phonological encoding ii producingconnectedspeech
TRANSCRIPT
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Phonological Encoding II
Producingconnectedspeech
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Producing words: Lecture 2
Lexical Concepts
(Lemmas)
Word Forms
TIGER(X)
Tijger
<Tijger>
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Producing words: Lecture 3
Lexical Concepts
(Lemmas)
Word Forms
TIGER(X)
Tijger
<Tijger>
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Producing words: Lecture 4
Lexical Concepts
(Lemmas)
Word FormsStructureSegments
TIGER(X)
Tijger
<Tijger>
/t/ /EI/ /x/ /@/ /r/ ‘s1(on nu coda) s2(on nu coda)
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So what have got at the end of the day?
Lexical Concepts
(Lemmas)
Word FormsStructureSegments
TIGER(X)
Tijger
<Tijger>
/t/ /EI/ /x/ /@/ /r/ ‘s1(on nu coda) s2(on nu coda)
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Lecture 5
Lexical Concepts
(Lemmas)
Word FormsStructureSegments
Er…Word Forms
TIGER(X)
Tijger
<Tijger>
/t/ /EI/ /x/ /@/ /r/ ‘s1(on nu coda) s2(on nu coda)
‘s1(on /t/ nu /EI/) s2 (on/x/ nu /@/ coda /r/)
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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.
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Phonological word
• Content morpheme, preceded and/or followed by 0 or more closed class morphemes (e.g., inflections, pronouns).
• Examples:– <understand> + <ing>: un der stan ding
– <understand> + <er>: un der stan der
– <understand> + <her>: un der stan der
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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
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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)
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Thus:
<demand> <her>
/d/ /i/ /d/
16
... /h/ /@/ /r/
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Thus:
<demand> <her>
/d/ /i/ /d/
16
... /h/ /@/ /r/W(S S’) W(S)
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Thus:
<demand> <her>
/d/ /i/ /d/
16
... /h/ /@/ /r/W(S S’) W(S)
W(S1 S2’ S3)
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Thus:
<demand> <her>
/d/ /i/ /d/
16
... /h/ /@/ /r/W(S S’) W(S)
W(S1 S2’ S3)OnsetS1
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Thus:
<demand> <her>
/d/ /i/ /d/
16
... /h/ /@/ /r/W(S S’) W(S)
W(S1 S2’ S3)OnsetS1
NucleusS1
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Thus:
<demand> <her>
/d/ /i/ /d/
16
... /h/ /@/ /r/W(S S’) W(S)
W(S1 S2’ S3)OnsetS1
NucleusS1
OnsetS2
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Thus:
<demand> <her>
/d/ /i/ /d/
16
... /h/ /@/ /r/W(S S’) W(S)
W(S S’ S)
[di] [man] [d@r]
onsetonset
coda
SYLLABARY
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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.
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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.
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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.
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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).
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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.
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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)
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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.
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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
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Why a syllabary (3)?
• Additive effects of word frequency and syllable frequency
• Especially frequency of SECOND syllable was important
• Not reducible to syllabic complexity
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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).
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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.
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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)
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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.
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Nooteboom (in press)
P A E Tot
Corrected 103 442? 42? 587
Not correct 153 238 175 566
Total 256 680? 217? 1153
22% 59%? 19%? 100%
103: 153 = Acor : 238 => Acor = 160
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Nooteboom (in press)
P A E Tot
Corrected 103 160 324 587
Not correct 153 238 175 566
Total 256 398 499 1153
22% 35% 43% 100%
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Nooteboom (in press)
P A E Tot
Corrected 103 160 324 587
Not correct 153 238 175 566
Total 256 398 499 1153
22% 35% 43% 100%
Weaver 19% 80% 1%
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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.