against them.
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Duffy, Morris, Rayner (1988)
Explored the difference between balanced (right) and polarized (yarn)
homographs.
Method: eye tracking
Stimuli:
--biasing context: “The dragon was no longer in pain once the scale
was removed.”
--nonbiasing context: “Once the scale was removed, the dragon was
no longer in pain.”
Results:
--eye gaze was longer to the balanced ambiguous words than to
control words.
--When context was available, eye gaze to the target word was longer
only in the polarized condition.
Time issue in processing
ambiguous words
Simpson and Burgess (1985)
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Stimuli: prime-target pairs
(bank-money, bank-river)
Results:
--16 ms. ISI: only dominant meanings were
facilitated.
--300 ms. ISI: both meanings were equally activated.
--longer ISIs: the dominant meaning appears to
remain active while the less-frequent meaning
subsides.
Conclusions about processing
ambiguous words
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Multiple meanings of a word may be activated in
parallel, with the dominant meaning occurring first.
Context may speed access to several meanings, but
it doesn’t restrict access to all interpretations.
Lexical ambiguity resolution is a dynamic process
with various interpretations racing against each other
for access based on frequency of meaning and
contextual biases.
How do children acquire the mappings
of words and meanings?
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Reference Principle:
The assumption that words map onto a thing or an event.
Whole Object Principle:
Words refer to whole objects, rather than to their parts.
Extendibility Principle:
The assumption that a word refers to a class of objects rather
than a specific object.
Mutual Exclusivity Principle:
Each object can have only one name.
Principle of Contrast:
No two words have exactly the same meaning.