Lexical Access: Generation & Selection Main Topic Listeners as active participants in comprehension process Model system: word recognition

Lexical Access:Generation & Selection

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


2. Active Search



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

• Eye-tracking studies indicate effects of access within 200-300ms

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

Marslen-Wilson 1975

Speech shadowing involves on-line repetition of a speaker…Speech shadowing involves on-line repetition of a speaker…

Shadowing latency

250-1000ms

The new peace terms have been announced…

They call for the unconditional surrender of …universe of …already of …

normalsemanticsyntactic

Marslen-Wilson 1975

“If the interaction between higher and lower levels of of analysis takes place only after the initial phonetic and lexical identification of the word, then restoration of disrupted words should be equally frequent in all Context conditions. The shadower would have no basis, in his initial repetition, for rejecting contextually anomalous restorations. However, if immediate identification does interact on-line with the semantic and syntactic context, then it becomes possible for context variables to determine word restoration frequency.” (Marslen-Wilson, 1975, p. 226)

“The high incidence of WR errors in Normal2 illustrates the speed and the precision with which structural information can be utilized. If the first syllable indicates a word that matches the context, then the close shadower can immediately start to restore that word in his repetition. This implies, first, that the constraints derived from the preceding items of the string are available to guide the analysis of even the first syllable of the target word. Second, these constraints can specify the permissible form-class and meaning of the target word with sufficient precision to enable the shadower to assess the appropriateness of just its first syllable.” (Marslen-Wilson 1975, p. 227).

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?

Classic Experimental Paradigms

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

(Embick et al., 2001)

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


2. Active Search



Active Recognition

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

This allows for speed, but …

Cost of Active Search…

• Many inappropriate words activated

• Inappropriate choices must be rejected

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

The mental lexicon

sport figure

sing door carry


turn


turnip turmoil

The mental lexicon

sport figure

sing door carry


turn


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)

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

Cross-Modal Priming

Evidence for Cohort Activation

KAPITEIN KAPITAAL

(Marslen-Wilson, Zwitserlood)


KAPITEIN KAPITAAL

KAPIT…



KAPITEIN KAPITAAL

KAPIT…

BOOT

GELD



KAPITEIN KAPITAAL

KAPIT…

BOOT

GELD



KAPITEIN KAPITAAL

KAPIT…

BOOT

GELD

KAPITEIN

BOOT

GELD



CAPTAIN CAPTIVE

CAPT…

SHIP

GUARD

CAPTAIN

SHIP

GUARD


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, then, 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

The guests drank vodka, sherry and port at the reception

(Swinney 1979, Seidenberg et al. 1979)

Cross-Modal Priming


WINE

SHIP


Cross-Modal Priming


WINE

SHIP


Cross-Modal Priming


WINE

SHIP


Cross-Modal Priming


WINE

SHIP


Generation and Selection

• Investigating the dependence on ‘bottom-up’ information in language understanding

• ‘Active’ comprehension has benefits and costs

– Speed

– Errors

– Overgeneration entails selection

• Sources of information for generating candidates

– Bottom-up information (e.g., lexical cohorts)

– ‘Top-down’ information (e.g., sentential context)

– Questions about whether context aids generation or selection

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)

• Context vs. frequency

– The guests drank wine, sherry, and port at the reception.

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

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?

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

– [… or recognition following uniqueness point must be slow in the absence of context.]

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

Tanenhaus & Lucas 1987

Cross-Modal Lexical Access

• Seidenberg, Tanenhaus, Leiman, & Bienkowski (1982)

– Cross-modal naming

– They all rose vs. They bought a rose Probes: FLOWER, STOOD

– Immediate presentation: equal priming; 200ms delay: selective priming

• Prather & Swinney (1977): similar w/ cross-modal lexical decision

• Tanenhaus & Donnenworth-Nolan (1984): similar, w/ extra delay in presenting target word

Experiment 1

Experiment 1

Experiment 2

cost no cost

Summary so far

• Accounting for single vs. multiple access findings in context

• How to relate context to lexical retrieval processes

• (Non-)effects of syntactic category constraints

Electrophysiology of Sentence Comprehension

• Semantic anomaly

N400

I drink my coffee with cream and sugarI drink my coffee with cream and socks

Kutas & Hillyard (1980)

N400

he mowshe *mow

P600

Left Anterior Negativity (LAN)

Electrophysiology of Sentence Comprehension

N400

Negative polarity peaking at around 400 ms central scalp distribution

Kutas & Federmeier, 2000, TICS

and priming

The day was breezy so the boy went out to fly …

deLong, Urbach, & Kutas, 2005, Nature Neurosci.

(Kutas & Federmeier 2000)

(Kutas & Federmaier 2000)

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

Ultra-fast Syntactic Analysis

(Friederici et al., 2000)

• Puzzle…

– As fast or faster than word recognition

– Leaves almost zero time for syntactic analysis!

– Elicited by a subclass of errors

– Localizes to Ant. Tpl. Regions and Broca’s Area

Early negativity

(Hahne et al., 2002)

1500ms

• Ultra-Fast Analysis

Electrophys. studies show responses to some syntactic errors within 150-250ms after word onset - Early Left Anterior Negativity, ELAN

– John criticized Max’s proof of the theory.– John criticized Max’s of proof the theory.

(Neville et al., 1991)

Ultra-fast Syntactic Analysis

• Suggestion: fastest analysis occurs when structure is built before word is seen in input

• Fastest responses reflect mismatch, when incoming word mismatches predicted category

NP

Max’s N

criticized

of

FT7

1000ms

With prediction

Without prediction

(Lau, Stroud, Plesch, & Phillips, 2006)

• Test case: same error, varying prediction

Although John criticized Bill’s data, he didn’t criticize Max’s.

a. Although John criticized Bill’s data…

…he didn’t criticize Max’s of proof the theory.

b. Although John criticized Bill…

…he didn’t criticize Max’s of proof the theory.

Eye-tracking

Frequency in Object Recognition

X

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


X

bench

bed

bell

lobster

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


• Timing estimates

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

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


(Dahan, Magnuson, & Tanenhaus, 2001)





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, then, to capture facilitatory effect of context…

Cohort

SPINA spinach

Cohort

SPIN

spin

spinach

spinster

spinaker

spindle


CAPTAIN CAPTIVE

CAPT…

SHIP

GUARD

CAPTAIN

SHIP

GUARD


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

B I G A T R

BIG BAT DOG Words

Phonemes

Feedback vs. Decision Bias

Non-Cohort Competitors

(Allopenna, Magnuson, & Tanenhaus, 1998)

“Pick up the…”

beaker

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




beaker





beaker


I wanted to point out a minor difference in your interpretation of Allopenna, Magnuson, & Tanenhaus (1998) and mine. Allopenna et al. is cited on p. 75 as one of the "estimates in the literature [that] the earliest processes involved in lexical access often fall in the 200 ms range". But eye tracking data of the sort we presented actually gives a strikingly different estimate. What we find again and again in studies using the visual world paradigm is that there is an approximately 200-250 ms lag between events in the speech signal and changes in fixation proportions. However, this should not suggest that it takes 200 ms for processes of lexical access to kick in. Rather, given that it takes at least about 150 ms to plan and launch an eye movement to a point of light in a darkened room, this means we can roughly subtract 150 msecs of the lag and attribute it to saccade planning. This leaves us with only about 50 msecs to attribute to the very earliest processes of access that are indexed by the eye movements. (This seems too short by 1-2 dozen msecs, but note that only a very small proportion of trials include such early eye movements, and statistically reliable differences between related and unrelated items emerge another ~25-50 msecs later.)

[Email message, 6/26/07]

Jim Magnuson, UConn

Outline


2. Active Search



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

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.

(Embick et al., 2001)

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, 2003)

Effect of probability/density (words)

100

200

300

400

500

600

700

M170 M250 M350 RT

HighProbWord LowProbWord

n.s.

n.s.

**

*


Effect of probability/density (nonwords)

0

100

200

300

400

500

600

700

800

M170 M250 M350 RT

HighProbNonword LowProbNonword

n.s.n.s.

*

**


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

Automatic vs. Controlled Processes

NURSEDOCTOR

DINRUP

COUCH

NURSE

NURSE

Semantic association facilitation [consistent]No association inhibition [sometimes]

Controlled/strategic effectsLong SOA (Stimulus Onset Asynchrony), e.g. > 500msExplicit pairing of wordsHigh proportion of associated pairs

(Automatic) Spreading Activation

Lau, Phillips, & Poeppel, in press, Nature Rev. Neurosci.

fMRI studies of semantic priming






High ambig: The shell was fired towards the tank.Low ambig: Her secrets were written in her diary.

Rodd, Davis, & Johnsrude, 2005, Cereb. Cortex

Masked Priming

#######

brother

BROTH

Documents

Lexical Access: Generation & Selection Main Topic Listeners as active participants in comprehension process Model system: word recognition