2. PSY 369: Psycholinguistics Language Production: Speech errors cont.

3. 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.

4. Announcements Exam 3 Average was 64.2% Negatively skewed distribution Range was very broad, max = 92% Min = 36% 30’s40’s50’s60’s70’s80’s90’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 29 th ) In resources part of ReggieNet Taft and Hambly (1986) – 15 pts Perfetti et al (1987) – 15 pts

5. 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

6. 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 > Syllable Syllable VC or CV Cluster Phoneme Feature Phrase Word Morpheme

7. 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.”

8. 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.

9. 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”

10. 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

11. 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

12. 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”.

13. 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

14. 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.

15. 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)

16. 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

17. Experimental speech errors Can we examine speech errors in under more controlled conditions? SLIP technique: speech error elicitation technique Motley and Baars (1976)

18. Task: Say the words silently as quickly as you can Say them aloud if you hear a ring

19. dog bone

20. dust ball

21. dead bug

22. doll bed

23. barn door “darn bore” dog bone dust ball dead bug doll bed

24. 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

25. 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

26. 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 buns mangy 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 cats rainy days red cars

27. 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

28. 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

29. 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?

31. car tires

32. cat toys

33. can tops

34. cup trays

35. tool kits “cool tits”

36. 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?

37. 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?

38. 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?

39. 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

40. 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)

41. 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 levelSyntactic level Phonemic level Articulation

42. From thought to speech Propositions to be communicated Message level Morphemic levelSyntactic level Phonemic level Articulation Selection and organization of lexical items Morphologically complex words are constructed Sound structure of each word is built

43. From thought to speech Propositions to be communicated Message 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.

44. 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

45. From thought to speech It was such a happy moment when Ross kissed Rachel… Ross Emily Rachel

46. From thought to speech … Oops! I mean “kissed Emily.” Ross Emily Rachel

47. From thought to speech LEXICON ROSS KISS EMILY RACHEL SYNTACTIC FRAME NP S VP V(past)NN Spreading activation

48. 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.

49. 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

50. Hear and repeat a sentence Describe the picture  Bock (1986): syntactic persistance tested by picture naming Syntactic priming

51.  a: The ghost sold the werewolf a flower  b: 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

52. 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

53. 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 buzzes The 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

54. 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

55. 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

56. 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

57. From thought to speech LEXICON /d/, C /g/, C, V Onset Word Rhyme VCC PHONOLOGICAL FRAME Syllable

58. 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

59. An instrument used by navigators for measuring the angular distance of the sun, a star, etc. from the horizon Tip-of-the-tongue

60. 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

61. “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

62. 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

63. 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)

64. 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

65. Results suggest a basic split between semantics/syntax and phonology: People can access meaning and grammar but not pronunciation Tip-of-the-tongue

66. 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

67. 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

68. 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)

69. 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)

70. Nitty-gritty details of the model Message level Morphemic levelSyntactic 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

71. 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.

72. Two different models TACTIC FRAMESLEXICAL NETWORK Dell (1986)Levelt (1989)

73. 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)

74. 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

75. 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 VNP

76. 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

77. has stripesis dangerous TIGER (X) Fem. Noun countable tigre /tigre/ /t//I//g/ Lexical concepts Lemmas Lexemes Phonemes Levelt’s model (see chpt 5, pg 115-117)

78. has stripesis 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

79. 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 stripesis dangerous /tigre/ /t//I//g/ countable

80. 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 stripesis dangerous

81. 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 stripesis dangerous

82. 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 stripesis dangerous Fem. Nouncountable tigre TIGER (X)

83. 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

84. 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

85. Dell (1986) A moment in the production of: “Some swimmers sink” TACTIC FRAMESLEXICAL NETWORK Dell’s interactive account

86. as well as “downwards” information Interactive because information flows “upwards” Dell (1986) Cascading because processing at lower levels can start early TACTIC FRAMESLEXICAL NETWORK Dell’s interactive account

87. 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 FURRYBARKS doglog /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

88. 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

89. 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

90. 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

91. 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

92. 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

93. 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

94. 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

95. Schriefers, Meyer, and Levelt (1990) DOT phonologically related CAT semantically related SHIP unrelated word Early Only Semantic effects Late Only Phonological effects Evidence against interactivity

96. 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

97. 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

98. 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

99. 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

100. 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

101. 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

102. Damian & Martin (1999) early semantic inhibition couch (unrelated) peach (semantically related) apathy (phonologically related) apricot (sem & phono related) Evidence for interactivity

103. 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

104. 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

105. 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

106. ball BALL (X) ball /ball/ DANCE (X) dance GAME (X) game Cascading Prediction:danceball/ball/ Cutting and Ferreira (1999) Evidence for interactivity

107. Early semantic inhibition Cutting and Ferreira (1999) Evidence for interactivity

108. 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

109. Peterson & Savoy (1998) Slightly different task Prepare to name the picture If “?” comes up name it ? Evidence for interactivity

110. 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

111. Peterson & Savoy (1998) Used pictures with two synonymous names Used words that were phonologically related to the non dominant name of the picture sofacouch DominantSubordinat e soda Evidence for interactivity

112. 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

113. 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

114. 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

115. 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.

116. 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.

117. 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?

118. 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.

119. 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".

120. Conversational interaction “the horse raced past the barn” Conversation is more than just two side-by- side monologues. “the kids swam across the river”

121. 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?”

122. 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?

123. 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 ImmediacyMediumControl Other settings may lack some of these features e.g., telephone conversations take away co-presence and visibility, which may change language use

124. 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

125. 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

126. Conversation Herb Clark (1996) Speaking and listening Component actions in production and comprehension come in pairs SpeakingListening 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

127. 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

128. 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

129. EavesdropperAll listeners Identifying participants Conversation often takes place in situations that involve various types of participants and non- participants Bystander Side participants All participants Speaker Addressee

130. EavesdropperAll listeners Identifying participants Bystander Side participants All participants Speaker Addressee Humor come in part because we (eavesdroppers) share common ground that Lou and Bud didn’t)

131. 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.”

132. 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

133. 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

134. 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

135. 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

136. 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

137. 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 Closing the conversation

138. 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

139. 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

140. 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

141. 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)

142. 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”

143. 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

144. 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”

145. 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

146. 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

147. 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