View
215
Download
0
Category
Tags:
Preview:
Citation preview
PSY 369: Psycholinguistics
Language Production:Speech errors cont.
Announcements Homework 7 (Due April 22) Try to be vigilant for four or five days in noting speech errors
made by yourself and others. Write each slip down (carry a small notebook and pencil with you). Then, when you have accumulated a reasonably size sample (aim for 20 to 30, but don't panic if you don't get that many), try to classify each slip in terms of
the unit(s) involved the type of error
Remember that each error may be interpreted in different ways. For some of them, see if you can come up with more than one possibility.
Announcements
Exam 3 Average was 64.2% Negatively skewed
distribution Range was very broad,
max = 92% Min = 36%
30’s 40’s 50’s 60’s 70’s 80’s 90’s
1
2
3
4
5
Extra extra credit opportunity: Up to 30 points added to
your exam score 2 additional journal
summaries (due April 29th)
In resources part of ReggieNet Taft and Hambly (1986) – 15 pts Perfetti et al (1987) – 15 pts
Logic: how the system breaks down, tells us something about how it works
Speech can go wrong in many ways Different sized units can slip The ways that they go wrong are not random
Look for regularities in the patterns of errors
It is not always easy to categorize errors
Speech error regularities What can we learn from speech errors?
Speech errors Frequency of units in errors
Different sized units can slip Suggestions of “building blocks” of production
Estimates of frequencies of linguistic units in exchange errors (Bock, 1991)
10% 20% 30% 40%
Sentence
> SyllableSyllable
VC or CVCluster
PhonemeFeature
PhraseWord
Morpheme
From this we can infer that– Speech is planned in advance. – Accommodation to the phonological environment takes place
(plural pronounced /z/ instead of /s/).– Order of processing is
– Selection of morpheme error application of phonological rule
Speech error regularities What can we learn from speech errors?
If we look at this error (a shift or is this an exchange?)
“a maniac for weekends.” FOR “a weekend for maniacs.”
Stress exchange:
What can we learn from speech errors?
Speech error regularities
econ 'om ists FOR e ’con omists
From this we can infer that– Stress may be independent and may simply move from one
syllable to another (unlikely explanation).– The exchange may be the result of competing plans
resulting in a blend of
e ’con omists and econ 'omics.
Is this a double substitution (/b/ for /p/ and /t/ for /d/)?– /p/ and /t/ are vocieless plosives and /b/ and /d/ voiced
plosives– Better analysed as a shift of the phonetic feature voicing.
What can we learn from speech errors?
Speech error regularities
From this we can infer that Indicates that phonetic features are psychologically real -
phonetic features must be units in speech production.
“bat a tog” FOR “pat a dog”
Consonant-vowel rule: consonants never exchange for vowels or vice versa
Suggests that vowels and consonants are separate units in the planning of the phonological form of an utterance.
Errors produce legal non-words. Suggests that we use phonological rules in production.
Lexical bias effect: spontaneous (and experimentally induced) speech errors are more likely to result in real words than non-words.
Grammaticality effect: when words are substituted or exchanged they typically substitute for a word of the same grammatical class
What can we learn from speech errors?
Speech error regularities
Observed regularities
That speech is planned in advance - anticipation and exchange errors indicate speaker has a representation of more than one word.
Substitutions suggest that the lexicon is organised phonologically and semantically.
Strong grammatical component: Appear to occur after syntactic organization as substitutions are always from the same grammatical class (noun for noun, verb for verb etc.).
External influences – situational context may also influence speech production.
Environmental intrusions (e.g., Harley, 1990) “My bill is gone” for “my mind is gone” while looking at college
bill.
Speech error regularities What can we learn from speech errors?
Implications for theories of language production
Problems with speech errors Not an on-line technique. We only remember (or notice) certain types of
errors. People often don’t (notice or) write down errors
which are corrected part way through the word, e.g. “wo..wring one”.
Even very carefully verified corpora of speech errors tend to list the error and then “the target”.
However, there may be several possible targets. Saying there is one definitive target may limit
conclusions about what type of error has actually occurred.
Evidence that we are not very good at perceiving speech errors.
Problems with speech errors
How well do we perceive speech errors? Ferber (1991)
Problems with speech errors
Did you hear what he said?!
The tapes were played to subjects whose task was to record all the errors they heard.
The errors spotted by the subjects were compared with those that actually occurred.
Method: Transcripts of TV and radio were studied very carefully
to pick out all the speech errors.
Problems with speech errors
Results: Subjects missed 50% of all the errors And of the half they identified
50% were incorrectly recorded (i.e. only 25% of speech errors were correctly recorded).
Conclusion: We are bad at perceiving errors.
How well do we perceive speech errors? Ferber (1991)
Experimental approaches Not prey to same problems as observational
studies: Reduces observer bias Isolates phenomenon of interest Increases potential for systematic observation
Different problems! How to control input and output? Input: ecological validity problem (‘controlling thoughts’) Output: controlling responses:
Response specification - artificiality ‘Exuberant responding’ – loss of data
Experimental speech errors Can we examine speech errors in under more
controlled conditions? SLIP technique: speech error elicitation technique
Motley and Baars (1976)
Task: Say the words silently as quickly as you canSay them aloud if you hear a ring
dog bone
dust ball
dead bug
doll bed
barn door
“darn bore”
dog bonedust balldead bugdoll bed
• This technique has been found to elicit 30% of predicted speech errors.
• Lexical Bias effect: error frequency affected by whether the error results in real words or non-words
Experimental speech errors
“wrong loot” FOR “long root”
“rawn loof” FOR “lawn roof “
Some basic findings
More likely
Influence of semantics (Motley, 1980)
Experimental speech errors
Hypothesis: If preceded by phonologically and semantically
biasing material (PS) If preceded by only phonologically biasing material
(P).
Some basic findings
Predicted to be more likely
Influence of semantics (Motley, 1980)
Experimental speech errors
Method: 2 matched lists 20 word pairs as targets for errors
e.g. bad mug mad bug Each preceded by 4 - 7 neutral “filler”
word pairs
Some basic findings
mashed bunsmangy bears
Then 4 interference word pairs 2 phonological PLUS
2 semantic (SP)
angry insect
ornery fly
angled inset
older flu
or semantically neutral controls (P)
bad mug
small catsrainy daysred cars
Results: More errors in the Semantic and Phonological (SP) condition than in the Phonological (P) condition.
Conclusion: Semantic interference may contribute to a distortion of the
sound of a speaker’s intended utterance
Experimental speech errors
Influence of semantics (Motley, 1980)
Some basic findings
Experimental Freudian slips? Motley & Baars (1979)
Hypothesis: Spoonerisms more likely when the resulting content is congruous with the situational context.
Method: 90 males, same procedure previously used by Motley, 1980 (SLIP).
3 Conditions: “Electricity” - expecting to get shocked “Sex” - researcher provocatively attired female Neutral
Same word pairs in all conditions spoonerism targets were non-words (e.g. goxi furl
foxy girl), targets preceded by 3 phonologically biasing word pairs not semantically related to target words
Some resulting errors were sexually related (S), some were electrically related (E)
Bine foddy -> “fine body” Had bock -> “bad shock”
Experimental Freudian slips?
car tires
cat toys
can tops
cup trays
tool kits
“cool tits”
Results (number of errors, by type): Electricity set: 69 E, 31 S Sex set: 36 E, 76 S Neutral set: 44 E, 41 S
Hence errors were in the expected direction. Conclusion: subjects’ speech encoding systems are
sensitive to semantic influences from their situational cognitive set.
Experimental Freudian slips?
Hypothesis: subjects with high levels of sex anxiety will make more “sex” spoonerisms than those with low sex anxiety.
Method: 36 males selected on the basis of high, medium, & low sex
anxiety (Mosher Sex-Guilt Inventory). SLIP task same as previous experiment but with 2 additional
Sex targets and 9 Neutral targets.
Experimental Freudian slips?
Results: looked at difference scores (Sex - Neutral) High sex anxiety > medium > low. Overall: Sex spoonerisms > Neutral spoonerisms.
Conclusion: appears to support Freud’s view of sexual anxiety being revealed in Slips of the Tongue
BUT: the experimenters (Baars and Motley) went on to show that any type of anxiety, not just sexual produced similar results.
SO: anxiety was at play but it was more general, so the priming
was more global.
Experimental Freudian slips?
Many of the same effects found in naturalistic errors are found in experimental errors
Lexical Bias effect: error frequency affected by whether the error results in real words or non-words (Motley & Baars, 1976)
Motley, (1980a) Semantic effects on phonological exchange speech errors
Can isolate particular factors and get a lot of errors This technique has been found to elicit 30% of predicted
speech errors. (Motley & Baars, 1976) Motley, (1980b) Situational contexts can affect frequency
and type of error
Experimental speech errors Some basic findings
From thought to speech
Jane threw the ball to Bill
General Model of Language Production
What do speech errors suggest? Fromkin (1971) Garrett (1975)
(And experiments too)
From thought to speech General Model of Language Production
Ordered sequence of independent planning units
Four levels of processing are typically proposed
Typically they are ordered this way (but there is debate about the independence of the different levels)
Note the similarity to models of comprehension
Message level
Morphemic level
Syntactic level
Phonemic level
Articulation
From thought to speech Propositions to be communicatedMessage level
Morphemic level
Syntactic level
Phonemic level
Articulation
Selection and organization of lexical items
Morphologically complex words are constructed
Sound structure of each word is built
From thought to speech Propositions to be communicatedMessage level
Syntactic level
Morphemic level
Phonemic level
Articulation
Not a lot known about this step Typically thought to be shared with
comprehension processes, semantic networks, situational models, etc.
From thought to speech Grammatical class constraint
Most substitutions, exchanges, and blends involve words of the same grammatical class
Slots and frames A syntactic framework is constructed, and
then lexical items are inserted into the slots
Message level
Syntactic level
Morphemic level
Phonemic level
Articulation
From thought to speech
It was such a happy moment when Ross
kissed Rachel…
Ross
Em
ily
Rachel
From thought to speech
… Oops! I mean “kissed Emily.”
Ross
Em
ily
Rachel
From thought to speech
LEXICON
•ROSS
•KISS
•EMILY
•RACHEL
SYNTACTIC FRAME
NP
S
VP
V(past) NN
Spreading activation
From thought to speech
LEXICON
•ROSS
•KISS
•EMILY
•RACHEL
SYNTACTIC FRAME
NP
S
VP
V(past) NN
Grammatical class constraint:
If the word isn’t the right grammatical class, it won’t “fit” into the slot.
From thought to speech Grammatical class constraint
Most substitutions, exchanges, and blends involve words of the same grammatical class
Slots and frames A syntactic framework is constructed, and
then lexical items are inserted into the slots Other evidence
Syntactic priming
Message level
Syntactic level
Morphemic level
Phonemic level
Articulation
Hear and repeat a sentence
Describe the picture
Bock (1986): syntactic persistance tested by picture naming
Syntactic priming
a: The ghost sold the werewolf a flowerb: The ghost sold a flower to the werewolf
Bock (1986): syntactic persistance tested by picture naming
Syntactic priming
b: The girl gave the flowers to the teacher
a: The girl gave the teacher the flowers
Syntactic priming In real life, syntactic priming seems to
occur as well Branigan, Pickering, & Cleland (2000):
Speakers tend to reuse syntactic constructions of other speakers
Potter & Lombardi (1998): Speakers tend to reuse syntactic constructions of
just read materials
From thought to speech
The inflection stayed in the same location, the stems moved
Inflections tend to stay in their proper place
Do not typically see errors like
The beeing are buzzesThe bees are buzzing
Message level
Syntactic level
Morphemic level
Phonemic level
Articulation
Stranding errors
I liked he would hope you
I hoped he would like you
From thought to speech
Closed class items very rare in exchanges or substitutions
Two possibilities Part of syntactic frame High frequency, so lots of practice,
easily selected, etc.
Message level
Syntactic level
Morphemic level
Phonemic level
Articulation
Stranding errors
From thought to speech
Message level
Syntactic level
Morphemic level
Phonemic level
Articulation
Consonant vowel regularity Consonants slip with other
consonants, vowels with vowels, but rarely do consonants slip with vowels
The implication is that vowels and consonants represent different kinds of units in phonological planning
From thought to speech
Message level
Syntactic level
Morphemic level
Phonemic level
Articulation
Consonant vowel regularity Frame and slots in syllables
Similar to the slots and frames we discussed with syntax
From thought to speech
LEXICON
•/d/, C
•/g/, C
• , VOnset
Word
Rhyme
V CC
PHONOLOGICAL FRAME
Syllable
From thought to speech
Message level
Syntactic level
Morphemic level
Phonemic level
Articulation
Consonant vowel regularity Frame and slots in syllables Evidence for the separation of meaning
and sound
Tip of the tongue Picture-word interference
An instrument used by navigators for measuring the angular distance of
the sun, a star, etc. from the horizon
Tip-of-the-tongue
Uhh…It is a.. You know.. A.. Arggg.I can almost see it, it has two
Syllables, I think it starts with A …..
TOT Meaning access No (little) phonological
access What about syntax?
Tip-of-the-tongue
“The rhythm of the lost word may be there without the sound to clothe it; or the evanescent sense of something which is the initial vowel or consonant may mock us fitfully, without growing more distinct.” (James, 1890, p. 251)
Tip-of-the-tongue
Low-frequency words (e.g., apse, nepotism, sampan), prompted by brief definitions.
On 8.5% of trials, tip-of-the-tongue state ensued:
Had to guess: word's first or last letters the number of syllables it contained which syllable was stressed
Brown & McNeill (1966)
Tip-of-the-tongue
Total of 360 TOT states: 233 ="positive TOTs" (subject was thinking of target
word, and produced scorable data 127 = "negative TOTs" (subject was thinking of other
word, but could not recall it) 224 similar-sound TOTs (e.g., Saipan for sampan)
48% had the same number of syllables as the target 95 similar-meaning TOTs (e.g., houseboat for
sampan). 20% had same number of syllables as target.
Tip-of-the-tongue Brown & McNeill (1966)
Similar words come to mind about half the time but how much is just guessing?
First letter: correct 50-71% of time (vs. 10% by chance) First sound: 36% of time (vs. 6% by chance)
Tip-of-the-tongue
Results suggest a basic split between semantics/syntax and phonology: People can access meaning and grammar
but not pronunciation
Tip-of-the-tongue
Semantics Syntax
grammatical category (“part of speech”) e.g. noun, verb, adjective
Gender e.g. le chien, la vache; le camion, la voiture
Number e.g. dog vs. dogs; trousers vs. shirt
Count/mass status e.g. oats vs. flour
Tip-of-the-tongue
Vigliocco et al. (1997) Subjects (Italian speakers) presented with word definitions
Gender was always arbitrary If unable to retrieve word, they answered
How well do you think you know the word? Guess the gender Guess the number of syllables Guess as many letters and positions as possible Report any word that comes to mind
Then presented with target word Do you know this word? Is this the word you were thinking of?
Tip-of-the-tongue
Vigliocco et al (1997)
Scoring + TOT
Both reported some correct information in questionnaire
And said yes to recognition question - TOT
Otherwise
Vigliocco et al. (1997)
Vigliocco et al (1997)
Results + TOT: 84% correct gender guess - TOT: 53% correct gender guess
chance level Conclusion
Subjects often know grammatical gender information even when they have no phonological information
Supports split between syntax and phonology in production
Vigliocco et al. (1997)
Nitty-gritty details of the model
Message level
Morphemic level
Syntactic level
Phonemic level
Articulation
Central questions: How many levels are there? Are the stages discrete or cascading?
Discrete: 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
Doing it in time Strongest constraint may be fluency:
Have to get form right under time pressure.
Incrementality: ‘Work with what you’ve got’ Flexibility: allows speaker to say something quickly, also
respond to changing environment.
Modularity: ‘Work only with what you’ve got’ Regulate flow of information.
Two different models
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)
Formalization on the Syntax side of the model
Works in parallel with the lexicon side
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 side
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
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)
has stripes is dangerous
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”
has stripes is dangerous
/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”
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/
has stripes is dangerous
TIGER (X)
Fem.
Noun
tigre
Levelt’s model: meaning & syntax
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/
has stripes is dangerous
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/
has stripes is dangerous
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
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”
TACTIC FRAMES LEXICAL NETWORK
Dell’s interactive account
as well as “downwards”
info
rmat
ion
inform
ation
Interactive because information flows “upwards”
Dell (1986)
Cascading because processing at lower levels can start early
TACTIC FRAMES LEXICAL NETWORK
Dell’s interactive account
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/
Dell’s interactive account
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
Evidence against interactivity
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
Evidence against interactivity
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
Evidence for interactivity
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)
Evidence for interactivity
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
Evidence for interactivity
Damian & Martin (1999)
early semantic inhibition
couch (unrelated)
peach (semantically related)
apathy (phonologically related)
apricot (sem & phono related)
Evidence for interactivity
Damian & Martin (1999)
late phonological facilitation (0 and + 150 ms)
early semantic inhibition
couch (unrelated)
peach (semantically related)
apathy (phonologically related)
apricot (sem & phono related)
Evidence for interactivity
Damian & Martin (1999)
late phonological facilitation (0 and + 150 ms)
Shows overlap, unlike Schriefers et al.
early semantic inhibition
couch (unrelated)
peach (semantically related)
apathy (phonologically related)
apricot (sem & phono related)
Evidence for interactivity
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
Evidence for interactivity
ball
BALL (X) BALL (X)
ball
/ball/
DANCE (X)
dance
GAME (X)
game
Cascading Prediction: dance ball /ball/
Cutting and Ferreira (1999)
Evidence for interactivity
Early semantic inhibition
Cutting and Ferreira (1999)
Evidence for interactivity
Early Facilitation from a phonologically mediated distractor
Early semantic inhibition
Cutting and Ferreira (1999)
Evidence of cascading information flow (both semantic and phonological information at early SOA)
Evidence for interactivity
Peterson & Savoy (1998) Slightly different task
Prepare to name the picture
If “?” comes up name it?
Evidence for interactivity
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
Evidence for interactivity
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
Evidence for interactivity
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?
Evidence for interactivity
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 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.
Conversational interaction 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.
Conversational interaction 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’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?
Conversational interaction ABBOTT: The Word in Office for Windows. COSTELLO: But there are three words in "office for windows"! ABBOTT: No, just one. But it’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.
Conversational interaction 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".
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 Fillmore (1981)
“The language of face-to-face conversation is the basic and primary use of language”
(pg. 152)
So all instances of language usage can (should) be compared to conversation
What is the impact of the presence or absence of different features of face-to-face conversation?
Conversation Herb Clark (1996)
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
Conversation Herb Clark (1996)
Joint action Autonomous actions
Things that you do by yourself Participatory actions
Individual acts only done as parts of joint actions 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
Conversation Herb Clark (1996)
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
Conversation Herb Clark (1996)
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
Conversation Herb Clark (1996)
Arena’s of language use - places where people do things with language
Meaning and understanding Establishing Common Ground
Identifying participants Layers Conversation is structured
Meaning and understanding Common ground
Common ground is necessary to coordinate speaker’s meaning with listener’s understanding
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
Lack of successful communication was due to lack of common ground Starting around 1:20
EavesdropperAll listeners
Identifying participants Conversation often takes place in situations that involve
various types of participants and non-participants
BystanderSide
participantsAll participants
Speaker Addressee
EavesdropperAll listeners
Identifying participants
BystanderSide
participantsAll participants
Speaker Addressee
Humor come in part because we (eavesdroppers) share common ground that Lou and Bud didn’t)
Layers Conversations may have several layers
Layer 1 The primary conversation
Layer 2 A commentary about Layer 1
Each layer needs to be coherent (within the layer) as well as be connected to other layers in a relevant way
Layer 2: “I'm going to click your blue "w" if you don't start with some straight
answers. OK, forget that.”
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
Opening the conversation Identifying participants Taking turns Negotiating topics Closing conversations
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
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
Opening the 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
Exchanging information
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
Exchanging a message
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: byeClosing the conversation
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?
Need to pick who starts Turn taking is typically not decided upon in advance Potentially a lot of ways to open
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
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!)
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)
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”
Dialog is the key Why so little research on dialog?
Most linguistic theories were developed to account for sentences in de-contextualized isolation
Dialog doesn’t fit the competence/performance distinction well
Hard to do experimentally Conversations are interactive and largely unplanned
Pickering and Garrod (2004) Proposed that processing theories of language
comprehension and production may be flawed because of a focus on monologues
Processing models of dialog Pickering and Garrod (2004)
Interactive alignment model Alignment of situation
models is central to successful dialogue
Alignment at other levels is achieved via priming
Alignment at one level can lead to alignment at another
Model assumes parity of representations for production and comprehension
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
Recommended