PSY 369: Psycholinguistics Language Production: Models of language production

PSY 369: Psycholinguistics

Language Production:Models of language production

Announcements

Exam 2 is coming up (Thurs, Apr. 1) An updated review sheet is on the syllabus

Brief roadmap

Language production research Today:

Models of Language production Levelt’s model Dell’s model Some of the characteristics that distinguish the

models Some of the research to investigate the models

Tuesday: Conversation – Production and Comprehension come together

Nitty-gritty details of the model

Message level

Morphemic level

Syntactic level

Phonemic level

Articulation

A central question: How do we do speak so quickly and fluently?

Are the stages discrete or cascading? Discrete (modular): must complete before

moving on Cascade: can get started as soon as some

information is available Is there feedback?

Top-down only (serial processing) Garrett, Levelt

Bottom up too (interactive processing) Dell, Stemberger, McKay

Two different models

Message

Lexicon

Grammatical

Form

Articulation

FunctionalProcessing

PositionalProcessing

TACTIC FRAMES LEXICAL NETWORK

Dell (1986)Levelt (1989)

Levelt’s model Four broad stages:

Conceptualization Deciding on the message (= meaning

to express) Formulation

Turning the message into linguistic representations

Grammatical encoding (finding words and putting them together)

Phonological encoding (finding sounds and putting them together)

Articulation Speaking (or writing or signing)

Monitoring (via the comprehension system)

Message

Lexicon

Grammatical

Form

Articulation



Formalization on the Syntax side of the model

Works in parallel with the lexicon sideMessage

Lexicon

Grammatical

Form

Articulation



Levelt’s model

Functional processing: Assignment of roles

Direct object

Grammatical subject

Formalization on the Syntax side of the model

Works in parallel with the lexicon sideMessage

Lexicon

Grammatical

Form

Articulation



Levelt’s model

Positional processing: Build syntactic tree

NP VP

S

V NP

Tip of tongue state when lemma is retrieved without word-form being retrieved

Message

Lexicon

Grammatical

Form

Articulation



Levelt’s model

Involves lexical retrieval: Semantic/syntactic content

(lemmas) Phonological content

(lexemes or word-forms)

Formalization on the Lexicon side of the model

has stripes is dangerous

TIGER (X)

Fem.

Noun

countabletigre

/tigre/

/t/ /I/ /g/

Lexical concepts

Lemmas

Lexemes

Phonemes

Levelt’s model (see chpt 5, pg 115-117)


TIGER (X)

Levelt’s model: conceptual level

Conceptual level is not decomposed one lexical concept node for

“tiger” instead, conceptual links from

“tiger” to “stripes”, etc.

Fem.

Noun

tigre

/tigre/

/t/ /I/ /g/

countable

TIGER (X)

Fem.

Noun

tigre

Levelt’s model: meaning & syntax

First, lemma activation occurs This involves activating a lemma or

lemmas corresponding to the concept thus, concept TIGER activates lemma

“tiger”


/tigre/

/t/ /I/ /g/

countable

TIGER (X)

Fem.

Noun

tigre


First, lemma activation occurs This involves activating a lemma or

lemmas corresponding to the concept thus, concept TIGER activates lemma

“tiger”

But also involves activating other lemmas

TIGER also activates LION (etc.) to some extent

and LION activates lemma “lion”

LION (X)

lion

/tigre/

/t/ /I/ /g/


TIGER (X)

Fem.

Noun

tigre


First, lemma activation occurs Second, lemma selection occurs

LION (X)

lion

Selection is different from activation

Only one lemma is selected Probability of selecting the target

lemma (“tiger”) ratio of that lemma’s activation to

the total activation of all lemmas (“tiger”, “lion”, etc.)

Hence competition between semantically related lemmas

/tigre/

/t/ /I/ /g/


Morpho-phonological encoding (and beyond)

The lemma is now converted into a phonological representation

called “word-form” (or “lexeme”) If “tiger” lemma plus plural (and

noun) are activated Leads to activation of morphemes

tigre and s Other processes too

Stress, phonological segments, phonetics, and finally articulation/tigre/

/t/ /I/ /g/


Fem.

Noun countable

tigre

TIGER (X)

Modularity Later processes cannot affect

earlier processes No feedback between the word-form

(lexemes) layer and the grammatical (lemmas) layer

Also, only one lemma activates a word form

If “tiger” and “lion” lemmas are activated, they compete to produce a winner at the lemma stratum

Only the “winner” activates a word form (selection)

The word-forms for the “losers” aren’t accessed

Model’s assumptions

Message

Lexicon

Grammatical

Form

Articulation



Dell’s interactive account Dell (1986) presented the one of the best-known

interactive accounts other similar accounts exist (e.g., Stemberger, McKay)

Network organization 3 levels of representation

Semantics (decomposed into features) Words and morphemes phonemes (sounds)

These get selected and inserted into frames

Dell (1986)

A moment in the production of:

“Some swimmers sink”


Dell’s interactive account

as well as “downwards”

information

inform

ation

Interactive because information flows “upwards”

Dell (1986)

Cascading because processing at lower levels can start early



these send activation back to the word level, activating words containing these sounds (e.g., “log”, “dot”) to some extent

Dell (1986)

this activation is upwards (phonology to syntax) and wouldn’t occur in Levelt’s account

FURRY BARKS

dog log

/a//g//d/ /l/

MAMMAL e.g., the semantic features mammal, barks, four-legs activate the word “dog”

this activates the sounds /d/, /o/, /g/dot

/t/


Model comparisons

Levelt’s Dell’s

Similar representations

Frames and slots

Insertion of representations into the frames

Serial

Modular

External monitor(comprehension)

Interactive

Cascaded

Similarities

Differences

Testing Models of language production

Experimental investigations of some of these issues

Time course - cascading vs serial Picture word interference

Separation of syntax and semantics Subject verb agreement

Abstract syntax vs surface form Syntactic priming

tiger

Picture-word interference task Task:

Participants name basic objects as quickly as possible

Distractor words are embedded in the object (or presented aloud)

Participants are instructed to ignore these words

Experimental tests

Semantic interference Meaning related words can

slow down naming the picture

e.g., the word TIGER in a picture of a LION

Experimental tests

tiger

Picture-word interference task

Form-related words can speed up processing

e.g., the word liar in a picture of a LION

liar

Experimental tests Picture-word interference task

Semantic interference

Experiments manipulate timing: picture and word can be presented

simultaneously

liar

time

liar

or one can slightly precede the other We draw inferences about time-course of processing

liar

Experimental tests

SOA (Stimulus onset asynchrony) manipulation -150 ms (word …150 ms … picture) 0 ms (i.e., synchronous presentation) +150 ms (picture …150ms …word)

Schriefers, Meyer, and Levelt (1990) DOT phonologically related CAT semantically related SHIP unrelated word

Evidence against interactivity

Schriefers, Meyer, and Levelt (1990) DOT phonologically related CAT semantically related SHIP unrelated word

EarlyOnly Semantic effects

LateOnly Phonological effects


Schriefers, Meyer, and Levelt (1990) Also looked for any evidence of a mediated

priming effect

hat dog

DOG (X) CAT (X)

cat

/cat/ /hat/

/t//a//k/ /h/

Found no evidence for it


Early semantic inhibition Late phonological facilitation Fits with the assumption that semantic processing

precedes phonological processing No overlap

suggests two discrete stages in production an interactive account might find semantic and phonological

effects at the same time

Interpretation

Mixed errors Both semantic and phonological relationship to target word Target = “cat”

semantic error = “dog” phonological error = “hat” mixed error = “rat”

Occur more often than predicted by modular models if you can go wrong at either stage, it would only be by chance

that an error would be mixed

Evidence for interactivity

Dell’s explanation The process of making an error

The semantic features of dog activate “cat” Some features (e.g., animate, mammalian) activate “rat” as well “cat” then activates the sounds /k/, /ae/, /t/ /ae/ and /t/ activate “rat” by feedback This confluence of activation leads to increased tendency for

“rat” to be uttered Also explains the tendency for phonological errors to be real

words (lexical bias effect) Sounds can only feed back to words (non-words not

represented) so only words can feedback to sound level


A number of recent experimental findings appear to support interaction under some circumstances (or at least cascading models) Damian & Martin (1999) Cutting & Ferreira (1999) Peterson & Savoy (1998)


Damian and Martin (1999) Picture-Word interference The critical difference:

the addition of a “semantic and phonological” condition

Picture of Apple peach (semantically related) apathy (phonologically related) apricot (sem & phono related) couch (unrelated)

peach


Damian & Martin (1999)

early semantic inhibition

couch (unrelated)

peach (semantically related)

apathy (phonologically related)

apricot (sem & phono related)



late phonological facilitation (0 and + 150 ms)


couch (unrelated)






late phonological facilitation (0 and + 150 ms)

Shows overlap, unlike Schriefers et al.


couch (unrelated)





Cutting and Ferreira (1999) Picture-Word interference The critical difference:

Used homophone pictures Related distractors could be to

the depicted meaning or alternative meaning

“game”

“dance”

“hammer” (unrelated)

Only tested -150 SOA

dance


ball

BALL (X) BALL (X)

ball

/ball/

DANCE (X)

dance

GAME (X)

game

Cascading Prediction: dance ball /ball/

Cutting and Ferreira (1999)


Early semantic inhibition



Early Facilitation from a phonologically mediated distractor

Early semantic inhibition


Evidence of cascading information flow (both semantic and phonological information at early SOA)


Peterson & Savoy (1998) Slightly different task

Prepare to name the picture

If “?” comes up name it?


Peterson & Savoy (1998) Slightly different task

Prepare to name the picture

If “?” comes up name it If a word comes up

instead, name the word

liar

Manipulate Word/picture relationship SOA


Peterson & Savoy (1998) Used pictures with two

synonymous names

Used words that were phonologically related to the non dominant name of the picture

sofa couch

DominantSubordinate

soda


Peterson & Savoy Found evidence for phonological activation of near

synonyms: Participants slower to say distractor soda than unrelated

distractor when naming couch Soda is related to non-selected sofa

Remember that Levelt et al. assume that only one lemma can be selected and hence activate a phonological form

Levelt et al’s explanation: Could be erroneous selection of two lemmas?


Can the two-stage account be saved?

Evidence for interaction is hard to reconcile with the Levelt account However, most attempts are likely to revolve

around the monitor Basically, people sometimes notice a problem and

screen it out Levelt argues that evidence for interaction

really involves “special cases”, not directly related to normal processing

Levelt et al.’s theory of word production: Strictly modular lexical access Syntactic processing precedes phonological

processing Dell’s interactive account:

Interaction between syntactic and phonological processing

Experimental evidence is equivocal, but increasing evidence that more than one lemma may activate associated word-form

Overall summary

Conversational interaction“the horse raced past

the barn”

Conversation is more than just two side-by-side monologues.

“the kids swam across the river”

Conversational interaction“The horse raced past

the barn”

Conversation is a specialized form of social interaction, with rules and organization.

“Really? Why would it do that?”

Conversation Herb Clark (1996)

Joint action People acting in coordination with one another

doing the tango driving a car with a pedestrian crossing the street

The participants don’t always do similar things Autonomous actions

Things that you do by yourself Participatory actions

Individual acts only done as parts of joint actions


Speaking and listening Traditionally treated as autonomous actions

Contributing to the tradition of studying language comprehension and production separately

Clark proposed that they should be treated as participatory actions


Speaking and listening Component actions in production and

comprehension come in pairs

Speaking Listening A vocalizes sounds for B

A formalizes utterances for B

A means something for B

B attends to A’s vocalizations

B identifies A’s utterances

B understands A’s meaning

The actions of one participant depend on the actions of the other


Face-to-face conversation - the basic setting Features

Co-presence Visibility Audibility

Instantaneity

Evanescence Recordlessness Simultaneity

Extemporaneity Self-determination Self-expression

Immediacy Medium Control

Other settings may lack some of these features e.g., telephone conversations take away co-presence and

visibility, which may change language use

Meaning and understanding ABBOTT: Super Duper computer store. Can I help you? COSTELLO: Thanks. I'm setting up an office in my den, and I'm thinking about buying a

computer. ABBOTT: Mac? COSTELLO: No, the name is Lou. ABBOTT: Your computer? COSTELLO: I don't own a computer. I want to buy one. ABBOTT: Mac? COSTELLO: I told you, my name is Lou. ABBOTT: What about Windows? COSTELLO: Why? Will it get stuffy in here? ABBOTT: Do you want a computer with windows? COSTELLO: I don't know. What will I see when I look in the windows? ABBOTT: Wallpaper. COSTELLO: Never mind the windows. I need a computer and software. ABBOTT: Software for windows? COSTELLO: No. On the computer! I need something I can use to write proposals, track

expenses and run my business. What have you got? ABBOTT: Office.

Meaning and understanding COSTELLO: Yeah, for my office. Can you recommend anything? ABBOTT: I just did. COSTELLO: You just did what? ABBOTT: Recommend something. COSTELLO: You recommended something? ABBOTT: Yes. COSTELLO: For my office? ABBOTT: Yes. COSTELLO: OK, what did you recommend for my office? ABBOTT: Office. COSTELLO: Yes, for my office! ABBOTT: I recommend office with windows. COSTELLO: I already have an office and it has windows!OK, lets just say, I'm sitting at

my computer and I want to type a proposal. What do I need? ABBOTT: Word. COSTELLO: What word? ABBOTT: Word in Office. COSTELLO: The only word in office is office. ABBOTT: The Word in Office for Windows.

Meaning and understanding COSTELLO: Which word in office for windows? ABBOTT: The Word you get when you click the blue "W.” COSTELLO: I'm going to click your blue "w" if you don't start with some straight

answers. OK, forget that. Can I watch movies on the Internet? ABBOTT: Yes, you want Real One. COSTELLO: Maybe a real one, maybe a cartoon. What I watch is none of your

business. Just tell me what I need! ABBOTT: Real One. COSTELLO: If it ﾕ s a long movie I also want to see reel 2, 3 and 4. Can I watch them? ABBOTT: Of course. COSTELLO: Great, with what? ABBOTT: Real One. COSTELLO; OK, I'm at my computer and I want to watch a movie.What do I do? ABBOTT: You click the blue "1.” COSTELLO: I click the blue one what? ABBOTT: The blue "1.” COSTELLO: Is that different from the blue "W"? ABBOTT: The blue 1 is Real One and the blue W is Word. COSTELLO: What word?

Meaning and understanding ABBOTT: The Word in Office for Windows. COSTELLO: But there are three words in "office for windows"! ABBOTT: No, just one. But it ﾕ s the most popular Word in the world. COSTELLO: It is? ABBOTT: Yes, but to be fair, there aren't many other Words left. It pretty much wiped out all the other

Words. COSTELLO: And that word is real one? ABBOTT: Real One has nothing to do with Word. Real One isn't even Part of Office. COSTELLO: Stop! Don't start that again. What about financial bookkeeping you have anything I can

track my money with? ABBOTT: Money. COSTELLO: That's right. What do you have? ABBOTT: Money. COSTELLO: I need money to track my money? ABBOTT: It comes bundled with your computer. COSTELLO: What's bundled to my computer? ABBOTT: Money.

Meaning and understanding COSTELLO: Money comes with my computer? ABBOTT: Yes. No extra charge. COSTELLO: I get a bundle of money with my computer? How much? ABBOTT: One copy. COSTELLO: Isn't it illegal to copy money? ABBOTT: Microsoft gave us a license to copy money. COSTELLO: They can give you a license to copy money? ABBOTT: Why not? THEY OWN IT!

(LATER) COSTELLO: How do I turn my computer off?? ABBOTT: Click on "START".

Meaning and understanding Common ground

Knowledge, beliefs and suppositions that the participants believe that they share

Members of cultural communities Shared experiences What has taken place already in the conversation

Common ground is necessary to coordinate speaker’s meaning with listener’s understanding

Conversations are purposive and unplanned Typically you can’t plan exactly what you’re going

to say because it depends on another participant Conversations look planned only in retrospect

Conversations have a fairly stable structure

Structure of a conversation

Joe: (places a phone call) Kevin: Miss Pink’s office - hello Joe: hello, is Miss Pink in Kevin: well, she’s in, but she’s engaged at

the moment, who is it? Joe: Oh it’s Professors Worth’s secretary,

from Pan-American college Kevin: m, Joe: Could you give her a message “for

me” Kevin: “certainly” Joe: u’m Professor Worth said that, if Miss

Pink runs into difficulties, .. On Monday afternoon, .. With the standing subcommittee, .. Over the item on Miss Panoff, …

Structure of a conversation Kevin: Miss Panoff? Joe: Yes, that Professor Worth would be

with Mr Miles all afternoon, .. So she only had to go round and collect him if she needed him, …

Kevin: ah, … thank you very much indeed, Joe: right Kevin: Panoff, right “you” are Joe: right Kevin: I’ll tell her, Joe: thank you Kevin: bye bye Joe: bye

Structure of a conversation Action sequences: smaller joint projects to fulfill a

goal Adjacency pairs

Opening the conversation Kevin: Miss Pink’s office - hello Joe: hello, ..

Exchanging information about Pink Joe:.., is Miss Pink in Kevin: well, she’s in, but she’s engaged at the moment…

Structure of a conversation Action sequences: smaller joint projects to fulfill a

goal Adjacency pairs

Exchanging the message from Worth Joe: u’m Professor Worth said that, if Miss Pink runs into

difficulties, .. On Monday afternoon, .. With the standing subcommittee, .. Over the item on Miss Panoff, …

Closing the conversation Kevin: I’ll tell her, Joe: thank you Kevin: bye bye Joe: bye

Opening conversations Need to pick who starts

Turn taking is typically not decided upon in advance Potentially a lot of ways to open, but we typically restrict

our openings to a few ways Address another Request information Offer information Use a stereotyped expression or topic

Opening conversations Has to resolve:

The entry time Is now the time to converse?

The participants Who is talking to whom?

Their roles What is level of participation in the conversation?

The official business What is the conversation about?

EavesdropperAll listeners

Identifying participants Conversation often takes place in situations

that involve various types of participants and non-participants

BystanderSide

participantsAll participants

Speaker Addressee

Taking turns Typically conversations don’t involve two (or

more) people talking at the same time

Individual styles of turn-taking vary widely Length of a turn is a fairly stable

characteristic within a given individual’s conversational interactions

Standard signals indicate a change in turn: a head nod, a glance, a questioning tone

Taking turns Typically conversations don’t involve two (or

more) people talking at the same time Three implicit rules (Sacks et al, 1974)

Rule 1: Current speakers selects next speaker Rule 2: Self-selection: if rule 1 isn’t used, then next

speaker can select themselves Rule 3: current speaker may continue (or not)

These principles are ordered in terms of priority The first is the most important, and the last is the least

important Just try violating them in an actual conversation (but

debrief later!)

Taking turns Typically conversations don’t involve two (or more)

people talking at the same time

Use of non-verbal cues Drop of pitch Drawl on final syllable Termination of hand signals Drop in loudness Completion of a grammatical clause Use of stereotyped phrase

“you know”

Negotiating topics Keep the discourse relevant to the topic

(remember Grice’s maxims) Coherence again

Earlier we looked at coherence within a speaker, now we consider it across multiple speakers

Must use statements to signal topic shifts

Closing conversations Closing statements

Must exit from the last topic, mutually agree to close the conversation, and coordinate the disengagement

signal the end of conversation (or topic) “okay”

Justifying why conversation should end “I gotta go”

Reference to potential future conversation “later dude”

Summary “People use language for doing things with

each other, and their use of language is itself a joint action.” Clark (1996, pg387) Conversation is structured

But, that structure depends on more than one individual Models of language use (production and

comprehension) need to be developed within this perspective

Documents

PSY 369: Psycholinguistics Language Production: Models of language production