1. Phonological Encoding II Producingconnectedspeech

2. Producing words: Lecture 2 Lexical Concepts (Lemmas) Word Forms TIGER(X) Tijger

3. Producing words: Lecture 3 Lexical Concepts (Lemmas) Word Forms TIGER(X) Tijger

4. Producing words: Lecture 4 Lexical Concepts (Lemmas) Word Forms Structure Segments TIGER(X) Tijger /t/ /EI/ /x/ /@/ /r/‘s1(on nu coda) s2(on nu coda)

5. So what have got at the end of the day? Lexical Concepts (Lemmas) Word Forms Structure Segments TIGER(X) Tijger /t/ /EI/ /x/ /@/ /r/‘s1(on nu coda) s2(on nu coda)

6. Lecture 5 Lexical Concepts (Lemmas) Word Forms Structure Segments Er…Word Forms TIGER(X) Tijger /t/ /EI/ /x/ /@/ /r/‘s1(on nu coda) s2(on nu coda) ‘s1(on /t/ nu /EI/) s2 (on/x/ nu /@/ coda /r/)

7. Levelt’s paradox All models of phonological encoding distinguish between the retrieval of content (segments) and structure (word or syllable template) Evidence: properties of speech errors But what’s the point to re-order, if you’ve stored the order in the lexicon (word form)? Answer: domain of syllabification (thus, structure) is the phonological word.

8. Phonological word Content morpheme, preceded and/or followed by 0 or more closed class morphemes (e.g., inflections, pronouns). Examples: – + : un der stan ding – + : un der stan der

9. Syllabification Rules Principle of Maximal Onset (Dutch, English) Principle of Minimal Coda (Dutch) Sonority hierarchy (Universal?): the ideal syllable has a maximal rise in sonority in the onset, and a minimal decline in sonority in the coda –Vowels > liquids, nasals, glides > the rest

10. How does it work in Levelt et al (1999)? Word form(s) are retrieved Word forms are spelled out –Spell-out of segments –Spell-out of structure (#sylls and stress) Frames are merged Segments are placed in frames, respecting language-specific rules of syllabification Syllable nodes are retrieved (from a syllabary)

11. Thus: /d/ /i//d/ 1 6... /h//@/ /r/

12. Thus: /d/ /i//d/ 1 6... /h//@/ /r/ W(S S’)W(S)

13. Thus: /d/ /i//d/ 1 6... /h//@/ /r/ W(S S’)W(S) W(S1 S2’ S3)

14. Thus: /d/ /i//d/ 1 6... /h//@/ /r/ W(S S’)W(S) W(S1 S2’ S3) Onset S1

15. Thus: /d/ /i//d/ 1 6... /h//@/ /r/ W(S S’)W(S) W(S1 S2’ S3) Onset S1 Nucleus S1

16. Thus: /d/ /i//d/ 1 6... /h//@/ /r/ W(S S’)W(S) W(S1 S2’ S3) Onset S1 Nucleus S1 Onset S2

17. Thus: /d/ /i//d/ 1 6... /h//@/ /r/ W(S S’)W(S) W(S S’ S) [di][man][d@r] onset coda SYLLABARY

18. Properties of the model The segments connected to the word form are numbered. Numbers specify attachment order. Segments know where to go, and can look at their neighbours. –If I am a vowel: nucleus of next available syllable –If I am a consonant, put me in the onset of the next syllable –If there is no next syllable, put me in the coda of the current syllable.

19. Properties of the model(2) There is a verification mechanism, preventing errors. Thus, if phoneme /d/ is selected, only syllable programs [d*] can be selected. There is a suspension/resumption mechanism, allowing for incrementality. Thus, even if /m/, /ae/, etc., or not selected yet, the model can already build the Phon. Word corresponding to the first syllable.

20. Meyers’ paradox Meyer & Schriefers (1991): Picture/Word interference, with phonological relatedness. –TAFEL with tapir vs jofel –Early SOA: Effect of Begin-relatedness –Late SOA: Effect of END-relatedness Meyer (1990, 1991): Implicit priming with begin and end-homogenous sets: –Lotus, loner, local; murder, ponder, boulder –Effect of Begin-relatedness only.

21. Explanation Explicit priming (p/w interference) speeds up the retrieval of segments. This depends on the time- course of the spoken distractor. Implicit priming does not speed up the retrieval of segments. But the participant, when doing a homogeneous set, can prepare part of the phonological word (suspension/resumption mechanism).

22. The Syllabary Stored programs for entire syllables, specified as sets of articulatory gestures. That is, abstract instructions to the articulators. For example, one such instruction could be to “close the lips” (but not: move upper-lip -8 mms AND move lower-lip + 5 mms, following velocity trajectories v1 and v2). Thus, these instructions are not external context- sensitive.

23. Why a syllabary? Phonetic accomodation in speech errors. If phonemes end up in the wrong place, they are pronounced correctly for their environment: E.g., tab stops -> tap [stabz] (Fromkin, 1971)

24. Why a syllabary (2)? If you do something really often, it is better to store and reuse it than it is to start from scratch. The top 500 sylls (out of roughly 12,000) cover 80% of words in English, 85% in Dutch.

25. Why a syllabary (3)? Levelt & Wheeldon (1994): Frequency effects in word production. Practice phase: Symbol to word association. –%%% = Tiger, ***** = Lotus Test phase: Symbol cue for production –%%%TIGER

26. Why a syllabary (3)? Additive effects of word frequency and syllable frequency Especially frequency of SECOND syllable was important Not reducible to syllabic complexity

27. Why a syllabary (3)? Additive effects of word frequency and syllable frequency Especially frequency of SECOND syllable was important Not reducible to syllabic complexity HOWEVER: there were confounding factors in the experiment. Conclusions should not be taken at face value! (Levelt et al., 1999).

28. What about errors? Weaver++ does not make ANY errors. It always ensures that the selected unit at level n+1 is connected to the selected unit(s) at level n. Errors were simulated, by assuming that this checking mechanism sometimes produces false positives at the level of the syllabary. Thus, target is red sock. If the syllable program [sed] is happy -> anticipation. If [rok] is happy -> persevaration. If both happy, exchange.

29. Exchange rate: sed rock In WEAVER, probability of false positive for [sed] is independent of that for [rok]. Both p’s are extremely small. The p of both occurring is infinitely small => 0% exchanges. In Dell’s model, selected phonemes are turned off. Thus, if /r/ is not selected in word 1, it has an advantage over /s/ for word 2 (because /s/ is set to 0). See also Dell, Burger, & Svic (Psych. Rev. 97)

30. Exchange rate Fromkin (1971) (and Matt, last week): Anticipations could be half-way corrected exchanges! Yew…New York Nooteboom (in press). If we assume detection p is same for anticipation and perseveration, we can estimate the proportion of half-way corrected exchanges.

31. Nooteboom (in press) PAETot Corrected103442?42?587 Not correct153238175566 Total256680?217?1153 22%59%?19%?100% 103: 153 = Acor : 238=> Acor = 160

32. Nooteboom (in press) PAETot Corrected103160324587 Not correct153238175566 Total2563984991153 22%35%43%100%

33. Nooteboom (in press) PAETot Corrected103160324587 Not correct153238175566 Total2563984991153 22%35%43%100% Weaver19%80%1%

34. Conclusions WEAVER++ (as opposed to Dell’s model) accounts for resyllabification in running speech Like Dell’s model, it captures seriality effects It accounts for the paradoxical RT data found in implicit and explicit priming It’s syllable theory is supported by theoretical arguments, but not by conclusive data Unlike Dell’s model, it does not predict the occurrence of exchange errors.