Frequency Effects and the Representational Status of ......Clelland, 1986; Stemberger, 1995) and spel-ling–sound correspondences (Plaut, McClel-land, & Seidenberg, 1996; Seidenberg

Journal of Memory and Language40, 41–61 (1999)Article ID jmla.1998.2607, available online at http://www.idealibrary.com on

Frequency Effects and the Representational Status of Regular Inflections

Maria Alegre and Peter Gordon

University of Pittsburgh

There have been many recent proposals concerning the nature of representations for inflectionalmorphology. One set of proposals addresses the question of whether there is decomposition ofmorphological structure in lexical access, whether complex forms are accessed as whole words, or ifthere is a competition between these two access modes. Another set of proposals addresses thequestion of whether inflected forms are generated by rule-based systems by connectionist typeassociative networks or if there is a dual system dissociating rule-based regular inflections fromassociation-based irregular inflections. A central question is whether there are whole-word represen-tations for regularly inflected forms. A series of five lexical decision experiments addressed thisquestion by looking at whole-word frequency effects across a range of frequency values with constantstem-cluster frequencies. Frequency effects were only found for inflected forms above a threshold ofabout 6 per million, whereas such effects were found for morphologically simple controls in allfrequency ranges. We discuss these data in the context of two kinds of dual models and in relationto competition models proposed within the connectionist literature.© 1999 Academic Press

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Two surprisingly distinct lines of researchpsycholinguistics have addressed the psylogical status of inflectional morphology. Oline of research comes from the field of laguage acquisition and has concentrated oncontrast between regular and irregular infltional forms. The second line of research coout of the adult lexical access literature andconcentrated on how morphologically compforms are represented and how such repretations are accessed.

In comparing these two literatures, one fithat both contain what are called “dual modebut the meanings of the term differ in the tliteratures. Within the acquisition literature,notion of a dual model arose from an evaluaof claims made within the connectionist comunity that rule-like behavior could be emlated within a parallel distributed process(PDP) system that contained no represe

The authors thank David Plaut, Charles Perfetti, AJuffs, David Allbritton, and Carl Johnson for helpful coments, and Carey Ryan for advice on statistical issuespresent study was completed in partial fulfillment fordegree of Doctor of Philosophy at the University of Pburgh by Maria Alegre.

Address correspondence and reprint requests to Petedon, Department of Psychology, University of Pittsbu
Pittsburgh, Pennsylvania 15260. E-mail: [email protected].
41

-

e-ss

n-

”

-

tion of such rules (Rumelhart & McClellan1986). Challenging these claims, Pin(1991) proposed that rule systems arequired for regular inflectional morphologwhereas irregular inflectional morphology ehibits characteristics of an associative/cnectionist network.

Within the adult psycholinguistics literatuthe term “dual model” refers to the access stem for complex morphological forms, bothflectional and derivational. Proponents of thdual models assume that access to comforms can occur either through whole-word rresentations or through morphological decposition (Anshen & Aronoff, 1988; Baaye1991; Burani & Caramazza, 1987; BuraniLaudanna, 1992; Caramazza, Laudanna, &mani, 1988; Caramazza, Miceli, Silveri, & Ladanna, 1985; Chialant & Caramazza, 19Frauenfelder & Schreuder, 1991; LaudanBadecker, & Caramazza, 1989, 1992; Schre& Baayen, 1995; Stemberger & MacWhinn1988). In contrast, single-route models propaccess only through whole-word represetions (Butterworth, 1983; Cole, Beauvillain,Segui, 1989; Cutler, 1983; Emmorey, 19Lukatela, Gligorijevic & Kostic, 1980; Rubin

e

or-

Becker, & Freeman, 1979; Segui & Zubizarreta,

0749-596X/99 $30.00Copyright © 1999 by Academic Press

All rights of reproduction in any form reserved.

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42 ALEGRE AND GORDON

1985). The present study attempts to bringgether some of the issues raised in theselines of inquiry and to test predictions regardthe representations of regularly inflected for

Beginning with the language acquisitionerature, Pinker (1991) proposed that forms wregular inflections (e.g.walked) are handled brule, whereas irregular inflections (e.g.went)are handled by associative memory. To msuch a claim, it is critical to have a clear secriteria for distinguishing between rule-basprocesses and generalizations based on astive principles. According to Pinker, a worformation rule is an abstract operation that ccatenates an affix with a variable standingthe stem (Marcus, Brinkmann, Clahsen, WieWoest, & Pinker, 1993; Pinker, 1991; PinkerPrince, 1991). Rule-based processes aredefault generalizations and apply freely toitems of the right category unless applicatioblocked by a competing irregular form (e.wentblocks the generation of *goed).

On the other hand, irregulars are storedemorized pairs with their stems and their mhological relations. These are linked in anociative structure with certain connectistlike properties (Pinker & Prince, 1991). Trregular system allows some degree of gelization. This is accomplished by exploitiatterns of similarity between irregular formhe more similar a stem is to other frequtems known to undergo irregular inflection,ore likely it is to also undergo such a proceor example, when asked to provide the p

ense form for a nonce verb such asspling,eople are very likely to producesplang—innalogy to spring–sprang, ring–rang, singang, drink–drank,and so on (Bybee & Mode983; Prasada & Pinker, 1993).Productive generalizations based on res

lance to families of stored forms are knowngang effects” (Stemberger & MacWhinne988). The generalization of irregular patte

s highly sensitive to gang effects in both adBybee & Moder, 1983; Prasada & Pink993) and children (Bybee & Slobin, 198arcus, Pinker, Ullman, Hollander, Rosen,u, 1993; Pinker & Prince, 1988; Xu & Pinke
992). On the other hand, gang effects appear r
-o

.

ef

ia-

-r,

usl

s--

r-

t

.t

-

lay no role in the productive generationegular inflections. For example, gangs of rlar forms sharing phonological propertiesot facilitate production of nonce items shar

hose properties, nor do they enhance theeptability of such nonce forms (Prasadainker, 1993; Marcus et al., 1993).These facts notwithstanding, the contrast

ween “rule-based” and “stored” is far frolear. For example, is it the case that onlyegular inflections likesangare representedemory, while regularly inflected forms likalked are never represented in memorasada and Pinker suggest two possibleions of the dual model. In the strong vershere are no whole-word representations oflarly inflected forms. In the weak versioome storage of regularly inflected formsossible. Prasada and Pinker state thatrior storage of regulars is possible, and theright offer mild analogical assistance toeneralization of the regular inflection to sim

ar forms, but generalization never dependsrior storage of a similar form . . .” (Prasada &inker, 1993, p. 9). If the weak version ofual model is to remain consistent with the lf gang effects for regular inflections, then i

undamental that storage be limited to a rively small number of items.

One way to test the two versions of Pinkeodel is to look at frequency effects. If reg

arly inflected forms are not representedhole words, then the base form must beessed every time an inflected word is pessed. Thus, access speed should depehe cluster frequency of the base form, defis the aggregated frequencies of the base a

ts inflectional variants (e.g., forwalk, theummed frequencies ofwalk, walks, walkedndwalking). On the other hand, if whole-woepresentations are available for regularlyected forms, then the frequency of theected form itself should determine access tiTurning to the lexical access literature,

nd a family of dual models. These modhare the assumption that access to morphcally complex forms (inflectional and derivional) can occur through either a whole-w
toepresentation or through a decompositional

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43FREQUENCY EFFECTS

route. These two routes are claimed to worparallel and compete with one another (Ans& Aronoff, 1988; Baayen, 1991; Burani & Caamazza, 1987; Burani & Laudanna, 1992; Camazza et al., 1985; 1988; Chialant & Camazza, 1995; Frauenfelder & Schreuder, 1Laudanna et al., 1989, 1992; SchreudeBaayen, 1995; Stemberger & MacWhinn1988).

The models differ considerably in how eplicit they are and in how they specify tnature of the competition between accroutes. However, there is agreement thatwhole-word access system works faster thanmorpheme access system and will win oumost cases. An exception to this is low-fquency complex forms, especially those whthe constituent morphemes are high inquency. For example, the complex formcleansis very low in whole-word frequency, but tconstituentscleanand -s are each very highrequency. Such forms are predicted to beessed through decomposition rather thanhole-word route. In general, whole-word fuency effects should be obtained for item

he higher end of the frequency distributionot for items in the lower end. The thresholdefining “high” versus “low” frequency has neen specified in any of these models andains an empirical matter to be addressed inresent studies.Dual models, which assume the existenc

ule systems, are challenged by connectiopproaches, which provide alternative pers

ives on many of these issues. In connectioystems, network nodes represent minimal petic and/or semantic units. Weighted conn

ions between nodes capture patterns of rarity in the input. Much of the debate within tonnectionist literature concerns whether rear and irregular processes can be hanithin a single system using associative norks. This discussion addresses the regu

rregular distinction in both morphology (Bee, 1995; MacWhinney & Leinbach, 199lunkett & Marchman, 1991; Rumelhart & Mlelland, 1986; Stemberger, 1995) and s

ing–sound correspondences (Plaut, McC
and, & Seidenberg, 1996; Seidenberg & Mc-
n

-

;

,

see

e-

-e

t

-e

ft-t---

-d-r–

l--

Clelland, 1989). While these models contuniform representations, they produce outpthat distinguish between regular and irregprocesses by exploiting their different distribtional properties.

In the case of morphology, Bybee (199proposed that complex forms are stored inassociative network where recurring phonoical and semantic patterns are representelinks between units. Morphological relationsdefined by parallel phonological and semaconnections found in multiple sets of itemMorphemes do not have any independent sor representation and are considered to bephenomenal. For example, the wordstarted isconnected to the wordstartingthrough the overlapping sequencestart and to the wordwalkedthrough the common endinged. Such multipleconnections allow for rule-like behavioremerge as generalizations over propertiestored items.

In Bybee’s model, activation levels areresult of two factors: lexical strength and lexiconnections. Lexical strength is determinedthe frequency of the lexical item. Lexical conections are the pattern of weights associwith the interconnections between related iteas illustrated above. For high-frequency wolexical strength would be high and wouswamp activation due to lexical connectioLow-frequency words would be weak in lexicstrength and thus rely on lexical connectionsaccess.

Like the dual access model, Bybee’s mopredicts that whole-word frequency effeshould be found only above a certain frequethreshold. However, in Bybee’s model,strength of the frequency effect depends oncomposition of the cluster. The number of ittypes that compose the stem cluster (i.e., sand inflected forms) determines the strengtlexical connections for that cluster. Thereforcluster containing many inflected forms whave strong lexical connections, which wocompete strongly against the individual lexistrength of any inflected form within that cluter. When lexical connections are stronger tlexical strength, then whole-word frequency
fects should be weak to nonexistent. Con-

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versely, when a cluster contains only a smnumber of inflectional types, the connectstrengths are weak and whole-word frequeeffects should be stronger. In other words,bee’s model predicts an interaction betweennumber of inflectional types within a cluster awhole-word frequency effects.

This aspect of the model can be testedcomparing nouns and verbs. Noun paradiare inherently weak, as only two forms, singuand plural, are usually observed. On the ohand, regular verbs usually have four differforms (e.g.,play, plays, playingand played).Thus, for any given cluster frequency valwhole-word frequency effects should be mreadily obtained for nouns than for verbs. Topposite pattern should hold for cluster fquency effects. We will test these predictioagainst the data found in the following stud

Stemberger’s (1995) connectionist modelfers from Bybee’s model in several respectshis model, Stemberger attempted to accounthe lack of frequency effects for regularlyflected forms compared to strong frequencyfects for irregular inflections (StembergerMacWhinney, 1988; Prasada, Pinker, & Sny1990). In the case of regular inflections, lexstrength, based on word frequency, faces stcompetition from lexical connections toother words sharing the same ending (e.g.words ending in -ed). Given that this group

xtremely large, then the strength of theseociations should swamp any activation duhe frequency of the individual inflected woather than predicting a threshold for findin

requency effect for regular inflections, Steerger’s model suggests that no whole-w

requency effects should be found.What does current research tell us about

epresentation of regular inflections? Unfoately, the results are ambiguous. One setudies has used priming to examine the rion between base forms and inflected foFowler, Napps, & Feldman, 1985; Hernonall, 1979; Napps, 1989; Stanners, Neisapps, & Fowler, 1987). Several of these st

es have shown that regularly inflected forrime their base forms as strongly as the b

orms themselves (identity priming). However,e

ll

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,

.

r

-

,lg

ll

-o

e

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e

uch results only show that base forms areivated in the process of accessing regulnflected forms. Such results might be expecnder both a morpheme access system ahole-word access system, if one assumeshole-word representations of related forluster together in the lexicon (Lukatela et980; Butterworth, 1983).Other studies have manipulated frequencway to investigate representational and ac

ssues. Prasada et al. (1990) provided evidgainst the existence of whole-word represe

ions for regularly inflected forms. They useroduction task in which participants were pented with the base form of a verb (e.g.,walk)

and were asked to produce the corresponpast tense form (walked). The items were contructed in pairs matched for cluster frequeut differing in whole-word frequency. For emple, the verbsjump and boil are equally

requent, whereasjumpedis much more comon thanboiled. If the past tense forms accessed through the base form, then no dinces in reaction times are expected. Onther hand, if regularly inflected words are resented as such, and there is no on-line cosition, thenjumpedshould be produced fas

hanboiled.Prasada et al. found no differencn RT for the regularly inflected words. Howver, when irregular forms were tested iname fashion, high-frequency past tense foere produced significantly faster than lo

requency past tense forms. These resultsest that regular inflections are put togethe

ine, while irregular inflections are storedhole words.One problem with the Prasada et al. (19

tudy is their method for computing cluster fuency. They included the frequencies oftem plus the inflectional forms other thanast tense. This is rather unconventional s

he cluster frequency normally includes allectional forms. Presumably the reason forecision was that they were comparing regnd irregular inflections. Irregular inflectiore not normally included in the cluster fuency measure because they are not likee accessed through the stem. However, by
xcluding the regular past tense inflections from

athen iarlheth

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45FREQUENCY EFFECTS

the cluster frequency computation, Prasadal. had items where the word frequency ofpast tense form was sometimes higher thaassociated stem–cluster frequency. If regulinflected forms are accessed through tstems, then they should also contribute toactivation levels associated with the frequeeffect. Another problem in interpreting tPrasada et al. (1990) study is the nature oftask. Since the participants read the stem fbefore producing the past tense form, it issurprising that they would use a compositioroute by adding the past tense morphologycould be the case that whole-word represetions are available for regularly inflected formbut are simply not used under these circstances.

Other studies in this area have employedlexical decision procedure and present a radifferent picture. Taft (1979) and Burani, Smaso, and Caramazza (1984) have lookewhole-word frequency effects in lexical accfor regular inflections. These studies tested pof regularly inflected items where one wordeach pair was high in whole-word frequenand the other was very low, but both wmatched in cluster frequency (stem frequeplus all inflections). Both studies obtainedsignificant whole-word frequency effect, sugesting that regular inflections are storedwhole words, in contrast to Prasada et(1990).

Once again, there are problems with thesign of these studies. In Taft (1979), 9 out oflow-frequency items involved stems that wdenominal verbs (e.g.,classed, numberesized), while none of the high-frequency itemhad derived stems. If denominal verbs are pchologically derived, then this requires two pcesses (zero derivation plus inflection), whwould increase reaction times for many oflow-frequency items. Alternatively, if denomnal verbs are stored separately from their relnoun forms, then Taft’s measure of clusterquency was inaccurate because it includedfrequency of the noun base form as well asverb form, and the noun form tended to bemajor contributor to the cluster frequen
count. In either case, RTs for inflected formst
et

tsyirey

e

tlt-

-

er

at

s

y

s.

-

-

d-ee

based on denominal verbs should be slowgardless of their representational status.

Burani, et al., (1984) failed to find an effeof word frequency using Taft’s procedureItalian. They did find an effect when they moified the design by testing pairs of words tshared the same stem but had different intions (e.g.,sent-ireversussent-ivi). This opti-

ally controls for cluster frequency issuowever, the frequency of the inflected word

ikely to be correlated with the frequency of tffix itself. To use English examples, if we we

o test a low-frequency inflection likecleansersus a high-frequency relative suchleaned,the frequency of the affixes themseli.e., -s vs -ed) would be confounded: past tenorphology is much more frequent than therson-s.Thus, even if bothcleansandcleanedere to be accessed through decomposittaching-edmight take less time than attachs. Once again, differences in RT mightxpected whether inflected words are storeingle units or not.A common problem in previous studies

hat frequency has been treated as a categoariable (high versus low). This may overeate or underestimate the existence of whord frequency effects, depending on whart of the frequency distribution is being saled from. Furthermore, this method cannot

ect discontinuities in frequency effects thatredicted by dual access models. In the preaper, we will describe several experiments

reat frequency as a continuous variable inttempt to provide an unambiguous picture

he representational status of regular inflecti

EXPERIMENT 1

articipants

Thirty-one undergraduate students fromsychology subject pool at the Universityittsburgh participated in the experiment. Innd subsequent experiments, all participompleted the task and all were native speaf English.

aterials

Sixty-six experimental items were selec
o: (a) be regularly inflected, (b) have similar

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stem–cluster frequencies, and (c) be evenlytributed in terms of log word frequency. Clusfrequency ranged from 99 to 122 (log 2 to 2.based on Francis and Kucˇera (1982). This rangs small but not zero and so cluster frequenctill included as a variable in the analysis. Wrequency varied from 0 to 101 (see Appendtems were selected so that word length, sactic category (noun vs verb), and clusteruency had very low correlations among theelves and with respect to the criticxperimental variable: whole-word frequenmin 5 .03; max5 .2). Filler items included 6imple words (not inflected); 66 “inflecteonwords, where an inflectional ending was

ached to a nonce base form (e.g., *pramed);and 66 simple nonwords.

Procedure

Participants performed a lexical decision ton a PC using the Micro Experimental L(MEL) software (Schneider, 1988). After reaing the instructions they began with 40 practrials. They were then tested on the experimtal and filler items, which were presented idifferent random order for each subject. Paripants were allowed 3 1-min breaks duringexperiment.

On each trial, an asterisk appeared inmiddle of the screen for 1.5 s and then an iwas displayed, centered around the asterisksition. Participants were instructed to press“1” key each time they saw a word, and thekey each time they saw a nonword. The pretation of the item was terminated by the sject’s response. If participants took longer th1.5 s to respond, the screen showed a mes“too slow.” Data for such trials were discardThis amounted to 3.3% of the responsesExperiment 1. Also, participants were informif their responses were incorrect with the msage: “wrong answer.”

Results and Discussion

For the item analyses we performed standmultiple regressions. That is, we collapsed dacross subjects and regressed RT on five i
pendent variables: length, category, neighbor
-

)

s

.---

-

-

-

e

o-e

--

e:

n

-

dae-

hood frequency, cluster frequency, and wfrequency.

For the subject analyses, a straightforwMANOVA could not be used because wedealing with continuous variables. The presstudy requires us to capture within-subjectfects using regression analyses. For this, aarate regression equation was estimated forsubject in which RTs for that subject weregressed on the five independent variables inmodel. This leads to a slope estimate for eindependent variable from each participaThen we computed the mean slope for eindependent variable across subjects and tewhether those mean slopes were significadifferent from zero (see Ryan, Sherman,Judd, 1994 for an example of this type of stistical analysis). Such tests tell whether eacthe independent variables has a significantpact on RT, assessing those effects withinjects. Degrees of freedom are based onnumber of subjects. These statistical analwere also used for the accuracy data and wrepeated in all of the studies reported inpaper.

Because some of the experimental itemsnot occur in the Francis and Kucˇera word countheir zero frequency was a problem for thetransformation. We dealt with this in two waOne way was to use the log of the word fquency1 1. The second way was to postulatreal frequency between zero and one for thitems, which we set at 0.5, yielding a log wofrequency of20.3. In most cases, the two meods did not produce differences in significanUnless there was a difference, we report oresults based on log (word frequency1 1).

The present analyses initially included neiborhood frequency as a variable. GraingO’Regan, and Segui (1989) and Grain(1990) have shown that word frequency effecan sometimes be confounded with frequeof orthographic neighbors (i.e., items sharingbut one letter of the target word). Howevernone of the analyses in this paper did this vable show any effects and so it was dropfrom the model.

The only variable that was significant by s
-jects and items was word length [F1(1,30) 5

i-heby

ininsngctsncta

inThe-

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le-m–ha

m

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int of

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in

47FREQUENCY EFFECTS

31.02,p , .0001;F2(1,65)5 14.42,p , .001;Min F9(1,97) 5 9.84, p , .005]. Each addtional letter contributed about 9 ms to RT. Teffect of word frequency was significant onlysubjects [F1(1,30)5 5.12,p , .05;F2(1,65)51.7, p 5 .19]. Slope coefficients are givenTable 1, and Fig. 1 is a scatter plot of RT agalog-word frequency. Accuracy was at ceili(98%) and so there were no significant effe

The present results provide weak evidefor the existence of whole-word representions for regularly inflected forms withthe frequency range tested (0 to 101).interpretation of the present results will bcome clearer when items in a different fquency range are considered in the nextperiment.

EXPERIMENT 2

This experiment sought to examine whoword frequency effects for a different stecluster frequency value of around 50 rather t100 for the first experiment.

Participants

Thirty undergraduate students from the sapopulation as in Experiment 1 participated.

Materials

Sixty-eight regularly inflected words were

TABLE 1

Summary of RT Results for Experiment 1

Mean slope SD F p

A. Subject analysis

Category 21.78 13.61 0.51 .48Word length 9.0 8.85 31.02,.001Log-cluster frequency 24.7 640.7 0 .97Log-word Frequency 28.15 19.72 5.12 .03

Slope SE F p

B. Item analysis

Category 22.97 3.94 0.57 .45Word length 9.00 2.37 14.42 ,.001Log-cluster frequency 246.94 141.6 0.11 .74Log-word frequency 29.59 7.36 1.7 .2

lected whose stem–cluster frequencies range

t

.e-

e

-

n

e

from 49 to 60 (log 1.70 to 1.78). Word frquency varied from 0 to 44 (see Appendix).other aspects of the materials were identicathose in Experiment 1. Filler items includedsimple words, 68 inflected nonwords, andsimple nonwords.

Procedure

The procedure was the same as in Expment 1.


The results are displayed in Table 2. AsExperiment 1, there was a significant effecword length on RT [F1(1,29) 5 55.6, p ,.0001; F2(1,67) 5 14.1, p , .0001; MinF9(1,96) 5 11.23, p, .005]. Each additionaletter contributed 10 ms to RT. Unlike Expement 1, log-word frequency was highly signicant for both subject and item analys[F1(1,29)5 33.5,p , .0001;F2(1,67)5 10.9,p , .005; MinF9(1,96)5 8.24,p , .01]. Figure2 shows a scatter plot of word frequency agaRT. One unit increase in log-word frequencorresponded to a 32-ms decrease in RT. Aracy was again at ceiling (97%) yieldingsignificant effects.

A major assumption of dual access modethat for low-frequency inflected forms, the copositional route should win out over the whoword access route. As a consequence, wh

FIG. 1. Reaction times for regularly inflected words
dExperiment 1.

becya

ichperndzeFont

pant

on

ovehis.9 to84ncy

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ues


word frequency effects are not predicted tofound within the lower end of the frequendistribution. To test this prediction, we didmedian split on the frequency values, whdivided them at the frequency value of 6million. Items with word frequencies below aabove the median were separately reanalyThere were 30 items in the 0 to 6 range.these items, length was highly significa[F1(1,29)5 32.19,p , .0001;F2(1,29)5 8.0,

, .01; Min F9(1,44) 5 6.41, p , .05], butlog-word frequency was no longer signific

TABLE 2

Summary of RT Results for Experiment 2

Mean slope SD F p

A. Subject analysis

Category 2.8 13.4 1.27 .27Word length 9.92 7.17 55.55,.001Log-cluster frequency 42.46 398.3 0.60 .4Log-word frequency 232.17 29.94 33.48,.001

Slope SE F p

B. Item analysis

Category 2.72 4.53 0.36 .5Word length 9.86 2.63 14.08,.001Log-cluster frequency 45.75 145.9 0.10 .7Log-word frequency 232.14 9.72 10.93 .00

FIG. 2. Reaction times for regularly inflected words
Experiment 2.
d.r

[F1(1,29)5 .28, p 5 .6; F2(1,29)5 .07, p 5.8]—see Fig. 3. Again, we found no effectsaccuracy, which remained high at 97%.

There were 38 items with frequencies abthe median split in the 7 to 50 range. Trepresents a log frequency spread of 0.8 (01.7), which was slightly lower than the 0.spread in the 0 to 6 range. Log-word frequewas highly significant [F1(1,29) 5 16.7, p ,.0005;F2(1,37)5 6, p , .005; MinF9(1,60)54.41,p , .05]. The estimated slope coefficiefor log-word frequency was244. In othewords, a unit increase in log-word frequencorresponded to a decrease of 44 ms in RT

This reanalysis of the data supports thediction of dual access models that inflecforms in the lower frequency range shouldshow whole-word frequency effects. The laof frequency effects is unlikely to be the resof a decrease in the number of items tesThere was a similar decrease in the numbeitems with frequencies above 6 per million,frequency effects remained in that reanalyAnother possibility is that the lack of frequeneffects in the 0 to 6 range was due to racompression. We will address that issue innext experiment.

Reanalysis of Experiment 1 Data

How do the present data compare to those

FIG. 3. Reaction times for whole-word frequency valin the 0 to 6 range for Experiment 2.

Experiment 1 where we found only weak effects

ov-thave

nchesferedela

Exge54og

nt

rn

logdtwlapain

cttheal

ngmsnlyns

by

d 2isin-lityhenseecfreheon

per

andofa

ddi-re-ac-ll, itoneto

ingllerderre-ordthems

meted.

ed60

iedc-do

s nocy.ar-s50

on-

revi-

a-rd

,

n

49FREQUENCY EFFECTS

of word frequency? Items in Experiment 1 cered a broader frequency range (0 to 101)Experiment 2 (0 to 44), so there could habeen a floor effect above a certain frequerange for items in Experiment 1. Within thigher frequency ranges, it generally takelarger increase in frequency to make a difence in RT and the distribution of inflectforms at the higher frequency ranges is rtively sparse.

We decided to reexamine the data fromperiment 1 by looking at the frequency rancomparable to Experiment 2. There wereitems in the 0 to 50 range in Experiment 1. Lfrequency was significant by subjects [F1(1,30)5 15.74,p , .0005] and marginally significaby items [F2(1,53) 5 3.35, p 5 .07]. Itemanalyses showed significance when the altetive log word frequency measure was used (p ,.05). The estimated slope coefficient forword frequency was215 for both subjects anitems. This suggests that the data from theexperiments are comparable within the overping frequency range of 0 to 50. Once agaccuracy remained close to ceiling at 98%.

In Experiment 2, the word frequency effeon RT disappeared in the lower end offrequency distribution. For a comparable anysis, we examined the 0 to 6 frequency rafor Experiment 1. There were 23 inflected itein this range. Log word frequency was not ononsignificant, but was in opposite directiofor subject and item analyses [F1(1,30)5 .44,p 5 .51; F2(1,22) 5 1.81, p 5 .19; slopecoefficient 5 211.5 by subjects but 34.2items]. Accuracy remained at 98%.

Overall, the results of Experiments 1 anseem to support the conclusion that therereliable word frequency effect for regularlyflected words, which indicates the availabiof whole-word representations. However, wwe performed a median split of the items baon their frequency, the word frequency effappeared to be restricted to words with aquency of 7 or more. In the lower end of tfrequency distribution, we found no indicatiof whole-word representations.

There were three problems with these ex
iments. First, the 0 to 6 range was establishe
n

y

a-

-

-

a-

o-,

-e

a

dt-

-

when the data had already been collectedexamined. It is important to replicate the lacka frequency effect on RT within this range inprospective study, with new subjects and ational items. Second, it is possible that fquency counts in this range are simply notcurate. When frequency values are very smamay be the case that the difference betweenvalue and another might be more relatedsampling and chance than to real underlydifferences in frequency. Finally, the smarange of frequency values might make it harto get a significant correlation with RT. Thefore, we needed to investigate whether wfrequency effects could be observed withinlower frequency ranges when uninflected iteare considered.

EXPERIMENT 3

Participants

Thirty undergraduate students from the sapopulation as Experiments 1 and 2 participa

Materials

Fifty regularly inflected words were uswhose cluster frequencies were in the 49 torange (log 1.70 to 1.78). Word frequency varonly from 0 to 6. Fifty monomorphemic adjetives were used as control items. Adjectivesnot take inflectional endings and thus there idistinction between word and cluster frequenLike the inflected items, the adjectives also vied in word frequency from 0 to 6. Filler itemincluded 30 uninflected nouns and verbs,inflected nonwords, and 80 uninflected nwords.

Procedure

The procedure was the same as in the pous experiments.

Results and discussion

The results from Experiment 3 are summrized in Table 3. For inflected forms, wolength was again significant [F1(1,29)5 52.52p , .0001;F2(1,49)5 16.63,p , .0005; MinF9(1,74)5 12.63,p , .001]. There was also a
deffect of category whereby RTs were faster for

anMin

y othadth

astheithms

atvi-

d oifi

ofd-

edsrdes.for

cyd a

CWLL

9

in


verbs than for nouns. This effect was significby subjects and items and was marginal byF9 [F1(1,29) 5 14.69, p , .001, F2(1,49) 54.16,p , .05; Min F9(1,73)5 3.24,p 5 .08].Since we did not see a category effect in anthe other studies reported here, it is possiblethe presence of the adjectives somehow mcategory differences more salient. However,reasons for such an effect are unclear.

Log-word frequency for inflected forms wnot only nonsignificant but the effect was inopposite direction than would be predicted, wpositive slopes for both subjects and ite[F1(1,29)5 0.27,p 5 .6; F2(1,49)5 0.13,p 5.72]—see Table 3 and Fig. 4. Therefore the dfor inflected forms replicate those of the preous studies.

When the same analyses were performethe adjectives, word length was again signcant [F1(1,29)5 36.0,p , .0001;F2(1,49)514.49,p , .0005; Min F9(1,77) 5 10.33,p ,.005). Unlike the inflected items, the effectlog word frequency was significant for the ajectives in this frequency range [F1(1,29) 520.19,p , .0005;F2(1,49)5 7.5,p , .01; Min

TAB

Summary of RT R

Inflections

Meanslope SD F

A. Subj

ategory 225.89 36.38 14.7ord length 13.25 9.84 52.5

og-cluster freq. 2104 568 0.97og-word freq. 5.61 57.8 0.27

Inflections

Slope SE F

B. Item

Category 227.07 13.28 4.16Word length 12.95 3.18 16.63Log-cluster freq. 294.01 195 .23Log-word freq. 8.15 22.99 .13

F9(1,76) 5 5.47, p , .05]—see Fig. 5. To

t

fate

e

a

n-

directly compare adjectives with inflectitems, we performed a pairedt test by subjectcomparing the slope coefficients for log-wofrequency for inflected forms versus adjectivThe difference was significant [mean slopeinflected forms 5 5.61, for adjectives5257.48,t(29) 5 3.57,p , .005].

The results were similar for the accuradata. For the inflected forms, only length ha

3

lts for Experiment 3

Adjectives

pMeanslope SD F p

analysis

,.001 — — — —,.001 20.77 18.64 36.0 ,.001

.33 — — — —.60 257.48 68.89 20.2 ,.001

Adjectives

p Slope SE F p

nalysis

.04 — — — —,.001 23.5 6.17 14.49 ,.001

.63 — — — —.72 279.58 29.07 7.5 .00

FIG. 4. Reaction times for regularly inflected items

LE

esu

ect

a

Experiment 3.

Fnt

thean

by

ecumsmsthje

heforanfo

rd6

ncytedk os ata-

all,

fortersc-iva-s,re-nalcu-fora-

emterndjec-thencyrd

g-not

tsri-ad-

nalTheari-for

ct

ncere-ford-sultes

anypes

Ex-

51FREQUENCY EFFECTS

significant effect [F1(1,29) 5 8.54, p , .01;2(1,49)5 6.46,p , .05; Min F9(1,79)5 3.68,

p 5 .052]. Word frequency was not significa[F1(1,29)5 1.15,p 5 .29;F2(1,49)5 .61,p 5.44]. Accuracy remained high at 96%. Foradjectives, word frequency was signific[F1(1,29)5 71, p , .0001;F2(1,49)5 6.38,p , .05; Min F9(1,59)5 5.85,p , .05], whilelength was significant by subjects but notitems [F1(1,29)5 20.55,p , .0001;F2(1,49)5 1.84, p 5 .18]. Average accuracy for thadjectives was 79%. The differences in acracy rates for adjectives and inflected forprobably reflects the fact that inflected forcould be accessed compositionally throughhigher frequency base form, whereas the adtives could not.

A paired t test by subjects comparing tslope coefficients for log word frequencyinflected forms versus adjectives was significfor the accuracy data as well [Mean slopeinflected forms5 20.015, for adjectives50.285,t(29) 5 29.05,p , .0001].

In summary, we replicated the lack of a wofrequency effect for inflected forms in the 0 tofrequency range. However, a word frequeeffect was found in this range for uninflecadjectives. This result suggests that the lacfrequency effects for inflected forms reflectreal unavailability of whole-word represen

FIG. 5. Reaction times for uninflected adjectives inperiment 3.

tions rather than sampling limitations due to

t

-

ec-

tr

f

unrepresentativeness of items within a smlow frequency range.

It is possible that the frequency effectsadjectives might be affected by the clusformed by derivational forms. Although adjetives are not inflected, some can take dertional affixes such as-er, -est, -ly, -en, -nesand-ity. We calculated derivational cluster fquencies based on this family of derivatioforms for the adjectives. In addition, we callated similar derivational cluster frequenciesthe inflected forms. It is possible that, if derivtional cluster frequency is correlated with itfrequency, then either the derivational clusfrequency or a combination of the item acluster frequency might be pushing the adtives to exhibit a frequency effect. However,log-transformed derivational cluster frequewas only moderately correlated with log wofrequency (r 5 0.14 for the inflected items;r 50.15 for the adjectives). Effects of loderivational cluster frequency for RT weresignificant for inflected items [F1(1,29)5 .30,p 5 .59; F2(1,49) 5 .06, p 5 .81], althoughthey were significant for adjectives [F1(1,29)527.86,p , .0001; F2(1,49) 5 6.91, p , .05;Min F9(1,44) 5 5.54, p , .05]. This suggesthat the family cluster formed by adding devational morphology can support access forjectives.

We reran all of the analyses with derivatiocluster frequency included as a variable.results were not essentially affected by this vable. In particular, the word frequency effectadjectives remained [F1(1,29) 5 17.66, p ,.0005;F2(1,49)5 6.06,p , .05; Min F9(1,48)5 4.51,p , .05], and there was still no effefor inflected forms.

EXPERIMENTS 4 AND 5

The previous experiment provided evidethat frequency effects occur in the lower fquency ranges for uninflected forms, but notregularly inflected forms. In the next two stuies, we sought to replicate and extend this reby examining inflected forms and adjectivseparately. This would allow us to negatepossible contamination between the two ty
of items. In addition, by using a larger number

the

f tharynge iideis

ra-mis

w-us-vahisord

opuederer

eds inrds94

on-

ec-thein-on-

revi-

dis-in

ant


of items for each type, we could increasepower of the tests.

We were also concerned that the choice o0 to 6 frequency range was relatively arbitrbased on the median split of the frequency rafor Experiment 2. We were interested to sethe same pattern of results occurred for a wlow-frequency range of 0 to 24. Although thisalso arbitrary, it does allow for further explotion. It is possible to increase the potential nuber of inflected forms if the cluster frequencykept relatively low. This is because most lofrequency items belong to low-frequency clters. We therefore chose frequency clusterues of 25 to 31 for the next experiment. Talso allowed us to examine the effects of wfrequency for a new cluster value.

Participants

Undergraduate students from the same plation as previous experiments participatTwenty-seven subjects were tested in Expment 4 and 26 subjects were tested in Exp

TAB

Summary of RT Resu

Inflections

Meanslope SD F

A. Subj

Category 2.53 18.06 .02Word length 13.16 13.02 26.56Log-cluster freq. 2237 314 14.8Log-word freq. 223.27 29.58 16.1

Inflections

Slope SE F

B. Item

Category 2.02 4.78 .00Word length 13.12 3.04 18.63Log-cluster freq. 2259 117 4.84Log-word freq. 221.45 12.92 2.76

ment 5. 1

e

efr

-

l-

-.i-i-

Materials

For Experiment 4, 94 regularly inflectwords were selected with cluster frequenciethe 25 to 31 range (log 1.40 to 1.49). Wofrequency varied from 0 to 24. Filler itemincluded 94 uninflected nouns and verbs,inflected nonwords, and 94 uninflected nwords.

In Experiment 5, 94 monomorphemic adjtives were selected with word frequencies in0 to 24 range. Filler items included 94 unflected nouns and verbs and 188 simple nwords.

Procedure

The procedure was the same as in the pous experiments.


The results of Experiments 4 and 5 areplayed in Table 4. For the inflected itemsExperiment 4, word length had a significeffect on RT [F1(1,26) 5 26.56, p , .0001;F2(1,93)5 18.63,p , .0001; MinF9(1,100)5

4

for Experiments 4 and 5

Adjectives

pMeanslope SD F p

analysis

.88 — — — —,.001 12.84 9.37 46.9 ,.001

.006 — — — —,.001 291.61 48.52 89.1 ,.001

Adjectives

p Slope SE F p

nalysis

.99 — — — —,.001 13.48 3.21 17.64 ,.001

.03 — — — —.10 296.25 13.97 13.97 ,.001

LE

lts

ect

a

0.95,p , .005]. Unlike the other experiments,

Ft o am thp ef b-j y

.daighre-

d oandh:

.the-logad-an-

sic-

e4

ms.

ncyr toorddata

wecy51

ec-hebleh:

1

mscyms

incetioneri-ant

wecu-omin

Ex-

53FREQUENCY EFFECTS

there was a cluster frequency effect [F1(1,26)514.8,p , .001;F2(1,93)5 4.84,p , .05; Min

9(1,121)5 3.65,p 5 .06]. Although we triedo keep the range of cluster frequency tinimum, there was enough of a spread inresent experiment to create an effect. The

ect for word frequency was significant by suects [F1(1,26)5 16.1,p , .0005], but not bitems [F2(1,93)5 2.76,p 5 .10]—see Fig. 6The frequency effect suggested by theseindicate that the 0 to 24 frequency range mexceed the cut-off point for whole-word repsentations of inflected forms.

When the same analyses were performethe adjectives in Experiment 5, both lengthword frequency were significant [lengtF1(1,25) 5 46.93, p , .0001; F2(1,93) 517.64,p , .0001; MinF9(1,118)5 12.82,p ,.001; word frequency:F1(1,25)5 89.11,p ,.0001; F2(1,93) 5 47.45, p , .0001; MinF9(1,109)5 30.96,p , .0001]—see Figure 7

To directly compare the adjectives withinflected items, we performed at test by subjects comparing the slope coefficients forword frequency for inflected forms versusjectives. The difference was significant [meslope for inflected forms5 223.27, for adjectives 5 291.61,t(51) 5 26.22,p , .0001].

For the accuracy measures, there was anificant effect of word frequency for the adjetives in Experiment 5 [F1(1,25)5 84.58,p ,.0001; F2(1,93) 5 44.79, p , .0001; Min

FIG. 6. Reaction times for regularly inflected items
Experiment 4.
ef-

tat

n

g-

F9(1,109)5 29.28,p , .0001], but not for thregularly inflected words in Experiment[F1(1,26)5 2.7,p 5 .11;F2(1,93)5 2.41,p 5.12]. Average accuracy for the inflected itewas 95% while for the adjectives it was 90%

To summarize, by increasing the frequerange of the inflected forms to 24, we appeahave gone beyond the threshold for whole-wrepresentations. To be sure that the presentare compatible with the previous findings,looked at items in the 0 to 6 word frequenrange in Experiments 4 and 5. There wereinflected items in Experiment 4 and 51 adjtives in Experiment 5 within this range. For tinflected items, length was the only variawith a significant effect on RT [for lengtF1(1,26) 5 19.12, p , .0001; F2(1,50) 5

3.27,p , .0001; Min F9(1,77) 5 7.83, p ,.01; for word frequency:F1(1,26)5 .32, p 5.58; F2(1,50)5 .34, p 5 .56).

Analyses on accuracy for inflected iteshowed a significant effect of word frequenby subjects and a marginal effect by ite[F1(1,26) 5 4.47, p , .05; F2(1,50) 5 3.14,p 5 .08]. These results are unexpected sthey seem to contradict the data from reactimes and the findings from previous expments where accuracy showed no significeffects for inflected forms. Furthermore,found no significant frequency effect for acracy when we looked at the 0 to 24 range fr

FIG. 7. Reaction times for uninflected adjectives inperiment 5.

the same experiment. If there were a true un-

ex-eal

ad-th

ittle. Inralerioleeail

an

yby

d

cesed

nif

nlyredn-jecterll oncnod-

ne

t onc

onexex

mis

inren-

nif-s

derentcieshere

msge,

inancyTa-inan

there-

ofs

ge., 2,howsterd ifegu-x-

er-

cys,

ves,

08


derlying frequency effect, then one wouldpect it to be greater when the frequency rangextended. This was the case with RTs forforms and for accuracy with adjectives. Indition, average accuracy remained at 95% in0 to 6 range. This trend therefore makes lsense in the context of the other findingsother ways, the present results are geneconsistent with the results of previous expments. Taken together, they suggest that whword representations are not available in thto 6 frequency range, but do begin to be avable at frequencies above that range.

For the adjectives, length had a significeffect on RT within the 0 to 6 range [F1(1,25)5 24.83,p , .0001;F2(1,50)5 11.4,p , .005;Min F9(1.77)5 7.81,p , .01]. Word frequencwas significant by subjects and marginalitems when log (word frequency1 1) was use[F1(1,25) 5 4.35, p , .05; F2(1,50) 5 3.69,p 5 .06]. This effect did reach significanwhen the alternative log method was u[F1(1,25) 5 7.85, p , .01; F2(1,50) 5 8.58,p , .005; MinF9(1,67)5 4.1,p , .05]. For theaccuracy data, word frequency was also sigicant [F1(1,25)5 33.88,p , .0001;F2(1,50)56.93,p , .05; Min F9(1,68)5 5.75,p , .05].Average accuracy went down to 80% when oadjectives in the 0 to 6 range were conside

As in Experiment 3, it was important to esure that word frequency effects for the adtives were not an artifact of derivational clusfrequency effects. Once again, we reran athe analyses with derivational cluster frequeincluded as a variable. This variable wassignificant for either the inflections or the ajectives and word frequency results remaiunaffected.

CLUSTER FREQUENCY EFFECTS

Our approach in designing the present seexperiments has been to hold cluster frequeconstant and to look at effects due to variatiin word frequency. However, because weamined different cluster frequencies acrossperiments, we can ask whether the base foractivated when a regularly inflected formaccessed.

Taft (1979) and Burani et al. (1984) both

isl

e

ly--

0-

t

-

.

-

fyt

d

fys--is

carried out lexical decision experimentswhich pairs of regularly inflected words wematched for word frequency but differed cosiderably in cluster frequency. RTs were sigicantly higher for low cluster frequency itemthan for high cluster frequency items. In orto do a comparable analysis with the presdata, we selected a range of word frequenthat was common across experiments and wthe cluster frequency differed significantly.

Experiments 1 and 2 included several itewith word frequencies in the 0 to 50 ranwhile the cluster frequency was around 100Experiment 1 and 50 in Experiment 2. MeRTs for the items in the 0 to 50 word frequenrange for each experiment are presented inble 5. A t test revealed that RTs for itemsExperiment 1 were significantly shorter ththose for Experiment 2 [t(121) 5 5.6, p ,.0001]. Presumably, this difference reflectsactivation of the base form, replicating thesults of Taft and Burani et al.

As a further test, we can add the resultsExperiment 4 by limiting the analysis to itemwith word frequencies in the 0 to 24 ranMean RTs for these items in Experiments 1and 4 are presented in Table 6. These data sthat RTs decreased with increases in clufrequency across experiments, as predictebase forms are activated when accessing rlarly inflected forms. Differences between Eperiments 1 and 2 were significant [t (101) 55.24,p , .0001], as were those between Expiments 2 and 4 [t (150) 5 3.11,p , .005].

Another interesting test of cluster frequeneffects is in the comparison of inflected formwhich are members of clusters, and adjecti

TABLE 5

Cluster Frequency Effects ComparingExperiments 1 and 2

Clusterfrequency

Meanword

frequencyRT

(MS)

Experiment 1 100 12.61 56Experiment 2 50 12.63 59

which lack inflectional clusters. If clusters fa-

ecfort 3as

vesar-fors).enericyer

steri-

edanfreothlexredultsdectsemncob-onginbympao

cal

sorddelslex-n ber-areata

dic-els.tedectsrbsncy

rac-fre-

ofof

e-

ac-notse

a portst e’sm

bee eti-t tesw r-s le-w tew herh ant,w esa forfi hep eset lsoa ncye ivesl noc ectf

at,a thet e-

336

55FREQUENCY EFFECTS

cilitate lexical access, then we would expRTs to be lower for inflected forms thanadjectives. This was the case in Experimenwhere the mean RT for the inflected forms w619 ms compared to 677 ms for the adjectiHowever, this trend did not hold in the compison of Experiments 4 and 5 (mean RTinflections: 626 ms, for adjectives: 619 mThis may be due to the fact that in Experim3, the cluster frequency was 50 and in Expment 4 it was 25. In addition, the item frequenrange in Experiment 3 was 0 to 6 and in Expiments 4 and 5 it was 0 to 24. Thus, the clufrequency effect would be weaker in Expement 4 than in Experiment 3.

TESTING PREDICTIONS FROMCONNECTIONIST MODELS

In the Introduction to this article, we discussthe connectionist accounts of Bybee (1995)Stemberger (1995) with regard to whole-wordquency effects for regularly inflected words. Baccounts focused on the competition betweenical strength and lexical connections, but diffein the form of this competition. The present resare consistent with one aspect of Bybee’s mowhich predicted whole-word frequency effeonly above a certain frequency threshold. Stberger (1995) argued that whole-word frequeeffects for regular inflections should not betained due to the competition from the very strinterlexical connections to other items sharingflectional endings. This model is not supportedthe present data. However, it is likely that Steberger’s model could also accommodate thetern of results we found by lessening the roleinterlexical connections relative to the lexi

TABLE 6

Cluster Frequency Effects ComparingExperiments 1, 2, and 4

Clusterfrequency

Mean wordfrequency RT

Experiment 1 100 8.29 56Experiment 2 50 8.02 60Experiment 4 25 7.3 62

strength of the inflected items. q

t

,

.

t-

-r

d-

-

l,

-y

-

-t-f

Unfortunately, it is difficult to test predictionfrom these models based on simple whole-wfrequency effects. This is because these modepend on postulated relative contributions ofical strength and lexical connections, which caaltered to fit the data. It is also difficult to diffeentiate them from dual models since theydesigned to account for the same kind of doutcomes. Therefore, we should look for pretions that are specific to the connectionist modOne strong prediction of Bybee’s model, noearlier, is that nouns should show stronger effof whole-word frequency than verbs, and veshould show stronger effects of cluster frequethan nouns.

We tested whether there were any intetions between category and whole-wordquency for Experiments 1, 2, 3, and 4. Nonethe interactions was significant regardlesswhether all of the items or only the low-frquency items (0 to 6) were considered (p ..27). Similarly, the category by cluster intertions for Experiments 1, 2, and 4 were alsosignificant (p . .39). Therefore, neither of the

nalyses based on category differences suphe specific predictions derived from Bybeodel.It is possible that the current data might

xplained by a more straightforward compion model in which cluster frequency compeith whole-word frequency (David Plaut, peonal communication). In our studies, whoord frequency varied, which would promohole-word frequency effects. On the otand, cluster frequency was kept consthich would promote similar reaction timcross items. On this account, the thresholdnding whole-word frequency would be toint at which the competing strengths of th

wo factors are about equal. The model accounts for the strong whole-word frequeffects found for adjectives. Because adject

ack inflectional clusters there would beompetition to promote a flat frequency effor low-frequency items.

This model makes the distinct prediction ths cluster frequency decreases, so should

hreshold value for finding a whole-word fr
uency effect for inflected items. We can ap-

aterluselyorth

ominef-peatao

wostean. Inmsontendre-ifi-

5q

peri forw freq trat nol ncya fec( :s2 ncyo fre-q 25,t exp thism odb

cye rlyi tw il-l

t edf er-w ionsb ncye ad-j hisp rdsm gh-o

twok odelp rdsc ordr ute.T pe-t de-t Forh ep-r thep s, thec andw esh-o ents

sid-e col-l thatr d atm tos ereasi redi as as hes tedf ; ones Thep incew oldo r’sm ole-w ms,b sary.T thep

nk-e ithr eadst ms,


proach a test of this prediction by lookingidentical word frequency ranges across expments. Experiments 1, 2, and 4 examined cter frequencies of 100, 50, and 25, respectivAs cluster frequency decreases, the whole-wfrequency effect should become stronger asthreshold shifts downward.

Selecting items in the 0 to 24 range frExperiments 1, 2, and 4, we examined theteraction between whole-word frequencyfects and cluster frequency across these eximents. We ran a single test combining dfrom all three experiments and regressed RTcategory, length, log word frequency, and tcontrast coded variables that compared clu25 versus clusters 50 plus 100 (contrast 1)cluster 50 versus cluster 100 (contrast 2)addition, we looked at two interaction terbetween log word frequency and our two ctrast coded variables. The results replicamain effects for length, log word frequency, acluster frequency. However, the log word fquency by cluster interactions were not signcant [contrast 13 log word frequency:F(1,193)

0.02; p 5 .89; contrast 23 log word fre-uency:F(1,193)5 1.14;p 5 .29].We also looked at the data from each ex

ment noting whether the slope coefficientshole-word frequency increased as clusteruency increased across experiments. Con

o the predictions of the model, there wasinear relation between the cluster frequend the size of the whole-word frequency efExperiment 1: slope5 210.67; Experiment 2lope 5 231.09, Experiment 4: slope521.44). In other words, the cluster frequef 50 showed the strongest whole-worduency effects, followed by the cluster of

hen 100. Bearing in mind that the presenteriments were not directly set up to testodel, at present we cannot endorse the mased on the analysis of our results.

GENERAL DISCUSSION

Our results show that whole-word frequenffects can be reliably obtained for regula

nflected forms, although they disappear aord frequency threshold of about 6 per m

ion. This indicates that whole-word represent

i--.de

-

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n

rd

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a

ations are available for regularly inflectorms with frequencies above that value, othise they require compositional representatased on morphological structure. Frequeffects did not disappear for simple words (

ectives) below any frequency threshold. Tresumably reflects the fact that simple woust have whole-word representations throuut the frequency range.We began this paper with a discussion of

inds of dual models. In one case, the dual mroposed that morphologically complex woould be accessed either through a whole-wepresentation or through a decompositional rohe two access routes were said to be in com

ition with one another, and word frequencyermined which access route would win out.igh-frequency inflected forms, whole-word resentations are strong and therefore providerimary access route. As frequency decreaseompositional route becomes more reliablehole-word access no longer occurs. The thrld for frequency effects found in the prestudies clearly supports this dual model.The second kind of dual model that we con

red was that proposed by Pinker and hiseagues (Pinker, 1991). This model proposedegular and irregular inflections are dissociateany levels. Regular inflections were said

how evidence of rule-based processes whrregular inflections show evidence of being ston associative memory. We noted that there wtrong and a weak form of Pinker’s model. Ttrong version claimed that regularly inflecorms are never represented as whole wordshould find no frequency effects in any range.resent results do not support this position se did find frequency effects above the threshf 6 per million. The weaker version of Pinkeodel allows that there could be some whord representations for regularly inflected forut that such representations are not neceshis version appears to provide a better fit toresent data.However, endorsing the weak version of Pi

r’s dual model raises important questions wespect to the concept of storage. If storage lo connectionistlike associations between ite
-hen such items should show gang effects (Stem-

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57FREQUENCY EFFECTS

berger and MacWhinney, 1988). PrasadaPinker (1993) found that, unlike irregular infletions, regularly inflected forms show no gangfects. Since the number of regularly inflecforms above threshold for frequency effectsconsiderable, it is paradoxical that they doshow some evidence of associative processthe form of gang effects.

There are two possible solutions to thisparent paradox. First, it is likely that the twtests address different issues. On the one hwe have a question about the nature ofrepresentations: do we keep whole-word resentations in memory for complex words? Mnipulations of frequency are designed to addthis question. A very different issue is homorphological patterns generalize. PrasadaPinker’s results suggest that regular inflectigeneralize on the basis of abstract rules, wirregular inflections generalize on the basislexical associations (i.e., gang effects). Gealizations based on gang effects require whword representations; they exploit similaritiethe level of the entire word. Generalizatiobased on rules are independent of the existof whole-word representations, but by no meexclude them. In fact, from a processing pspective, it may be advantageous or evenessary to store whole-word representationsregularly inflected forms when they occur fquently in the language. As Sandra (19pointed out, on-line composition of morpholoically complex words reduces the need for sage space but at the cost of greater procesdemands. While whole-word representatimay not be necessary for regularly inflecitems, the limited nature of our on-line comptations paired with our enormous resourceslanguage memory may make them conveni

If all of the above is true, then this would seto imply that there is lexical storage for reguand irregular inflections but that associative meanisms arise only in the irregular vocabulary. Wshould associative memory act only on irregmorphology? One possibility is that gang effeand whole-word frequency effects tap into diffent levels of processing. In other words, these
tests for storage may address different kinds o
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representations, and only one of those exhassociative properties.

Dual models for lexical access proposewhole-word representations exist in the acsystem (Anshen & Aronoff, 1988; Baayen, 19Burani & Caramazza, 1987; Burani & Laudan1992; Caramazza et al., 1985; 1988; ChialanCaramazza, 1995; Frauenfelder & Schreu1991; Laudanna et al., 1989, 1992; SchreudBaayen, 1995; Stemberger & MacWhinn1988). Marslen-Wilson, Tyler, Waksler, aOlder (1994) have proposed that access reprtations are defined by the modality of the stimuinput (e.g., visual, auditory). It is here that fquency effects are assumed to arise. The modspecific access representations are said to feea more abstract, modality-neutral, internal lexicIt is possible that the lexicon, rather thanaccess system, is the locus of associative menisms giving rise to such things as gang effec

With regard to connectionist models, we nothat a threshold for whole-word frequency effecould be predicted by certain kinds of connectist models. However, when more specific pretions were tested, the connectionist models didfare so well. On the other hand, it was onlyconnectionist models that were specific enougallow such predictions, and one should not thfore take such failures as an endorsement of anative models that make no such specific pretions. In addition, the kinds of analyses we carout to test these models were not within the mdesign of the study and so further evaluatiowarranted.

To summarize, we have shown that thereindeed whole-word representations availableregularly inflected items. At the same time,have demonstrated that this is not true for itemthe lower end of the frequency distribution.other words, there is a critical role for combitional principles in the system, given that soitems can only be accessed through morpholodecomposition. The results highlight the needistinguish between frequency effects and geffects and the different conceptual issues asated with these two phenomena. The distincbetween access representation and central r
fsentation is particularly useful in this regard.

E

1

6

4

5

2

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52

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APPENDIX

Experimental Items

xperiment 1

WordW

FreqClusterFreq Word

WFreq

ClusterFreq

destroys 0 104 squares 13 12sevens 0 114 supplying 13 103suns 1 117 cared 15 108behaviors 1 100 oils 15 111finishes 1 120 selecting 15 112captains 1 99 balls 17 122incomes 1 110 refers 18 104eats 2 122 parks 19 111listens 2 122 traditions 21 115settles 2 105 successes 22 11naming 3 109 reflects 23 107announces 3 116 tended 24 10faiths 3 110 sessions 26 106discovers 3 122 responses 28 10justices 3 104 trips 29 109regarding 3 100 instances 30 11suffers 5 110 ladies 37 122saves 5 121 smiling 38 122compares 6 114 pages 40 10councils 6 115 regions 40 119denies 6 109 shared 40 10saints 6 103 shoulders 52 11proposing 6 110 motors 53 108forgetting 7 119 pushed 53 102gases 7 107 wondered 58 11observes 8 120 weapons 61 10mouths 8 113 arrived 62 108fixing 9 109 yards 65 100dinners 9 100 fingers 66 106depended 9 106 published 89 10seas 10 104 parents 97 11improves 11 121 facilities 100 111treating 11 122 interested 101 10

Experiment 2

WordW


WFreq

ClusterFreq

constructs 0 56 advertised 9 49convinces 0 57 vacations 9 54televisions 0 51 strangers 9 50tuesdays 0 59 retains 9 49installs 0 49 confronting 10 55mixes 0 56 afforded 11 58appointing 1 50 rejects 11 58cleans 1 58 constitutes 11 54jumps 1 58 restaurants 12 53

WordW


WFreq

ClusterFreq

adjusting 2 60 enabling 13 57bays 2 60 printing 13 53operas 2 49 chickens 13 49pouring 2 49 sisters 15 55solves 2 49 pockets 17 59bibles 2 60 implied 17 53majorities 3 60 favored 18 49uncles 3 58 victims 19 50absences 3 56 secrets 20 5interiors 4 49 shadows 20 54promotes 4 60 bullets 21 49chests 4 57 financing 21 55chemicals 4 57 substances 23 5accounted 5 49 prospects 24 49tendencies 5 54 critics 27 53ignoring 5 57 stars 29 58prefers 5 60 dancing 30 59tying 5 50 cooling 33 59dramas 6 49 advertising 36 49republics 6 49 authorized 37 49roots 6 53 approved 40 56implying 7 53 composed 40 50responds 7 54 neighbors 42 59tragedies 7 56 shoes 44 58liberties 8 56 acres 44 54

Experiment 3: Inflections

WordW


WFreq

ClusterFreq

televisions 0 51 appointing 1 50constructs 0 56 dictionaries 1 59convinces 0 57 leans 1 60installs 0 49 pouring 1 49isolates 0 49 advertises 1 49mixes 0 56 jumps 1 58surrounds 0 53 adjusting 2 60tuesdays 0 59 operas 2 49preferring 1 60 retires 2 54cleans 1 58 solves 2 49bays 2 60 chests 4 57bibles 2 60 concludes 4 60composing 2 50 ignores 5 57commits 2 50 affords 5 58majorities 3 60 reminding 5 57uncles 3 58 tendencies 5 54absences 3 56 confronts 5 55constituting 3 54 tying 5 50creations 3 50 doctrines 5 57interiors 4 49 authorizing 5 49

q

59FREQUENCY EFFECTS

WordW


WFreq

ClusterFreq

promotes 4 60 possessing 6 54rejecting 4 58 republics 6 49diameters 4 53 responding 6 54defends 4 56 roots 6 53forts 4 55 dramas 6 49

Experiment 3: Adjectives

Word WFreq Word WFre

macabre 0 candid 3nimble 0 mundane 3supple 0 lavish 3somber 0 transient 3brusque 0 diagonal 4abstruse 0 docile 4avid 1 innate 4insipid 1 inverse 4affable 1 numb 4convex 1 salient 4minuscule 1 languid 4obstinate 1 plump 4opulent 1 anterior 5rotund 1 fertile 5treble 1 mediocre 5succinct 1 fluent 5agile 2 lethal 5arrogant 2 aberrant 5covert 2 obsolete 5deft 2 sparse 5obscene 2 cordial 6profuse 2 clumsy 6tacit 2 meager 6insolent 2 opaque 6exquisite 3 placid 6

Experiment 4

WordW


WFreq

ClusterFreq

coped 0 30 fortunes 6 29cancers 1 25 gangs 6 27funerals 1 31 veins 6 31spheres 1 26 pretended 6 27tributes 1 25 yelling 6 31cellars 1 25 vectors 7 26climates 1 27 motels 7 31perceiving 1 29 cabins 7 30explores 1 29 negotiated 7 25

WordW


WFreq

ClusterFreq

neglects 1 28 denotes 7 25scaring 1 26 persists 7 25bellies 2 25 protesting 7 29charms 2 25 borrowing 7 31journeys 2 31 statues 8 25dilemmas 2 27 crystals 8 31gears 2 28 monuments 8 29shirts 2 29 clarified 8 25parades 2 26 bears 9 25regimes 2 25 charts 9 30compels 2 25 rails 9 25arresting 2 27 borders 10 30reverses 2 27 clues 10 25exciting 2 28 champions 10 31academies 3 28 departing 10 28bowls 3 26 enduring 10 31sheriffs 3 28 assessing 10 25crafts 3 25 blades 12 26cooperated 3 28 debts 12 25exerts 3 29 pretending 12 27arousing 3 30 bubbles 13 25aunts 4 27 deputies 13 27circuits 4 27 drifting 13 27pistols 4 31 breathing 13 31rituals 4 27 flames 14 27disasters 4 30 organs 14 26empires 4 26 minerals 14 26conveys 4 27 potatoes 15 30inducing 4 29 vegetables 16 26squeezing 4 30 devised 16 25baths 5 31 tanks 18 30cafes 5 25 toes 19 26garages 5 25 documents 19 30praying 5 30 boots 20 30linking 5 25 residents 20 28storms 6 31 educated 21 31cottages 6 25 dedicated 22 25cycles 6 30 norms 24 31

Experiment 5

WordW

Freq WordW

Freq

nimble 0 futile 6astute 1 rude 6brash 1 meager 6concise 1 opaque 6oblique 1 placid 6clandestine 1 blunt 7supine 1 bizarre 7convex 1 brisk 7rotund 1 polite 7

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WordW

Freq WordW

Freq

avid 1 dismal 8affable 1 pregnant 8affluent 2 sane 8arid 2 serene 8deluxe 2 fierce 8morose 2 latent 9prolific 2 potent 9terse 2 compact 9deft 2 coarse 10tacit 2 tense 10obscene 2 weird 10profuse 2 adverse 11agile 2 eloquent 11covert 2 prone 11bland 3 strict 11erudite 3 tender 11lenient 3 shy 11sordid 3 solemn 12candid 3 diverse 13mundane 3 acute 13lavish 3 transparent 13adept 4 dumb 14tame 4 elegant 14turbulent 4 intact 14lucid 4 ripe 14docile 4 shallow 14innate 4 sincere 15inverse 4 loud 15numb 4 sober 16plump 4 absurd 17austere 5 abrupt 18hoarse 5 naive 19inert 5 savage 19timid 5 nude 20torrid 5 smart 20cordial 6 bold 21clumsy 6 moderate 22desolate 6 stupid 24

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Received June 12, 1997)Revision received August 10, 1998)

Documents

Frequency Effects and the Representational Status of ......Clelland, 1986; Stemberger, 1995) and spel-ling–sound correspondences (Plaut, McClel-land, & Seidenberg, 1996; Seidenberg