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 Burton, M. W. (1992, November). Syllable priming in auditory word recognition. Poster presented at the 33rd annual meeting of the Psychonomic Society, St. Louis, MO. Corina, D. P. (1992). Syllable priming and lexical representations: Evidence from experiments and simulations. In Proceedings of the Fourteenth Annual Conference of the Cognitive Science Society (pp. 779-784). Bloomington: Indiana University. Emmorey, K. D. (1989). Auditory morphological priming in the lexicon. Language and Cognitive Processes, 4, 73-92. Gaskell, M. G., & Marslen-Wilson, W. D. (1997). Integrating form and meaning: A distributed model of speech perception. Language and Cognitive Processes, 12, 613-656. Marslen-Wilson, W. D., Moss, H. E., & van Halen, S. (1996). Perceptual distance and competition in lexical access. Journal of Experimental Psychology: Human Perception and Performance, 22, 1376-1392. McClelland, J. L., & Elman, J. L. (1986). Interactive processes in speech recognition: The TRACE model. In J. L. McClelland & D. E. Rumelhart (Eds.), Parallel distributed processing: Explorations in the microstructure of cognition (pp. 58121). Cambridge, MA: Bradford. Radeau, M., Morais, J., & Segui, J. (1995). Phonological priming between monosyllabic spoken words. Journal of Experimental Psychology: Human Perception and Performance, 21, 1297-1311. Slowiaczek, L. M., McQueen, J. M., Soltano, E. G., & Lynch, M. (2000). Phonological representations in prelexical speech processing: Evidence from form-based priming. Journal of Memory and Language, 43, 530-560. Stevens, K. N. (2002). Toward a model for lexical access based on acoustic landmarks and distinctive features. Journal of the Acoustic Society of America, 111, 18721891. Stevens, K. N. (2005). Features in Speech Perception and Lexical Access. In D. B. Pisoni and R. E. Remez (eds.), The handbook of speech perception. Malden, MA: Blackwell. Zwitserlood, P. (1996). Form priming. Language and Cognitive Processes, 11, 589-596.