Psy1302 Psychology of Language Lecture 8 & 9 Mental Dictionary – The Lexicon Spoken Word...

Psy1302 Psy1302 Psychology of LanguagePsychology of Language

Lecture 8 & 9Lecture 8 & 9Mental Dictionary – The LexiconMental Dictionary – The Lexicon

Spoken Word RecognitionSpoken Word Recognition

Agenda of the dayAgenda of the day Two related questionsTwo related questions

– How are words organized and stored How are words organized and stored in our brain?in our brain?

– How do we retrieve, look up words How do we retrieve, look up words from memory? from memory?

The LexiconThe LexiconA lexicon is usually a list of words together with additional word-specific information, i.e., a dictionary.

Question 1Question 1

How are words organized and How are words organized and stored in our brain?stored in our brain?

SubtextSubtext How might psychology experimentsHow might psychology experiments

– inform us of our mental processes inform us of our mental processes – help us create models of our mental help us create models of our mental

representations and of how our mind representations and of how our mind process information?process information?

Lexical Decision TaskLexical Decision TaskA Classical A Classical Reaction TimeReaction Time (RT) Paradigm (RT) Paradigm

– Task: Respond to “Is it a word?”Task: Respond to “Is it a word?”– Measure: RT for deciding Measure: RT for deciding “yes”“yes” or or “no”“no”

““blicket” is not a word. Respond: NOblicket” is not a word. Respond: NO ““lick” is a word. Respond: YESlick” is a word. Respond: YES

RT (i.e., speed of look-up) informs us of RT (i.e., speed of look-up) informs us of the organization of the mental lexiconthe organization of the mental lexicon

Lexical Decision TaskLexical Decision Task

+ASKRASKSNARLPURCEPLUPBLUTYNUMBERCLAM

(Embick et al., 2001)

Lexical Decision Task Lexical Decision Task Frequency Effect - ResultsFrequency Effect - Results

Lexical Decision Task Lexical Decision Task Frequency Effect - SummaryFrequency Effect - Summary

In a lexical decision task, In a lexical decision task, responses are faster for more responses are faster for more frequent wordsfrequent words

Implies lexicon organized by Implies lexicon organized by frequencyfrequency

Lexical Decision TaskLexical Decision TaskSemantic EffectSemantic Effect

SemanticallySemantically Related Word Pairs Related Word Pairsbutter milkbutter milk

doctordoctor nursenursehandhand fingerfingerspeakspeak talktalksoundsound volumevolumebookbook volumevolume

BREADBUTTER

NURSEBUTTER

WINEPLAME

PLAMEWINE

PABLEREAB

YES

Top: WordBottom: Associate YES

Top: WordBottom: Non-associate NO

Top: WordBottom: Nonword NO

Top: NonwordBottom: Word

NOTop: NonwordBottom: NonwordMeyer, D. E., & Schvaneveldt, R. W. (1971)

Lexical Decision TaskLexical Decision TaskSemantic Effect - DesignSemantic Effect - Design

Meyer, D. E., & Schvaneveldt, R. W. (1971)

Lexical Decision TaskLexical Decision TaskSemantic Effect - ResultsSemantic Effect - Results

RT Associated words < RT of ALL other conditions RT Associated words < RT of ALL other conditions Of the NO responses of First word is a Nonword < RT Of the NO responses of First word is a Nonword < RT

First word is a wordFirst word is a word

Lexical Decision Task Lexical Decision Task Semantics Effect - SummarySemantics Effect - Summary

In a lexical decision task, responses are In a lexical decision task, responses are faster for semantically associated wordsfaster for semantically associated words[Terminology:[Terminology:– when a target (e.g., BUTTER) is preceded by when a target (e.g., BUTTER) is preceded by

a stimulus (e.g., BREAD) and the target is a stimulus (e.g., BREAD) and the target is processed faster, this is called “processed faster, this is called “PRIMINGPRIMING” ”

– BREAD BREAD primesprimes BUTTER BUTTER– BREAD is the “BREAD is the “primeprime”.]”.]

Implies lexicon organized by Implies lexicon organized by meaningmeaning

Variants of PrimingVariants of Priming

Present the words seriallyPresent the words serially prime = CAPTAINprime = CAPTAIN

target = BOAT target = BOAT CAPTAIN

Time (lags vary)

####

BOAT

(sometimes introduce masking or other words introduced in between)

http://opl.apa.org/Experiments/Start.aspx?EID=8

Variants of PrimingVariants of Priming

Cross-modal PrimingCross-modal Priming

“captain”

BOAT

CAPTAIN PAMPHLET

BOAT BOAT

Cross-Modal PrimingCross-Modal Priming((Marslen-Wilson & Zwitserlood)

Prediction of RT?Prediction of RT?

SLOW<

FAST

• Things to control about the primes (CAPTAIN & PAMPHLET): • frequency, syllable duration, and # of letters are comparable.

Lexical Decision TaskLexical Decision TaskPhonology effectsPhonology effects

Design your own experimentDesign your own experiment How might you test whether the How might you test whether the

lexicon is organized by lexicon is organized by phonologyphonology??For Example:For Example:– When you are hearing “spinach” do When you are hearing “spinach” do

you access words like “spinster” or you access words like “spinster” or “spinach”?“spinach”?

Cross-modal PrimingCross-modal Priming((Marslen-Wilson & Zwitserlood)

Hear word through earphone.Hear word through earphone.– E.g. “Captain”E.g. “Captain”

Judge whether string presented Judge whether string presented on monitor is a word or not a on monitor is a word or not a word.word.– Does hearing “captain” which Does hearing “captain” which

sounds like “capital” PRIME sounds like “capital” PRIME “money”?“money”?

KAPITAALKAPITEIN

Cross-modal PrimingCross-modal Priming((Marslen-Wilson & Zwitserlood)

Vocabulary in DutchVocabulary in Dutch– KAPITEIN: captain– BOOT: boat– KAPITAAL: capital– GELD: money– PAMFLET: pamphlet

“KAPITEIN” (captain)

GELD KAPITAAL-GELD


Hear Prime:

Lexical Decision:

• KAPITEIN & KAPITAAL controlled for frequency (captain) (capital)

(capital-money)

“PAMFLET” (pamphlet)

GELD PAMFLET-GELD


Hear Prime:

Lexical Decision:

• KAPITEIN & PAMFLET controlled for frequency (captain) (pamphlet)

(pamphlet-money)

KAPITEIN PAMFLET

BOOT

GELD

BOOT

GELD


Prediction of RT if KAPITEIN activates Prediction of RT if KAPITEIN activates KAPITAAL?KAPITAAL?

SLOW

<

<FAST

=

SLOW

=<

(captain) (pamphlet)

(boat) (boat)

(money) (money)MEDIUM

Summary of Summary of ExperimentsExperiments The 3 Lexical Decision & Cross-The 3 Lexical Decision & Cross-

modal Priming Tasks show:modal Priming Tasks show:– lexicon organized by lexicon organized by frequencyfrequency– lexicon organized by lexicon organized by semantic semantic

relatednessrelatedness– lexicon organized by lexicon organized by phonological phonological

relatednessrelatedness

Question 2Question 2

How do we retrieve, look up How do we retrieve, look up words from memory?words from memory?

Two Historical Models of Two Historical Models of Organization and Organization and RetrievalRetrieval Serial Models (Forster)Serial Models (Forster) Parallel Models (Morton)Parallel Models (Morton)

SerialSerial Search Models Search Models Forster 1989Forster 1989

– Serially searchSerially search to match word to match word Frequency ordered phonological listFrequency ordered phonological list

– Explains more frequent words are accessed Explains more frequent words are accessed firstfirst

Semantically associate listSemantically associate list– Priming & Context plays a role and makes less Priming & Context plays a role and makes less

frequent words be accessed fasterfrequent words be accessed faster

Serial Search ModelsSerial Search ModelsForster’s ModelForster’s Model

SerialSerial Search Models Search Models Forster 1989Forster 1989

– Serially searchSerially search to match word to match word Frequency ordered phonological listFrequency ordered phonological list

– Explains more frequent words are accessed Explains more frequent words are accessed firstfirst

Semantically associate listSemantically associate list– Priming & Context plays a role and makes less Priming & Context plays a role and makes less

frequent words be accessed fasterfrequent words be accessed faster

SerialSerial Search Models Search ModelsEvaluationEvaluation Physiological unrealisticPhysiological unrealistic

– Neuron transmission slowNeuron transmission slow 100 time steps can be computed in ½ 100 time steps can be computed in ½

second (Feldman & Ballard, 1982)second (Feldman & Ballard, 1982)

– But retrieval of a word is FASTBut retrieval of a word is FAST– If we know ~75K words, searching If we know ~75K words, searching

serially is time consuming.serially is time consuming.

Parallel Parallel Search ModelsSearch Models Morton’s Logogen model (1964, Morton’s Logogen model (1964,

1979).1979).– (father of other models to come)(father of other models to come)

Next few slides adapted from J. Simner.

Parallel Search ModelParallel Search ModelMorton’s Logogen ModelMorton’s Logogen Model

The lexical entry for each word comes with aThe lexical entry for each word comes with a logogen logogen unitunit

Input such as [k] of “cat” Input such as [k] of “cat” activateactivate the relevant units in the relevant units in parallelparallel.. The lexical entry becomes available once the logogen ‘The lexical entry becomes available once the logogen ‘firesfires’ ’

– (i.e., reaches threshold)(i.e., reaches threshold)

skip

cat

campcot

INPUT [k]

Analogy of logogen unit ‘firing’.

skip

cat

campcot

INPUT /kaet/

Threshold

Parallel Search ModelParallel Search ModelMorton’s Logogen Morton’s Logogen ModelModel

High frequency words have a lower threshold for firing, so it takes less to activate.

lower threshold = shorter RT

‘cat’[kæt]

‘cot’[kot]

Parallel Search ModelParallel Search ModelMorton’s Logogen Morton’s Logogen ModelModel

canary

bird

animal

ostrich

mammal

yellow

doctordentist

fever

green

baby

cradle

bed hospital

sun

rainheat

grass

nurse

delirium

Network connection of Network connection of LogogensLogogens

canary

bird

animal

ostrich

mammal

yellow

doctordentist

fever

green

baby

cradle

bed hospital

sun

rainheat

grass

nurse

delirium

“doctor” spread activation to “nurse” so “nurse” becomes semi-activated.NURSE now requires less to fire.

Spreading ActivationSpreading Activation

ParallelParallel Search Models Search ModelsEvaluationEvaluationAccounting for DataAccounting for Data

– High frequency words have lower threshold High frequency words have lower threshold – Multiple Networks: Words related by… Multiple Networks: Words related by…

meaning are linked in a meaning are linked in a semantic networksemantic network sound are linked in a sound are linked in a phonological networkphonological network

– How to deal with ability to judge something How to deal with ability to judge something as a non-word?as a non-word?

Impose a timer. After a certain time period, decide Impose a timer. After a certain time period, decide not a wordnot a word

Appeal - EfficiencyAppeal - Efficiency Lexical access is in parallelLexical access is in parallel

In-Class Discussion In-Class Discussion TimeTime(Discussion of HW assignment)(Discussion of HW assignment)

Design a program to recognize Design a program to recognize words in speech when given the words in speech when given the phonetic transcription.phonetic transcription.– Simple Case: One wordSimple Case: One word– Hard Case: string of multiple words Hard Case: string of multiple words

(word segmentation problem)(word segmentation problem)

Recognizing a single Recognizing a single wordword The Simplest IdeaThe Simplest Idea

– Take the string of Take the string of phonemes/syllables in order and phonemes/syllables in order and match the string to find a word in match the string to find a word in our mental lexiconour mental lexicon

– (In the same way we look up words (In the same way we look up words in a dictionary – alphabet by in a dictionary – alphabet by alphabet.)alphabet.)

Cohort of CandidatesCohort of Candidates

SS

songsong

storystory

sparrowsparrow

sauntersaunter

slowslow

secretsecret

sentrysentry......

(i.e., words beginning w/ the sound heard so far)Slides adapted from P. Collins.


SPSP

spicespice

spokespoke

sparespare

spinspin

splendidsplendid

spellingspelling

spreadspread

(i.e., words beginning w/ the sound heard so far)

...


SPISPI

spitspit

spigotspigot

spillspill

spiffyspiffy

spinakerspinaker

spiritspirit

spinspin...

Segmenting a string of Segmenting a string of words (hw Q1B)words (hw Q1B) THEREDONATEAKETTLEOFTENCHIPS

THE RED ON A TEA KETTLE OFTEN CHIPS

THERE, DON ATE A KETTLE OF TEN CHIPS

PROCEDURE?

Alignment ProblemAlignment Problem

The sky is falling!

This guy is falling!

or

ThesKyisfalling!

Segmenting a string of Segmenting a string of wordswords THEREDONATEAKETTLEOFTENCHIPS

THE REDONATEAKETTLEOFTENCHIPS – THE RED ONATEAKETTLEOFTENCHIPS

THE RED ON ATEAKETTLEOFTENCHIPS– THE RED ON A TEAKETTLEOFTENCHIPS

…– THE RED ON ATE AKETTLEOFTENCHIPS

…– THE REDO NATEAKETTLEOFTENCHIPS

…– THE REDONATE AKETTLEOFTENCHIPS

… THERE DONATEAKETTLEOFTENCHIPS

– ...

(so on and so forth… MANY ALTERNATIVES TO GO THROUGH!!!)(Is this how our brains segments speech?)

Some Design IssuesSome Design Issues

Depth first vs. Breadth first Depth first vs. Breadth first SearchSearch

Pruning?Pruning?

Outline for rest of Outline for rest of today and next lecturetoday and next lecture We are fast at speech recognition.We are fast at speech recognition. How do we achieve speed?How do we achieve speed?

– Contextual EffectsContextual Effects– Terminologies and IdeasTerminologies and Ideas– Two Classic ModelsTwo Classic Models

Cohort ModelCohort Model TRACE ModelTRACE Model

[and many experimental paradigms and [and many experimental paradigms and findings]findings]

Speech Recognition is Speech Recognition is FASTFAST Intuitively immediate.Intuitively immediate. Comprehension happens around 200-Comprehension happens around 200-

300ms after hearing the word.300ms after hearing the word.– Eye-tracking StudiesEye-tracking Studies– Shadowing StudiesShadowing Studies– Gating StudiesGating Studies– Word Monitoring StudiesWord Monitoring Studies

Eye-tracking Eye-tracking TechnologyTechnology

“Pick up the square”

Computer records scene plus eye

fixation

Eye camera

Scene camera

“Pick up the candle”

http://www.psych.upenn.edu/trueswell_videos/adult1u.mov

Same Command: “Pick up the candle.”Two Different Scenes

++

COMPETITORof “candle”(phonologically)

TARGET

Competitor ABSENT Competitor PRESENT

Eye-tracking Eye-tracking TechnologyTechnology

ResultsResultsLatency from onset of spoken targetLatency from onset of spoken target

It takes 200ms It takes 200ms to program an to program an eye eye movement.movement.

So processing So processing time here is time here is about 200ms about 200ms to 250ms for to 250ms for word word comprehensiocomprehension.n.

FAST!!!FAST!!!

Digression: Digression: Typical Eyetracking Data Typical Eyetracking Data PresentationPresentation

Speech RecognitionSpeech Recognition How do we achieve speed?How do we achieve speed?

– Parallel search of wordsParallel search of words I.e. Activation of potential candidates in I.e. Activation of potential candidates in

parallelparallel

But…But…– Parallel search leads to many likely Parallel search leads to many likely

candidates to consider at the same time.candidates to consider at the same time.– If there are many possible likely If there are many possible likely

candidates, how do we QUICKLY select candidates, how do we QUICKLY select the right candidate among the choices?the right candidate among the choices?

Speech RecognitionSpeech Recognition

CONTEXTUAL EFFECTS?CONTEXTUAL EFFECTS? Suppose you hear:Suppose you hear:

– Popeye loves to eat… Popeye loves to eat…

Have you already guessed what Have you already guessed what the next word is going to be?the next word is going to be?

Shadowing TaskShadowing Task

1. Message entering participant’s ears.

2. Participant repeat (speak) what s/he hears while listening – SHADOWING!

3. The participant’s speech is recorded for analysis.

Record Sound


Message played into ears (160 words/min):Susan and Jill wanted…

Measure onset of each word shadowed relative to the tone.

Tone synchronized with start of every wordof message sent to recorder.

Shadowed Speech

(Marslen-Wilson 1973)


Susan and Jill wanted…

Measure onset of each word shadowed relative to the tone.

(Marslen-Wilson 1973)

Message Played:

Message Shadowed: Susan and Jill wanted…

onset

tone

time

Time unfolding…

Shadowing TaskShadowing Task(Marslen-Wilson 1973)

Record Shadowed Message

Finding: About 10% of the population can shadow with 250ms delay.Most people shadow between 800ms-1000ms.

Shadowing TaskShadowing Task(Marslen-Wilson 1973)

Record Shadowed Message

You might ask: Are they really retrieving words and processing what they heard that quickly?

(1) Post-reading, participants were good at answering content questions.

(2) Errors found were structurally appropriate:e.g. insertion of “that” From:It was beginning to be light enough so I could see…To:It was beginning to be light enough so that I could see…

In-Class Shadowing In-Class Shadowing DemoDemo 2 Volunteers2 Volunteers

– One to read a passageOne to read a passage– One to shadow a passageOne to shadow a passage

Psy1302 Psychology of Language Lecture 8 & 9 Mental Dictionary – The Lexicon Spoken Word...

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