PSY 369: Psycholinguistics

1. PSY 369: Psycholinguistics Language Production: Theories & Models

2. Announcements • Homework 8 (Due April 29) – Article summary: Griffin & Bock (2000) – using eye-movements to investigate language production processes • “Yes” even with the reduced number of homeworks (11->8), I still plan to drop the lowest grade in this category (so your top 7 homework grades are what will count). • Exam 3 Extra extra credit opportunity: • Up to 30 points added to your exam score • 2 additional journal summaries (due April 29th) • Taft and Hambly (1986) – 15 pts • Perfetti et al (1987) – 15 pts

3. Syntactic level Morphemic level Phonemic level Articulation Nitty-gritty details of the model Message level • General Model of Language Production • 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

4. Two different models Levelt (1989) Dell (1986) TACTIC FRAMES LEXICAL NETWORK

5. Describe this picture 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)

6. Functional processing: • Assignment of roles Grammatical subject Direct object • What’s happening here? • Something is doing something to something Levelt’s model • Formalization on the Syntax side of the model • Works in parallel with the lexicon side

7. S VP NP V NP • How do I structure? • Something is doing something to something Levelt’s model • Formalization on the Syntax side of the model • Works in parallel with the lexicon side • Positional processing: • Build syntactic tree

8. Levelt’s model • Tip of tongue state when lemma is retrieved without word-form being retrieved • Formalization on the Lexicon side of the model • Involves lexical retrieval: • Semantic/syntactic content (lemmas) • Phonological content (lexemes or word-forms)

9. Levelt’s model has stripes is dangerous TIGER (X) Lexical concepts Noun tigre Lemmas Fem. countable /tigre/ Lexemes /t/ /I/ /g/ Phonemes

10. Levelt’s model: conceptual level has stripes is dangerous • Conceptual level is not decomposed • one lexical concept node for “tiger” • instead, conceptual links from “tiger” to “stripes”, etc. TIGER (X) Noun tigre Fem. countable /tigre/ /t/ /I/ /g/

11. Levelt’s model: meaning & syntax has stripes is dangerous • First, lemma activation occurs • This involves activating a lemma or lemmas corresponding to the concept • thus, concept TIGER activates lemma “tiger” TIGER (X) Noun tigre Fem. countable /tigre/ /t/ /I/ /g/

12. Levelt’s model: meaning & syntax has stripes is dangerous • First, lemma activation occurs • This involves activating a lemma or lemmas corresponding to the concept • thus, concept TIGER activates lemma “tiger” TIGER (X) LION (X) Noun • But also involves activating other lemmas • TIGER also activates LION (etc.) to some extent • and LION activates lemma “lion” tigre lion Fem. /tigre/ /t/ /I/ /g/

13. Levelt’s model: meaning & syntax has stripes is dangerous • First, lemma activation occurs • Second, lemma selection occurs • 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 TIGER (X) LION (X) Noun tigre lion Fem. /tigre/ /t/ /I/ /g/

14. Morpho-phonological encoding(and beyond) • The lemma is now activates 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 has stripes is dangerous TIGER (X) Noun countable tigre Fem. /tigre/ /t/ /I/ /g/

15. Model’s assumptions • Serial and Discrete • 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

16. 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

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

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

19. Dell’s interactive account Dell (1986) • these send activation back to the word level, activating words containing these sounds (e.g., “log”, “dot”) to some extent FURRY BARKS MAMMAL • e.g., the semantic features mammal, barks, four-legs activate the word “dog” • this activates the sounds /d/, /o/, /g/ dot dog log /t/ /d/ /g/ /a/ /l/ this activation is upwards (phonology to syntax) and wouldn’t occur in Levelt’s account

20. Model comparisons Similar representations Frames and slots Insertion of representations into the frames Levelt’s Similarities Dell’s Serial Discrete External monitor (comprehension) Interactive Cascaded Differences

21. 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

22. Experimental tests • 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 tiger

23. Experimental tests • Semantic interference • Meaning related words can slow down naming the picture • e.g., the word TIGER in a picture of a LION • Picture-word interference task tiger

24. Experimental tests • Form-related words can speed up processing • e.g., the word liar in a picture of a LION • Picture-word interference task • Semantic interference liar

25. Experimental tests • Experiments manipulate timing: • picture and word can be presented simultaneously liar liar liar time • or one can slightly precede the other • We draw inferences about time-course of processing

26. Evidence against interactivity • 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

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

28. Evidence against interactivity Schriefers, Meyer, and Levelt (1990) • Also looked for any evidence of a mediatedpriming effect DOG (X) CAT (X) dog cat hat /cat/ /hat/ • Found no evidence for it /k/ /a/ /t/ /h/

29. Interpretation • 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

30. Evidence for interactivity • Speech errors: 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 “rat, uh… I mean cat”

31. 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 animate mammalian fur tail RAT (X) CAT (X) rat cat /cat/ /hat/ /rat/ /r/ /k/ /ae/ /t/ /h/

32. 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)

33. 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

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

35. Evidence for interactivity • Damian & Martin (1999) couch (unrelated) peach (semantically related) apathy (phonologically related) apricot (sem & phono related) • early semantic inhibition • late phonological facilitation (0 and + 150 ms)

36. Evidence for interactivity • Damian & Martin (1999) couch (unrelated) peach (semantically related) apathy (phonologically related) apricot (sem & phono related) • early semantic inhibition • late phonological facilitation (0 and + 150 ms) • Shows overlap, unlike Schriefers et al.

37. dance 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

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

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

40. Evidence for interactivity • Cutting and Ferreira (1999) • Early semantic inhibition • Early Facilitation from a phonologically mediated distractor • Evidence of cascading information flow (both semantic and phonological information at early SOA)

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

42. 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

43. soda Evidence for interactivity Peterson & Savoy (1998) • Used pictures with two synonymous names Subordinate Dominant • Used words that were phonologically related to the non dominant name of the picture sofa couch

44. 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?

45. 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

46. Overall summary • 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

47. 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.

48. 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.

49. 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?

50. 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.