Sonorant ms changes
P 9. "Since comparisons…statistical tests?)" Replace with: Target words in the fricative
and resonant lists were balanced for variables affecting lexical access. t tests showed no
significant difference in word frequency (p=0.68), number of segments (p=0.72), number
of consonants (p=0.97), and uniqueness point (p=0.24). The consonant change occurred
before the uniqueness point in all target words.
Replaced as instructed.
P 10, line 16. I don't know these symbols well enough, but it looks like the featurematching prime has a /b/ replacing the /f/. This is Experiment 1, which focused on
fricatives, so I think the replacing segment should be another fricative, not a stop. Am I
missing something?
The matching pair is rebolve-refolve and the mismatching pair is remolve-refolve. We
did focus on fricatives in this experiment, meaning the critical sound in the *targets* is
always a fricative. The critical sound in the *prime*, however, was either fricative or
stop. These examples were taken from the actual stimulus list we used.
P 12, just before Data Analysis. Should we add:
Many of the target words were of low frequency, and it was possible that participants
might not know some of them. Following the experiment, participants received a
Wordcheck to test whether any target words were unfamiliar to them. The sheet listed 20
phonotactically legal nonwords and the 20 target words having the lowest word
frequencies. Participants were asked to circle all items they thought were not words. If a
participant circled any real words, those words were removed from that participant's data
set.
Appended as instructed.
P 12. Results. We have ANOVAs on both latencies and errors, and those are probably
subject ANOVAs. Most journals also want an ANOVA with items as a random factor, so
I think we need to do these for both latencies and errors. Would you like for me to try to
get Albert to do these?
I do have the item analysis statistics, but none of the results were significant. You’re right
that some reviewers may ask for item analysis, but I’ve seen comments that subject
analysis is more essential because what one cares eventually is whether the effect
generalizes to everyone. Would it make sense if we give item analysis only if we’re asked
to?
P 14. . "Since comparisons…statistical tests?)" Replace with: Target words in the stop
and resonant lists were balanced for variables affecting lexical access. t tests showed no
significant difference in word frequency (p=0.57), number of segments (p=0.45), number
of consonants (p=0.38), and uniqueness point (p=0.74). The consonant change occurred
before the uniqueness point in all target words.
Replaced as instructed.
P 15, line 14. It looks like the target /p/ was replaced by an /s/. Stops were the focus in
this experiment, and I think stops were replaced by other stops in the feature-matching
condition.
Same comment as I made earlier. The critical sound in the primes were not limited to
stops. These examples were taken directly from the actual stimulus set we used
(matching: sertal-pertal; mismatching: nertal-pertal).
P 16. Results. As in Experiment 1, we perhaps should do item analyses on latencies and
errors.
Same comment as I made earlier.
P 17, line 19. Why are sonorants and obstruents different? Your comments here are
quite apt. You might add that vowels have been shown to be appreciably easier to
process in the word reconstruction task, so the vowel-like sonorants may also be easier to
process.
Added to the end of this paragraph.
P 19. Implications for models of spoken word recognition. Three models of spoken
word recognition incorporate feature processors: TRACE (McClelland & Elman, 1986),
the Distributed Cohort Model (Gaskell & Marslen-Wilson, 1997), and Stevens' FeatureBased Model (Stevens, 2002, 2005).
In TRACE, speech input is first assessed by a set of feature detectors. The effect
of a feature mismatch in the prime, as used in the present two experiments, is to reduce
the number of appropriate features activated for the target segment and its target word,
thereby reducing activation of the target word and its probability of being recognized. In
this manner, TRACE explains the effect of feature mismatch when fricatives are targets.
When the targets were stops or resonants, however, there was no effect for feature
mismatch, and TRACE seemingly has no mechanism for explaining that outcome.
The Gaskell and Marslen-Wilson (1997) model is a distributed connectionist
model that represents lexical knowledge in a distributed substrate having abstract
representation of both the forms and meanings of words. Successive sets of distinctive
features, representing connected speech, are input to the model. The identity of the
phonological form of a word is assessed by the goodness of fit between the output
computed by the model and the nearest word entry in the distributed network. The effect
of feature mismatch in the primes, as occurred with fricatives in our Experiment 1, can be
explained by the poorer goodness of fit. When feature mismatch occurred with stops and
resonants, as in our Experiment 2, the model predicts poorer goodness of fit as well, but
the results of the experiment showed no increase in latencies relative to the match
condition.
Stevens' Feature-Based Model estimates distinctive features from the acoustic
properties and landmarks in the speech signal. These features are matched against
ordered bundles of features representing the phonology of words in the mental lexicon.
Word identification occurs when a sequence of estimated features matches a sequence in
the mental lexicon. When a feature mismatch occurs, the latency for identifying a word
should increase, as occurred in the feature mismatch for fricatives in our Experiment 1.
The model does not explain why latencies were unaffected by the feature mismatch
condition for stops and resonants.
Added to general discussion.
Somewhere in the General Discussion, or maybe in the intro, it may be helpful to have a
note on methodology. See what you think about this.
The form-priming task used in these two studies has shown two types of priming.
1. The prime and target overlap at the stimulus onset in one or more segments, using
either words or pseudowords as primes. Priming has been shown with both lexical
decision and naming tasks.
2. The prime and target overlap in the rime of the target word. Rime overlap generally
leads to priming more often than does onset overlap, and pseudoword primes produce
greater facilitation than word primes. Rime priming has been shown with both lexical
decision and naming tasks.
Though form-priming effects are often reported, there are also many reports of
failure to find priming effects (see Zwitserlood, 1996, for a review).
Several studies illustrate these two types of priming. Radeau, Morais and Segui
(1995) used three-phoneme words as both primes and targets in lexical decision and
naming tasks. The primes overlapped the targets in either the first two segments or the
last two segments. Final overlap produced facilitation in both tasks, but initial overlap
produced no facilitation. Slowiaczek, McQueen, Soltano and Lynch (2000) also showed
final overlap priming with monosyllabic words in both naming and continuous lexical
decision tasks. The rime was a major contributor to the priming effect, but the amount of
phonological overlap was also an important contributor.
These two studies used monosyllabic targets, but the targets in our two studies
were 2- and 3-syllable words. Marslen-Wilson, Moss and van Halen (1996, Exp. 1)
showed rime priming with 2- and 3-syllable Dutch words. These words were semantic
mediators to targets in a lexical decision task. Nonword primes to the mediators differed
from the mediators in only the first segment. Emmorey (1989) used pairs of 2-syllable
words in a lexical decision task. Words with a strong-weak syllabic stress pattern (the
pattern in 79% of our 2-syllable words) showed large priming effects when primes and
targets shared the last syllable. Sharing only the rime (vowel plus final consonants) did
not produce priming. Burton (1992) also used 2-syllable primes and targets in lexical
decision and naming shadowing tasks. Both tasks showed facilitation for second syllable
overlap but no effect for initial syllable overlap.
Priming with initial overlap was shown by Corina (1992). Two-syllable items,
overlapping in the first syllable, produced significant priming in a lexical decision task
The present experiments used primes that differed from the targets in only one
segment, showing a mix of onset and rime overlap. As noted in the Method, the target
segment varied in its position in the target word. For 66 (41%) of the words, the target
fell in the onset of the word. This is the condition for rime priming. An additional 12
items (7%) fell in the coda of the second or third syllable. This is the condition for onset
priming. The remaining 83 items fell in the onset of the second or third syllable or the
rime of the first syllable, conditions that do not clearly match the conditions for either
onset or rime priming. ([check ANOVAs for syllable and location analyses. Any
interactions between matching priming and syllable or location?]
Added to general discussion. I also checked the ANOVAs. There was no interaction
between matching and syllable or location.
References
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presented at the 33rd annual meeting of the Psychonomic Society, St. Louis, MO.
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