psy1302 psychology of language lecture 14 & 15 speech production

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Psy1302 Psy1302 Psychology of Psychology of LanguageLanguage

Lecture 14 & 15Lecture 14 & 15

Speech ProductionSpeech Production

Comprehension vs. Comprehension vs. ProductionProduction

Comprehension vs. Comprehension vs. ProductionProduction

SNP VP V NP

<the> <dog> <chased> <the> <cat>

/th/.../uh/.../d/.../ah/.../g/.../ch/...etc.

Creating SentencesCreating Sentences

Our brain does not store all sentences Our brain does not store all sentences we might ever need to produce.we might ever need to produce.

We must construct and plan our speech We must construct and plan our speech using our knowledge of languageusing our knowledge of language

The main issue of The main issue of speech productionspeech production concern the processes by which units concern the processes by which units come to be selected and then come to be selected and then combined in a particular order.combined in a particular order.

Studying Speech Production Studying Speech Production

HOW?HOW? Can we find evidence that we build structure on the Can we find evidence that we build structure on the

fly? fly? – Yes...Yes... e.g. e.g. Slips of the TongueSlips of the Tongue

Much of our initial knowledge of speech production Much of our initial knowledge of speech production comes fromcomes from– Slips of the tongueSlips of the tongue– Tip of the tongue phenomenonTip of the tongue phenomenon– DisfluenciesDisfluencies

Slips of the TongueSlips of the TongueFreudian SlipsFreudian Slips

Presidential Slip during campaign (Reported in Newsweek, 1992): I don’t want to run the risk of ruining what is a lovely recession.“reception” not “recession”

Slips of the TongueSlips of the TongueMalapropismsMalapropisms

Webster definition:Webster definition: the usually unintentionally the usually unintentionally humorous misuse or distortion of a word or phrasehumorous misuse or distortion of a word or phrase

Origin:Origin: slips named after Mrs. Malaprop (mal à propos), slips named after Mrs. Malaprop (mal à propos), a fictional character in a Richard Sheridan play (The a fictional character in a Richard Sheridan play (The Rivals).Rivals).

O, he will O, he will dissolvedissolve my mystery! my mystery!

He was a man of great He was a man of great statuestatue.. Thomas Menino, Boston mayorThomas Menino, Boston mayor Republicans understand the importance of Republicans understand the importance of bondagebondage

between a mother and child.between a mother and child. Dan Quayle, Vice PresidentDan Quayle, Vice President

http://www.fun-with-words.com/malapropisms.html

Slips of the TongueSlips of the TongueSpoonerismsSpoonerismsWebster definition:Webster definition: a transposition of usually a transposition of usually

initial sounds of two or more words (as in initial sounds of two or more words (as in tons tons of soilof soil for for sons of toilsons of toil) )

Origin:Origin: slips named after Rev. William Archibald slips named after Rev. William Archibald SpoonerSpooner

You have You have hhissed all my issed all my mmystery lectures.ystery lectures.

He is a He is a shshoving oving lleopard to his flock.eopard to his flock.

Three cheers for our Three cheers for our ququeer old eer old ddean!ean!

Anglican PriestDean of Oxfordhttp://www.fun-with-words.com/spoon_history.html

Slips of the TongueSlips of the Tonguesciencescience

Knowing which slips are possible Knowing which slips are possible and which are not constrains and which are not constrains theories of productiontheories of production

Models of speech production need Models of speech production need to account for these regularities to account for these regularities in slipsin slips

Slips of the handSlips of the hand

Newkirk, Klima, Penderson & Bellugi Newkirk, Klima, Penderson & Bellugi (1980)(1980)

Corpus of 131 errors in ASL Corpus of 131 errors in ASL – 77 videotaped77 videotaped– 54 reported observations54 reported observations

Errors like slips of the tongueErrors like slips of the tongue– ExchangesExchanges– AnticipationsAnticipations– PerseverationsPerseverations

Digression…

Types of ErrorTypes of Error MisorderingMisordering

– SubstitutionSubstitution ExchangeExchange AnticipationAnticipation PerseverationPerseveration

– AdditionAddition Anticipatory additionAnticipatory addition Perseveration additionPerseveration addition

– ShiftShift– DeletionDeletion

Noncontextual errorNoncontextual error– SubstitutionSubstitution– AdditionAddition– DeletionDeletion– Blend (word level)Blend (word level)

ObservationsObservations

Exchanged segments are from the Exchanged segments are from the same levelsame level

Implies you would never hear:Implies you would never hear:– Phoneme Level with Word LevelPhoneme Level with Word Level

““The The clcl is is marketmarketosed.”osed.” (the market is (the market is closed)closed)

ObservationsObservations Exchanged segments tend to be from the Exchanged segments tend to be from the

same kind of segmentsame kind of segment– Consonant onset with consonant onsetConsonant onset with consonant onset– Vowel with vowelVowel with vowelEtc…Etc…– Verb with verbVerb with verb– Noun with nounNoun with noun

Implies you would never hear:Implies you would never hear:– Vowel with ConsonantVowel with Consonant

““HaHauuow thow thlld”d” (hallow thud) (hallow thud)

– Onset with RhymeOnset with Rhyme ““UdUdallow thallow thudud” ” (hallow thud)(hallow thud)

ObservationsObservations

Sound substitutions Sound substitutions – Often close to each otherOften close to each other– Not necessarily similar in grammatical Not necessarily similar in grammatical

category and often similar in soundcategory and often similar in sound

ImpliesTYPICAL ERROR:I saw you fight a liar in the back quad, in fact you have...

UNCOMMON ERROR:I saw you light a fire in the yack quad, in fact boo have...

ObservationsObservations

Sound substitutions Sound substitutions – Often close to each otherOften close to each other– Not necessarily similar in grammatical category Not necessarily similar in grammatical category

and often similar in soundand often similar in sound Word substitutions can cross phrasal Word substitutions can cross phrasal

boundariesboundaries– Often far apart, crossing phrasal boundariesOften far apart, crossing phrasal boundaries– Often same grammatical category and dissimilar Often same grammatical category and dissimilar

in soundin sound Independence of stem morphemes from Independence of stem morphemes from

derivational morphemederivational morpheme

SNP VP V NP

<the> <dog> <chased> <the> <cat>

/th/.../uh/.../d/.../ah/.../g/.../ch/...etc.

Stages of AssemblyStages of Assembly

Language production requires assembling Language production requires assembling multiple levels of linguistic structure accurately multiple levels of linguistic structure accurately and fluently, in real time.and fluently, in real time.

Three levels:Three levels:– ConceptualizationConceptualization

– FormulationFormulation

– ArticulationArticulation

SNP VP V NP

<the> <dog>

/th/.../uh/.../d/.../ah/.../g/.../ch/...etc.

<chased><cat>

The dog chased the cat.

FormulationFormulation

What did the speech errors tell us about What did the speech errors tell us about formulation?formulation?

Separation between accessing semantics/syntax Separation between accessing semantics/syntax (meaning/grammar) and phonology (meaning/grammar) and phonology (pronunciation) of word(pronunciation) of word

FormulationFormulation

Distributional properties of errors suggest Distributional properties of errors suggest Grammatical Encoding stageGrammatical Encoding stage

– Puts words in order Puts words in order – Sounds irrelevant Sounds irrelevant – Syntactic relations relevant Syntactic relations relevant – Wide scope planning Wide scope planning

Phonological Encoding stage Phonological Encoding stage – Puts phonemes in order Puts phonemes in order – Sounds are relevant Sounds are relevant – Syntax is irrelevant Syntax is irrelevant – Narrow scope planning Narrow scope planning

Language production requires assembling Language production requires assembling multiple levels of linguistic structure accurately multiple levels of linguistic structure accurately and fluently, in real time.and fluently, in real time.

Three levels:Three levels:– ConceptualizationConceptualization

– FormulationFormulation

– ArticulationArticulation

GrammaticalEncoding

PhonologicalEncoding

Single Word Single Word ProductionProduction Lemma Lemma retrieval: retrieval:

– select a word that matches needed select a word that matches needed meaning and grammatical category meaning and grammatical category

Lexeme Lexeme retrieval: retrieval: – retrieve the sound of a word retrieve the sound of a word

p. 111-113 of Carroll

Digression…

Why might you believe in a Why might you believe in a distinction between Lexeme distinction between Lexeme and Lemma?and Lemma?

Tip of the tongueTip of the tongue– Can retrieve Can retrieve

lemma without lemma without lexemelexeme

know the know the meaning, first meaning, first letter, syllables, letter, syllables, and stress pattern and stress pattern but can’t but can’t generate the generate the word!!!word!!!

Digression…

Picture Naming TasksPicture Naming Tasks Name that pictureName that picture Sometimes with Sometimes with PrintPrint or or AudioAudio

DistractorDistractor Vary Vary Stimulus Onset AssynchronyStimulus Onset Assynchrony

(SOA)(SOA)

SOA

timelineNegative SOA

0 msPositive SOA

Digression…

Picture Naming TasksPicture Naming Tasks Name that pictureName that picture Sometimes with Sometimes with PrintPrint or or AudioAudio

DistractorDistractor Vary Vary Stimulus Onset AssynchronyStimulus Onset Assynchrony

(SOA)(SOA)

SOA

timeline

goat

0 ms-150 ms

Hear:

Digression…

Picture Naming TaskPicture Naming Task Name that pictureName that picture Sometimes with Sometimes with PrintPrint or or AudioAudio

DistractorDistractor Vary Vary Stimulus Onset AssynchronyStimulus Onset Assynchrony

(SOA)(SOA)

SOA

timeline

goat

0 ms 150 ms

Hear:

Digression…

Schriefer, Meyer, & Schriefer, Meyer, & Levelt (1990)Levelt (1990)

Semantic distractor: (e.g. goat for sheep)Semantic distractor: (e.g. goat for sheep)Inhibition occurs at SOA = -150ms (Before presentation of picture)Inhibition occurs at SOA = -150ms (Before presentation of picture)

Phonological distractor: (e.g. sheet for sheep)Phonological distractor: (e.g. sheet for sheep)Facilitation occurs between SOA = 0 to 150 ms (After presentation of Facilitation occurs between SOA = 0 to 150 ms (After presentation of

picture)picture)No facilitation at SOA = -150 msNo facilitation at SOA = -150 ms

““goat” activates Goat Lemma competes with Sheep Lemma for goat” activates Goat Lemma competes with Sheep Lemma for selection, causing inhibition.selection, causing inhibition.

““sheet” activates sounds and is similar in sound to “sheep”, sheet” activates sounds and is similar in sound to “sheep”, facilitating production.facilitating production.

Suggest phonological encoding follows lexical selectionSuggest phonological encoding follows lexical selectionFinding is consistent with model we are going to seeFinding is consistent with model we are going to see

Digression…

Language production requires assembling Language production requires assembling multiple levels of linguistic structure accurately multiple levels of linguistic structure accurately and fluently, in real time.and fluently, in real time.

Three levels:Three levels:– ConceptualizationConceptualization

– FormulationFormulation

– ArticulationArticulation

GrammaticalEncoding

PhonologicalEncoding

FunctionalProcessing

PositionalProcessing

Garrett’s ModelGarrett’s Model

FunctionalProcessing

PositionalProcessing

GrammaticalEncoding

LEMMA

LEXEME

Planning a sentencePlanning a sentence

She handed him a broccoli.She handed him a broccoli.

Message Level – Intended meaning

AGENT

THEMERECIPIENT

ACTION

LEMMA RETRIEVAL

Feminine PronominalMasculine PronominalVegetable floretAct of Transferring

POSSIBLE ERRORS?SEMANTIC SUBSTITUTIONe.g. BROCCOLI CAULIFLOWER

AGENTRECIPIENTTHEME

ACTION

she

him

broccoli

hand

FUNCTIONAL ASSIGNMENT

• VERB ARGUMENTS• CASE ASSIGNMENTSPOSSIBLE ERRORS?

WRONG CASE ASSIGNMENTe.g. Female pronoun-nominative (SHE), Male pronoun-dative (HIM) Female pronoun-dative (HER), Male pronoun-nominative (HIM).

shehim

hand

FUNCTIONALPROCESSING

broccoliindefiinite

POSSIBLE ERRORS?STRANDING

He ordered up ending some broccoli.SHIFTS – often inflections NOT root

She was hand himming some broccoliSuggests processing of inflectional (and derivational) morphology at this level

POSITIONALPROCESSING

Errors and StagesErrors and Stages

Intended Message:Intended Message: She handed him some broccoliShe handed him some broccoli

Likely ErrorLikely Error He handed her some broccoliHe handed her some broccoli

Unlikely ErrorUnlikely Error Her handed he some broccoliHer handed he some broccoli Him handed she some broccoliHim handed she some broccoli

Common ThemesCommon Themes

Garden Path Theory (when we talked about Garden Path Theory (when we talked about comprehensioncomprehension)?)?And notions of:And notions of:– Modularity Modularity – Informational Encapsulation Informational Encapsulation

(e.g., Syntactic Parser: access to grammatical function (e.g., Syntactic Parser: access to grammatical function categories, but not thematic information in the initial parse)categories, but not thematic information in the initial parse)

Garrett’s Model (when we talked about Garrett’s Model (when we talked about productionproduction)?)?Same ideas of Modularity and Information Encapsulation:Same ideas of Modularity and Information Encapsulation:– Discrete ProcessingDiscrete Processing– Functional Processing – lemmasFunctional Processing – lemmas

(access to grammatical function but not phonological structure)(access to grammatical function but not phonological structure)– Positional Processing and Phonological Processing – Positional Processing and Phonological Processing –

lexemeslexemes(access to phonological structure but not grammatical function)(access to phonological structure but not grammatical function)

Issues:

Discrete-stage processingStrict Feedforward(Completion of one stage before the next)

Cascading processing(Partial information sent to the lower level)

Interactive processingFeedback(Lower level affect higher level)

Are the stages discrete or cascading? Are the stages discrete or cascading?

Production IssuesProduction IssuesLevelt et al. (1991)Levelt et al. (1991)

lemma level

lexeme level/sheep/

STAGE 1

STAGE 2

GOAT SHEEP

/goat/??

Are Are stages discrete or stages discrete or cascading? cascading? How do we test?How do we test?

Does sheep prime goal?

?

lemma level

lexeme level /sheep/

STAGE 1

STAGE 2

goat

/goat/

/goal/ /sheet/

SHEEP

Discrete ProcessingDiscrete Processing

lemma level

lexeme level /sheep/

STAGE 1

STAGE 2

goat

Does sheep prime goal?

/sheet/

Discrete Processing says NO!

SHEEP

lemma level

lexeme level /sheep/

STAGE 1

STAGE 2

goat

/goat/

/goal/ /sheet/

Cascading ProcessingCascading ProcessingDoes sheep prime goal?

Cascading Processing says YES!

SHEEP

lemma level

(Semantic)

lexeme level

(Phonology)

/sheep/

goat

/goat/

/goal/ /sheet/

/sheep/

goat

/sheet/

CASCADING DISCRETE

Cascade or Discrete?Cascade or Discrete?

sheep sheep

Primary Task: Name the PicturePrimary Task: Name the Picture

Secondary Task: Lexical DecisionSecondary Task: Lexical Decision

Naming: 600 ms

150 ms 125 ms 325 msV Lem Lex

Lexical decision:goal or goat or sheet or mukle(button yes/no-rt)

Mediated Priming Mediated Priming ParadigmParadigm

Does sheep prime goal? Levelt et al. (1991): No.

lemma level

couch

lexeme level/couch/

STAGE 1

STAGE 2

sofa

/sofa/

/soda/

Peterson & Savoy (1998): Yes it does: couch primes soda via sofa

sheep – goat: categorical associates

sofa – couch: near synonyms

Peterson & Savoy Peterson & Savoy (1998)(1998)

Production IssuesProduction Issues

Are the stages interactive? Are the stages interactive? (Levelt, no; Dell, yes)(Levelt, no; Dell, yes)

lemma level cat

lexeme level /cat/

Levelt

FOG DOG CAT RAT MAT

f r d k m ae o t g

Onsets Vowels

Codas

Dell

Gary Dell’s ModelGary Dell’s Model

Like the TRACE modelLike the TRACE model

FOG DOG CAT RAT MAT

f r d k m ae o t g

Onsets Vowels

Codas

Interactive processingFeedback(Lower level affect higher level)

Message: Cat

Message: Some swimmers sink.

A 2-step Interactive Model of A 2-step Interactive Model of Lexical Access in ProductionLexical Access in Production

FOG DOG CAT RAT MAT

f r d k m ae o t g

Onsets Vowels Codas

Semantic Features

Adapted from Gary Dell, “Producing words from pictures or from other words”

Activate semantic features Activate semantic features of CATof CAT

FOG DOG CAT RAT MAT

f r d k m ae o t g

Onsets Vowels Codas

Semantic Features

Adapted from Gary Dell, “Producing words from pictures or from other words”

1. Lemma Access: Activation 1. Lemma Access: Activation spreads through networkspreads through network

FOG DOG CAT RAT MAT

f r d k m ae o t g

Onsets Vowels Codas

Adapted from Gary Dell, “Producing words from pictures or from other words”

Activation after 8 Activation after 8 stepssteps

FOG DOG CAT RAT MAT

f r d k m ae o t g

Onsets Vowels Codas

Adapted from Gary Dell, “Producing words from pictures or from other words”

1. Lemma Access: 1. Lemma Access: Most active word from proper Most active word from proper category is selected and linked to category is selected and linked to syntactic framesyntactic frame

FOG DOG CAT RAT MAT

f r d k m ae o t g

Onsets Vowels Codas

Adapted from Gary Dell, “Producing words from pictures or from other words”

NP

N

2. Phonological Access: 2. Phonological Access: Jolt of activation is sent to selected Jolt of activation is sent to selected wordword

FOG DOG CAT RAT MAT

f r d k m ae o t g

Onsets Vowels Codas

Adapted from Gary Dell, “Producing words from pictures or from other words”

NP

N

2. Phonological Access: 2. Phonological Access: Activation spreads through Activation spreads through networknetwork

FOG DOG CAT RAT MAT

f r d k m ae o t g

Onsets Vowels Codas

Adapted from Gary Dell, “Producing words from pictures or from other words”

NP

N

2. Phonological Access: 2. Phonological Access: Most activated phonemes are Most activated phonemes are selectedselected

FOG DOG CAT RAT MAT

f r d k m ae o t g

Onsets Vowels Codas

Adapted from Gary Dell, “Producing words from pictures or from other words”

Syl

On Vo Co

Errors (top-down)Errors (top-down)Semantic: Shared features activate Semantic: Shared features activate semantic neighborssemantic neighbors

FOG DOG CAT RAT MAT

f r d k m ae o t g

Onsets Vowels Codas

Adapted from Gary Dell, “Producing words from pictures or from other words”

NP

N

Errors (bottom-up)Errors (bottom-up)Phoneme-word feedback activates Phoneme-word feedback activates formal neighborsformal neighbors

FOG DOG CAT RAT MAT

f r d k m ae o t g

Onsets Vowels Codas

Adapted from Gary Dell, “Producing words from pictures or from other words”

NP

N

Errors (top-down & bottom-Errors (top-down & bottom-up)up)neighbors activated by both top-neighbors activated by both top-down & bottom-up sourcesdown & bottom-up sources

FOG DOG CAT RAT MAT

f r d k m ae o t g

Onsets Vowels Codas

Adapted from Gary Dell, “Producing words from pictures or from other words”

NP

N

Errors (top-down & bottom-Errors (top-down & bottom-up)up)Selection of incorrect phonemesSelection of incorrect phonemes

FOG DOG CAT RAT MAT

f r d k m ae o t g

Onsets Vowels Codas

Adapted from Gary Dell, “Producing words from pictures or from other words”

Syl

On Vo Co

Interactive or Interactive or Discrete?Discrete?Bad Dean Dad Bean

Back Deal Dack Beal

Other:DAD

Other:BEAN

Target:BAD

Target:DEAN

C1/b/

C2/d/

V1/ae/

V2/i/

C3/d/

C4/n/

Target:BACK

Target:DEAL

C1/b/

C2/d/

V1/ae/

V2/i/

C3/k/

C4/l/

Lexical Bias EffectLexical Bias Effect Words in the lexicon influence sound Words in the lexicon influence sound

substitutionssubstitutions

Experimental Data:Experimental Data:– Probabilities calculated from speech error corpusProbabilities calculated from speech error corpus

Sound substitutions resulting in words is higher than Sound substitutions resulting in words is higher than chancechance

– Inducing speech errors in laboratory using the Inducing speech errors in laboratory using the Speech Error Generation ParadigmSpeech Error Generation Paradigm

Sound substitutions resulting in words is more likely to Sound substitutions resulting in words is more likely to happen than those not resulting in wordshappen than those not resulting in words

Bad Dean Dad Bean; Dad Dean; Bad BeanBack Deal Dack Beal; Dack Deal; Back Beal

Speech Error Generation Speech Error Generation ParadigmParadigm

Instructions:Instructions:– You will see word pairs on the screen.You will see word pairs on the screen.– Read the words to yourself silently,Read the words to yourself silently,– But be prepared to say the words out But be prepared to say the words out

loud.loud.– When you see “????????” on the When you see “????????” on the

screen,screen,– Say the last word pair out loud as Say the last word pair out loud as

quickly as possible.quickly as possible.

YELL NOTSEED REAPSAME ROPE????????

LAMB TOYLOOM TENTLET TANKTIME LINE????????

BID MEEKBUD MEEKBIG MENMAD BACK????????

BALL DOZEBASH DOORBEAN DECKBELL DARKDARN BORE????????

BIG DUTCHBANG DOLLBILL DEALBARK DOGDART BOARD????????

Speech Error Generation Speech Error Generation ParadigmParadigm(Dell 1986)(Dell 1986)

Additionally: Speech Rate Manipulation3 groups of participants:500 ms700 ms1000 ms

What kind of error?

Speech Error Generation Speech Error Generation ParadigmParadigm(Dell 1986)(Dell 1986)

Repeated Repeated PhonemePhoneme

(Same (Same Vowel)Vowel)

Non-Non-Repeated Repeated PhonemePhoneme

(Diff Vowel)(Diff Vowel)

Word Word OutcomeOutcome

Bead Dean Bead Dean Deed Deed BeanBean

Bad Dean Bad Dean Dad BeanDad Bean

No Word No Word OutcomeOutcome

Beak Deal Beak Deal Deak BeakDeak Beak

Back Deal Back Deal Dack BealDack Beal

HIGH error rate

LOW error rate

Predictions?Predictions?

Target:DEAN

Target:BAD

C1/b/

C2/d/

V1/ae/

V2/i/

C3/d/

C4/n/

Target:Bead

Target:Dean

C1/b/

C2/d/

V2/i/

C3/d/

C4/n/

Bad Dean Dad Bean

Bead Dean Deed Bean

Other:DAD

Other:BEAN

Other:DEED

Other:BEAN

LOWEST error rate

HIGHEST error rate

Word OutcomeWord OutcomeRepeated Phoneme

Repeated Phoneme

No Repeated Phoneme

No Repeated Phoneme

Non-Word Outcome Non-Word Outcome

>

>

> >

Speech Rate and Speech Rate and ErrorsErrors

1.1. ____ speech rate, more errors____ speech rate, more errors500 ms: 112; 700 ms: 89; 1000 ms: 55 errors500 ms: 112; 700 ms: 89; 1000 ms: 55 errors

2.2. Full exchanges occur at _____ speech rateFull exchanges occur at _____ speech rate500 ms: 39 (35%); 700 ms: 26 (29%); 1000 ms: 7 (13%)500 ms: 39 (35%); 700 ms: 26 (29%); 1000 ms: 7 (13%)

3.3. Lexical bias effect should increase for _____ speech Lexical bias effect should increase for _____ speech raterate

500 ms: 51 (46%); 700 ms: 54 (61%); 1000 ms: 34 (62%)500 ms: 51 (46%); 700 ms: 54 (61%); 1000 ms: 34 (62%)

4.4. Repeated phoneme effect should increase with Repeated phoneme effect should increase with _____ speech rate_____ speech rate

500 ms: 51 (46%); 700 ms: 48 (54%); 1000 ms: 29 (53%)500 ms: 51 (46%); 700 ms: 48 (54%); 1000 ms: 29 (53%)

faster

faster

slower

slower

Corpus EstimatesCorpus Estimates

Dell & Reich (1981)Dell & Reich (1981) Asked naïve students to collect speech Asked naïve students to collect speech

errors for a montherrors for a month From corpus take 2 word speech From corpus take 2 word speech

errors errors (e.g., pitch fork (e.g., pitch fork fitch pork) fitch pork)

– Calculate percentage of sound exchanges Calculate percentage of sound exchanges that resulted in wordsthat resulted in words

– Compare percentage to estimated chance Compare percentage to estimated chance that an exchange would result in a word.that an exchange would result in a word.

Estimating ChanceEstimating Chance

Estimating ChanceEstimating Chance

First position(Pitch Fitch)

Second position(Fork Pork)

60

50

40

30% r

esul

ting

in w

ords

(e.g. Pitch Fork Fitch Pork)

* Data for anticipation and perseveration similar: % resulting in words is higher than chance estimates.

Actual Data

Chance Estimate

ResultsResults

Interactive or Interactive or Discrete?Discrete?Distributional properties of errors suggest Distributional properties of errors suggest Grammatical Encoding stageGrammatical Encoding stage

– Puts words in order Puts words in order – Sounds irrelevant Sounds irrelevant – Syntactic relations relevant Syntactic relations relevant – Wide scope planning Wide scope planning

Phonological Encoding stage Phonological Encoding stage – Puts phonemes in order Puts phonemes in order – Sounds are relevant Sounds are relevant – Syntax is irrelevant Syntax is irrelevant – Narrow scope planning Narrow scope planning

??? Do phonological factors influence rates of word substitution?

Broccoli Cauliflower(NO SOUND SIMILARITY)

Present Pressure(SOUND SIMILARITY)

According to discrete processing, selection of lexical items should not be influenced by sound similarity.Q: are word substitutions with sound substitutions greater than chance?

Dell & Reich (1981) Dell & Reich (1981) continuedcontinuedFrom same corpus created by naïve students, From same corpus created by naïve students,

found 289 word substitutionsfound 289 word substitutions Determine type of word substitution: Determine type of word substitution:

– semantic or othersemantic or other Divide the word and target up by phoneme Divide the word and target up by phoneme

segments and calculate for each segment segments and calculate for each segment whether the sound matcheswhether the sound matches

Compare with chance estimate that is Compare with chance estimate that is based on proportions of phonemes at each based on proportions of phonemes at each segmentsegment

Things to think aboutThings to think about

New data mustered to support the New data mustered to support the interactive view.interactive view.

But could the discrete processing But could the discrete processing view account for the new data as view account for the new data as well? well?

Could we save Garrett’s model by a Could we save Garrett’s model by a fix?fix?– E.g. self-monitoring?E.g. self-monitoring?

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