Lexical Access: Generation & Selection

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 Speed & Robustness of Lexical Access Active Search Evidence for Stages of Lexical Access Autonomy & Interaction

The mental lexicon sing door carry turf turtle gold turk turkey turn 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) Eye-tracking studies indicate effects of access within 200-300ms

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 1 sickle cathartic torrid gregarious oxymoron atrophy List 2 parabola periodontist preternatural pariah persimmon porous Speed of look-up reflects organization of dictionary

Looking for Words +

Looking for Words DASH

Looking for Words RASK

Looking for Words CURLY

Looking for Words PURCE

Looking for Words WINDOW

Looking for Words DULIP

Looking for Words LURID

(Embick et al., 2001)

Looking for Words Semantically Related Word Pairs doctor nurse hand finger speak talk sound volume book 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 Speed & Robustness of Lexical Access Active Search Evidence for Stages of Lexical Access Autonomy & Interaction

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 Access activation vs. competition recognition vs. selection proposal vs. disposal

Automatic activation TURN turnip turmoil sing door carry sport figure sing door carry turf turtle gold turk turkey water turn turbo turquoise turnip turmoil TURN

Lateral inhibition TURN turnip turmoil sing door carry sport figure sing door carry turf turtle gold turk turkey water turn turbo turquoise turnip turmoil TURN

What is lexical access? Activation Competition Selection/Recognition TURN TURNIP level of activation TURF TURTLE resting level time Stimulus: TURN (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 SPINA spinach spinet spineret

Cross-Modal Priming

Evidence for Cohort Activation CAPTAIN CAPTIVE SHIP SHIP CAPT… CAPTAIN GUARD GUARD (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, then, to capture facilitatory effect of context?

Gating Measures Presentation of successive parts of words 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 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)

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)

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

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 SHIP SHIP CAPT… CAPTAIN GUARD 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 lobster bench X bell bed “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 SHIP SHIP CAPT… CAPTAIN GUARD 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 “Pick up the…” beaker beetle (onset) speaker (non-onset) carriage (distractor) (Allopenna, Magnuson, & Tanenhaus, 1998)

Non-Cohort Competitors “Pick up the…” beaker beetle (onset) speaker (non-onset) carriage (distractor) (Allopenna, Magnuson, & Tanenhaus, 1998)

Non-Cohort Competitors “Pick up the…” beaker beetle (onset) speaker (non-onset) carriage (distractor) (Allopenna, Magnuson, & Tanenhaus, 1998)

Overview Reasons to be ‘active’ Speed Using highly reliable information (e.g., eleph…; NP-nom…) Using partially reliable information (e.g., ele…; NP V…; wh NP V…) Robustness Minimize storage Reasons to be ‘informationally encapsulated’ (‘modular’) Architectural constraints Information availability Capturing effects of context Bottom-up word information proposes candidates for evaluation against context Bottom-up word information yields activation based on frequency, phonotactic probability, etc. (assuming multiple access) Contextual information may prime certain lexical/semantic features, leading to earlier activation/selection of some words; context can also prime morpho-syntactic features, leading to exclusion of some word candidates

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.

Outline Speed & Robustness of Lexical Access Active Search Evidence for Stages of Lexical Access Autonomy & Interaction

M350 (based on research by Alec Marantz, Liina Pylkkänen, Martin Hackl & others)

Lexical access involves Activation of lexical representations including activation of representations matching the input, and lateral inhibition between activated representations Followed by selection or decision involving competition among activated representations that are similar in form

M350 RESPONSE TO A VISUAL WORD 0 200 300 400 Time [msec] Sagittal view

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 …

Behavioral evidence for dual effects Same/different task (“low-level”) RTs to nonwords with a high phonotactic probability are speeded up. RT High probability: MIDE Sublexical frequency effect RT Low probability: YUSH Lexical decision task (“high-level”) RTs to nonwords with a high phonotactic probability are slowed down! High probability: RT MIDE Competition effect Low probability: RT YUSH (Vitevich and Luce 1997,1999)

Stimuli High probability Low probability Word BELL, LINE PAGE, DISH Materials of Vitevich and Luce 1999 converted into orthographic stimuli. Four categories of 70 stimuli: High probability Low probability Word BELL, LINE PAGE, DISH Nonword MIDE, PAKE JIZE, YUSH High and low density words frequency matched. (Pylkkänen, Stringfellow, Marantz, Brain and Language, 2003)

Effect of probability/density (words) * ** n.s. n.s. (Pylkkänen, Stringfellow, Marantz, Brain and Language, 2003)

Effect of probability/density (nonwords) ** * n.s. n.s. (Pylkkänen, Stringfellow, Marantz, Brain and Language, 2003)

M350 = 1st component sensitive to lexical factors but not affected by competition Activation Competition Selection/Recognition TURN TURNIP level of activation TURF TURTLE resting level time Stimulus: TURN

Outline Speed & Robustness of Lexical Access Active Search Evidence for Stages of Lexical Access 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 cohorts no 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

‘baseball’ is not at all plausible here, yet it elicits a smaller N400 - why? (Kutas & Federmaier 2000)

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

Implications If Kutas & Federmeier’s results are robust, this implies that lexical priming can cause apparent early context effects this implies ‘very active search’ hemispheres are not alike in this regard

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walk

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walk

Overview Reasons to be ‘active’ Speed Using highly reliable information (e.g., eleph…; NP-nom…) Using partially reliable information (e.g., ele…; NP V…; wh NP V…) Robustness Minimize storage Reasons to be ‘informationally encapsulated’ (‘modular’) Architectural constraints Information availability Capturing effects of context Bottom-up word information proposes candidates for evaluation against context Bottom-up word information yields activation based on frequency, phonotactic probability, etc. (assuming multiple access) Contextual information may prime certain lexical/semantic features, leading to earlier activation/selection of some words; context can also prime morpho-syntactic features, leading to exclusion of some word candidates Hemispheric contrasts - does differential processing reflect deep differences?