lexical access: generation & selection

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Lexical Access: Generation & Selection. Today’s Main Topic. Listeners as active participants in comprehension process Model system: word recognition. Outline. Speed & Robustness of Lexical Access Active Search Evidence for Stages of Lexical Access Autonomy & Interaction. Outline. - PowerPoint PPT Presentation

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Lexical Access:Generation & Selection

Today’s Main Topic

• Listeners as active participants in comprehension process

• Model system: word recognition

Outline

1. Speed & Robustness of Lexical Access

2. Active Search

3. Evidence for Stages of Lexical Access

4. Autonomy & Interaction

Outline

1. Speed & Robustness of Lexical Access

2. Active Search

3. Evidence for Stages of Lexical Access

4. Autonomy & Interaction

How do we recognize words?

The mental lexicon

sport figure

sing door carry

turf turtle gold turk turkey

turn

water turbo turquoise

turnip turmoil

How do we recognize words?

• The Simplest Theory

– Take a string of letters/phonemes/syllables, match to word in the mental lexicon

– (That’s roughly how word processors work)

• …is it plausible?

Word Recognition is Fast

• Intuitively immediate - words are recognized before end of word is reached

• Speech shadowing at very brief time-lags, ~250ms (Marslen-Wilson 1973, 1975)

Lexical Access is Robust

• Succeeds in connected speech

• Succeeds in fast speech

• Survives masking effects of morphological affixation and phonological processes

• Deleted or substituted segments

• Speech embedded in noise

But…

• Speed and robustness depends on words in context

sentence --> word context effects

• In isolation, word recognition is slower and a good deal more fragile, susceptible to error

• …but still does not require perfect matching

Questions

• How does lexical access proceed out of context?

• Why is lexical access fast and robust in context?

• When does context affect lexical access?

– does it affect early generation (lookup) processes?

– does it affect later selection processes?

Additional Context Effects

• Word context affects phoneme identification…

word --> phoneme context effects

Phoneme Restoration

• The _eel had a broken axleThe _eel on the orange was hard to cut(Warren 1970)

• Phoneme restoration effects are stronger(i) in words than non-words(ii) later in words(iii) in strongly biasing contexts

Phoneme Monitoring

• press the button as soon as you hear a ‘b’

• “in the yard was a large group of twittering birds”

“cat, dog, horse, rabbit …”

• Monitoring is facilitated by context

Perceptual Boundaries

Perceptual Boundaries

DA TA

Perceptual Boundaries

DASK TASK

(Ganong 1980)

Perceptual Boundaries

DASK TASK

(Ganong 1980)

Perceptual Boundaries

DASH TASH

(Ganong 1980)

Perceptual Boundaries

DASH TASH

(Ganong 1980)

Classic Experimental Paradigms

Accessing the Mental Dictionary

Reaction Time Paradigms

• Lexical Decision

• Priming

Looking for Words

• List 1sicklecathartictorridgregariousoxymoronatrophy

• List 2parabolaperiodontistpreternaturalpariahpersimmonporous

Looking for Words

• List 1sicklecathartictorridgregariousoxymoronatrophy

• List 2parabolaperiodontistpreternaturalpariahpersimmonporous

Speed of look-up reflects organization of dictionary

Looking for Words

+

Looking for Words

DASH

Looking for Words

+

Looking for Words

RASK

Looking for Words

+

Looking for Words

CURLY

Looking for Words

+

Looking for Words

PURCE

Looking for Words

+

Looking for Words

WINDOW

Looking for Words

+

Looking for Words

DULIP

Looking for Words

+

Looking for Words

LURID

1 2 3 4 5 6

Frequency Category (Frequent -- Infrequent)

Behavioral Data: Reaction Time

Categories (n/Million):

1: 7002: 1403: 30 4: 6 5: 1 6: .2

Looking for Words

+

Looking for Words

PRESSULE

Looking for Words

+

Looking for Words

DOCTOR

Looking for Words

+

Looking for Words

NURSE

Looking for Words

• Semantically Related Word Pairsdoctor nursehand fingerspeak talksound volumebook volume

Looking for Words

• In a lexical decision task, responses are faster when a word is preceded by a semantically related word

• DOCTOR primes NURSE

• Implies semantic organization of dictionary

Outline

1. Speed & Robustness of Lexical Access

2. Active Search

3. Evidence for Stages of Lexical Access

4. Autonomy & Interaction

Active Recognition

• System actively seeks matches to input - does not wait for complete match

Cost of Active Search…

• Many inappropriate words activated

• Inappropriate choices must be rejected

• Two Stages of Lexical Accessactivation vs. competitionrecognition vs. selectionproposal vs. disposal

Cohort

S

song

story

sparrow

saunter

slow

secret

sentry

etc.

Cohort

SP

spice

spoke

spare

spin

splendid

spelling

spread

etc.

Cohort

SPI

spit

spigot

spill

spiffy

spinaker

spirit

spin

etc.

Cohort

SPIN

spin

spinach

spinster

spinaker

spindle

Cohort

SPINA spinach

Cohort

SPINA spinach

word uniqueness point

Cohort

SPINAspinach

spinet

spineret

Evidence for Cohort Activation

KAPITEIN KAPITAAL

(Marslen-Wilson, Zwitserlood)

Evidence for Cohort Activation

KAPITEIN KAPITAAL

KAPIT…

(Marslen-Wilson, Zwitserlood)

Evidence for Cohort Activation

KAPITEIN KAPITAAL

KAPIT…

BOOT

GELD

(Marslen-Wilson, Zwitserlood)

Evidence for Cohort Activation

KAPITEIN KAPITAAL

KAPIT…

BOOT

GELD

(Marslen-Wilson, Zwitserlood)

Evidence for Cohort Activation

KAPITEIN KAPITAAL

KAPIT…

BOOT

GELD

KAPITEIN

BOOT

GELD

(Marslen-Wilson, Zwitserlood)

Cohort Model

• Partial words display priming properties of multiple completions: motivates multiple, continuous access

• Marslen-Wilson’s claims

– Activation of candidates is autonomous, based on cohort only

– Selection is non-autonomous, can use contextual info.

• How to capture facilitatory effect of context…

Gating Measures

• Presentation of successive parts of words

– S

– SP

– SPI

– SPIN

– SPINA…

• Average recognition times

– Out of context: 300-350ms

– In context: 200ms(Grosjean 1980, etc.)

Word Monitoring

• Listening to sentences - monitoring for specific words

– Mean RT ~240ms

– Identification estimate ~200ms

• Listening to same words in isolation

– Identification estimate ~300ms

(Brown, Marslen-Wilson, & Tyler)

Cross-Modal Priming

Cross-Modal Priming

The guests drank vodka, sherry and port at the reception

(Swinney 1979, Seidenberg et al. 1979)

Cross-Modal Priming

The guests drank vodka, sherry and port at the reception

WINE

SHIP

(Swinney 1979, Seidenberg et al. 1979)

Cross-Modal Priming

The guests drank vodka, sherry and port at the reception

WINE

SHIP

(Swinney 1979, Seidenberg et al. 1979)

Cross-Modal Priming

The guests drank vodka, sherry and port at the reception

WINE

SHIP

(Swinney 1979, Seidenberg et al. 1979)

Cross-Modal Priming

The guests drank vodka, sherry and port at the reception

WINE

SHIP

(Swinney 1979, Seidenberg et al. 1979)

Cross-modal Priming

• Early: multiple access

• Late: single access

…i.e., delayed effect of context

CMLP - Qualifications

• Multiple access observed– when both meanings have roughly even frequency

– when context favors the lower frequency meaning

• Selective access observed– when strongly dominant meaning is favored by context

(see Simspon 1994 for review)

Why multiple/selective access?

• How could context prevent a non-supported meaning from being accessed at all?

(Note: this is different from the question of how the unsupported meaning is suppressed once activated)

• Possible answer: selective access can only occur in situations where context is so strong that it pre-activates the target word/meaning

Cohort Model

• Partial words display priming properties of multiple completions: motivates multiple, continuous access

• Marslen-Wilson’s claims

– Activation of candidates is autonomous, based on cohort only

– Selection is non-autonomous, can use contextual info.

• How to capture facilitatory effect of context…

Cohort

SPINA spinach

Cohort

SPIN

spin

spinach

spinster

spinaker

spindle

Speed of Integration

• If context can only be used to choose among candidates generated by cohort…

– context can choose among candidates prior to uniqueness point

– but selection must be really quick, in order to confer an advantage over bottom-up information

• Summary of cohort story• Single/multiple access (Simpson)

– Context & dominant/subordinate frequency (Rayner & Frazier)– Types of context (Tabossi)

• Electrophysiological Evidence– M350, distinguishing access from selection/competition– Suggestions about N1, etc.

• Eye-tracking– continuous activation - TRACE– frequency - Dahan et al.

• Priority for category or morphological information, decomposition– Vannest & Boland

Refining the Story

• Frequency in context– eye-tracking in reading

– eye-tracking and object recognition

• Electrophysiological measures of multiple access

• When can context affect generation?– strongly supporting contexts

– ERP evidence

Evidence for Cohort Activation

CAPTAIN CAPTIVE

CAPT…

SHIP

GUARD

CAPTAIN

SHIP

GUARD

(Marslen-Wilson, Zwitserlood)

Frequency in Reading

• Rayner & Frazier (1989): Eye-tracking in reading

– measuring fixation durations in fluent reading

– ambiguous words read more slowly than unambiguous, when frequencies are balanced, and context is unbiased

– unbalanced words: reading profile like unambiguous words

– when prior context biases one meaning• dominant-biased: no slowdown due to ambiguity

• subordinate-biased: slowdown due to ambiguity

• contextual bias can offset the effect of frequency bias

– how can context boost the accessibility of a subordinate meaning?

Frequency in Object Recognition

X

bench

bed

bell

lobster

“Pick up the be..” (Dahan, Magnuson, & Tanenhaus, 2001)

Frequency in Object Recognition

• Timing estimates

– Saccadic eye-movements take 150-180ms to program

– Word recognition times estimated as eye-movement times minus ~200ms

Frequency in Object Recognition

(Dahan, Magnuson, & Tanenhaus, 2001)

Frequency in Object Recognition

(Dahan, Magnuson, & Tanenhaus, 2001)

Frequency in Object Recognition

(Dahan, Magnuson, & Tanenhaus, 2001)

Evidence for Cohort Activation

CAPTAIN CAPTIVE

CAPT…

SHIP

GUARD

CAPTAIN

SHIP

GUARD

(Marslen-Wilson, Zwitserlood)

Matches to other parts of words

• Word-ending matches don’t prime

– honing [honey] bij [bee]woning [apartment]foning [--]

Disagreements

– Continuous activation, not limited to cohort, as in TRACE model (McClelland & Elman, 1986)

– Predicts activation of non-cohort members, e.g. shigarette, bleasant

Non-Cohort Competitors

(Allopenna, Magnuson, & Tanenhaus, 1998)

“Pick up the…”

beaker

beetle (onset)speaker (non-onset)carriage (distractor)

Non-Cohort Competitors

(Allopenna, Magnuson, & Tanenhaus, 1998)

“Pick up the…”

beaker

beetle (onset)speaker (non-onset)carriage (distractor)

Outline

1. Speed & Robustness of Lexical Access

2. Active Search

3. Evidence for Stages of Lexical Access

4. Autonomy & Interaction

M350

(based on research by Alec Marantz, Liina Pylkkänen, Martin Hackl & others)

Lexical access involves

1. Activation of lexical representations• including activation of representations

matching the input, and• lateral inhibition between activated

representations

2. Followed by selection or decision• involving competition among activated

representations that are similar in form

The mental lexicon

sport figure

sing door carry

turf turtle gold turk turkey

turn

water turbo turquoise

turnip turmoil

The mental lexicon

sport figure

sing door carry

turf turtle gold turk turkey

turn

water turbo turquoise

turnip turmoil TURN

Automatic activation

TURN

sport figure

sing door carry

turf turtle gold

turk turkey

water turn

turbo turquoiseturnip turmoil

Lateral inhibition

TURN

sport figure

sing door carry

turf turtle gold

turk turkey

water turn turbo turquoise

turnip turmoil

What is lexical access?

time

leve

l of

activ

atio

n

resting level

TURN

Stimulus: TURN

TURNIP

TURFTURTLE

Activation Competition Selection/Recognition

(e.g. Luce et al. 1990, Norris 1994)

RESPONSE TO A VISUAL WORD Sagittal view

A P

M350

M350

0 200 300 400 Time [msec]

MEG response components elicited by visually presented words in the lexical decision task

RMS analysis of component field patterns.

1 2 3 4 5 6

Frequency Category (Frequent -- Infrequent)

Behavioral Data: Reaction Time

Categories (n/Million):

1: 7002: 1403: 30 4: 6 5: 1 6: .2

1 2 3 4 5 6

Frequency Category (Frequent -- Infrequent)

Latency of m350 Component

Categories (n/Million):

1: 7002: 1403: 30 4: 6 5: 1 6: .2

Neighbors & Competitors

• Phonotactic probability– sound combinations that are likely in English– e.g. ride vs. gush

• Neighborhood density– number of words with similar sounds– ride, bide, sighed, rile, raid, guide, died, tried,

hide, bride, rise, read, road, rhyme, etc.– gush, lush, rush, gut, gull …

RT

Behavioral evidence for dual effects

• Same/different task (“low-level”) RTs to nonwords with a high phonotactic probability are speeded up.

• Lexical decision task (“high-level”)RTs to nonwords with a high phonotactic probability are slowed down!

High probability: MIDE

YUSH RT

RT MIDE

YUSH RT

Low probability:

High probability:

Low probability:

Sublexicalfrequency effect

(Vitevich and Luce 1997,1999)

Competition effect

Stimuli

High probability Low probability

Word BELL, LINE PAGE, DISH

Nonword MIDE, PAKE JIZE, YUSH

• Materials of Vitevich and Luce 1999 converted into orthographic stimuli.

• Four categories of 70 stimuli:

• High and low density words frequency matched.

(Pylkkänen, Stringfellow, Marantz, Brain and Language, in press)

Effect of probability/density (words)

100

200

300

400

500

600

700

M170 M250 M350 RT

HighProbWord LowProbWord

n.s.

n.s.

**

*

(Pylkkänen, Stringfellow, Marantz, Brain and Language, in press)

Effect of probability/density (nonwords)

0

100

200

300

400

500

600

700

800

M170 M250 M350 RT

HighProbNonword LowProbNonword

n.s.n.s.

*

**

(Pylkkänen, Stringfellow, Marantz, Brain and Language, in press)

M350 = 1st component sensitive to lexical factors but not affected by competition

time

leve

l of

activ

atio

n

resting level

TURN

TURNIP

TURFTURTLE

Activation Competition Selection/RecognitionM350

Stimulus: TURN

Outline

1. Speed & Robustness of Lexical Access

2. Active Search

3. Evidence for Stages of Lexical Access

4. Autonomy & Interaction

Autonomy

• “…a system [is] autonomous by being encapsulated, by not having access to facts that other systems know about” (Fodor 1983)

• “Autonomy would imply that processing operations at a given level proceed in the same way irrespective of whatever counsel might be deducible from the higher-level considerations” (Boland & Cutler)

Model Implied So Far

• Stage 1: activation based upon cohortsno effect of context at this stage

• Stage 2:selection affected by context

Boland & Cutler

• The debate over interaction/autonomy in lexical access focuses on the generation (activation) stage

• There is broad agreement that context affects lexical choices once multiple candidates have been generated

Cross-Modal Priming

The guests drank vodka, sherry and port at the reception

WINE

SHIP

(Swinney 1979, Seidenberg et al. 1979)

Cross-Modal Priming

The guests drank vodka, sherry and port at the reception

WINE

SHIP

(Swinney 1979, Seidenberg et al. 1979)

Cross-Modal Priming

• How could context prevent a contextually unsupported meaning from being accessed?

Cross-Modal Priming

• Conflicting results over effect of context on multiple access

• Tabossi (1998)

– The violent hurricane did not damage the ships which were in the port, one of the best equipped along the coast.

– Contexts are highly constraining, prime a specific feature of the target meaning.

Active Comprehension

• Distinction between activation and selection applies equally to syntactic comprehension

• Is active comprehension a fully general property of language understanding?

N400

Negative polarity peaking at around 400 ms central scalp distribution

(Kutas & Federmaier 2000)

(Kutas & Federmaier 2000)

‘baseball’ is not at all plausible here, yet it elicits a smaller N400 - why?

Input to left hem. visual system must have privileged access to information about predictions.

Implications

• If Kutas & Federmaier’s results are robust, this implies that

– lexical priming can cause apparentearly context effects

– this implies ‘very active search’

– hemispheres are not alike in this regard

Conclusion…

• Word recognition is fast and robust because of use of context

• Speed/robustness is achieved by– active generation of candidates from incomplete input

– selection among candidates, based upon context

• Activation ˜ autonomousSelection ˜interactive

Next…

• Syntax

– most issues seen here also apply to syntactic processes

– generation stage is much more complex, since syntactic processing is more than just a lookup/activation process.

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