The interplay of root, suffix and whole-word
frequency in processing derived words*
Cristina Burani and Anna M. Thornton
In three lexical decision experiments we investigated whether the relative frequency
of root, derivational suffix and whole-word affects processing of Italian printed
derived stimuli. Experiment 1 considered pseudowords made up of pseudoroots
combined with either high-,medium-, or low-frequency suffixes. Only pseudowords with high-frequency suffixes resulted in increased decision times and
higher error rates relative to nonsuffixed pseudowords. Experiments 2 and 3 dealt
with suffixed derived words. In Experiment 2, low-frequency words with high-or
low-frequency roots and with high or low-frequency suffixes were orthogonally
contrasted. Lexical decision latencies were a function of the frequency of both the
root and the suffix. However, post-hoc comparisons showed an effect of wholeword familiarity. In Experiment 3, low-frequency derived words with orthogonal
variation of root and suffix frequency, and equal whole-word familiarity, were
investigated, and were contrasted with low-frequency nonderived words. Words
with high-frequency roots showed quicker and more accurate lexical decision
responses, irrespective of suffix frequency. By contrast, words with low-frequency
roots, irrespectively of suffix frequency, did not differ from nonderived words.
These results are interpreted within Schreuder and Baayen’s (1995) parallel dualroute model for morphological processing, as evidence for both benefits and costs
of morphemic access, due to the balancing of the quantitative characteristics of
root, suffix and whole word.
1. Introduction
In most models of morphological processing, it is assumed that the probability of accessing morphological constituents of words is conditioned, at
the different processing stages, by many properties of the morphologically
complex words. Among these properties, the frequency of morphological
constituents relative to the frequency of the complex word as a whole form
can play a major role.
Evidence for reliance on morphological structure in accessing printed
complex words comes from low-frequency words which include higher
frequency constituents (see, e.g., Andrews 1986; Burani and Caramazza
1987; Meunier and Segui 1999). In parallel dual-route models of lexical
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access (see, e.g., Burani and Laudanna 1992; Chialant and Caramazza
1995; Frauenfelder and Schreuder 1992; Schreuder and Baayen 1995),
words composed of more than one morpheme may activate in parallel two
types of access units, namely units corresponding to the whole word and
units corresponding to the morphemes included in the stimulus. In these
models, the relative frequency of the whole word and of the constituent
morphemes affect the relative time-course of activation of the different
units in the different components. Hence, frequency is the major determinant of the relative probability that lexical access is either whole-wordbased or morpheme-based.
The assumption underlying these models is that the higher the frequency of a given lexical unit, be it a word, a root or an affix, the greater the
likelihood that this unit is quickly activated and processed in the different
processing components. What is crucial, in determining the probability that
lexical access is provided by either whole-word or morpheme processing,
is the complex balance existing between the frequency of the whole word
and the frequency of its constituent morphemes, both roots and affixes, i.e.,
it is relative frequency, rather than absolute frequency (for a similar proposal, see Hay 2000; 2001).
Hence, it might be predicted that a transparent derived word which has
low-frequency in the language, like Italian bassezza (‘lowness’), but is
composed of a very frequent root (i.e., bass-, ‘low’) and a very frequent
suffix (i.e., -ezza, ‘-ness’) is likely to be accessed via activation of its morphemic constituents, rather than via the unit corresponding to the wholeword, which is supposed to be very scarcely activated. This prediction
implies that the frequencies of both the root and the suffix are capable of
affecting processing, and calls for evidence concerning the roles of both
root and suffix frequency. However, and surprisingly, only the frequency
of roots has been considered so far, while the frequency of affixes has been
usually neglected. No study on lexical access to derived words has systematically varied the quantitative values of derivational affixes. By contrast,
these values have been investigated in the context of pseudoword processing (see below).
1.1. Studies on words
Several studies conducted in different languages, including English, Italian,
French and Dutch, have shown that access times and accuracy to suffixed
The interplay of root, suffix and whole-word frequency
159
derived words are significantly affected by root frequency (see, e.g., Beauvillain 1996; Bradley 1979; Burani and Caramazza 1987; Colé, Beauvillain
and Segui 1989; Holmes and O’Regan 1992; Schreuder, Burani, and
Baayen 2002). Lexical decisions were faster and more accurate when a
suffixed word, usually of low frequency, included a root of high frequency.
The facilitatory effect of high-frequency root morphemes was found both
when calculation of root frequency included the frequency of the base
word and its inflected forms only (Burani and Caramazza 1987), and when
it was extended to include the frequencies of all the derived word-forms
sharing the same root (Colé, Beauvillain and Segui 1989).
The root frequency effect has been found in the context of suffixed derived words that were both orthographically and phonologically transparent
with respect to their base root, and were usually transparent for meaning
with respect to the meaning of their base. However, there has been evidence of root frequency effects also for derived words that included bound
roots, or could be rated as semantically opaque with respect to their base
(see, e.g., Holmes and O’Regan 1992; Schreuder, Burani and Baayen
2002). In the studies in which root frequency effects have been found, suffixes were usually productive and had high frequency. Suffix frequency
was not directly investigated per se, but it was usually kept constant across
categories by including the same suffixes in the high-frequency and lowfrequency root sets.
1.2. Studies on pseudowords
An investigation of suffix frequency per se was recently made, by adopting
pseudoword contexts made up of illegal root-suffix combinations. Burani
et al. (1997) submitted, to both lexical decision and naming, pseudowords
that were made up of real roots combined with derivational suffixes not
compatible with the root. In order to demonstrate that the probability of
access through activation of morphemic units corresponding to suffixes is
constrained by their frequency values (see also Laudanna and Burani
1995), Burani et al. (1997) made use of suffixes belonging to two distinct
frequency ranges. In one experimental set, roots were combined with highfrequency suffixes, and the resulting pseudowords were contrasted with
pseudowords in which the same roots were combined with control sequences that had analogous orthographic frequency in final position of
Italian words, but were not suffixes. In the second set, a comparison was
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made between pseudowords composed of roots plus low-frequency suffixes, and the same roots combined with control low-frequency orthographic
final sequences. Roots were in both cases of medium frequency. In order to
control for asymmetries in the possibility to assign meaning to suffixed
pseudowords of the two kinds (i.e., with high- and low-frequency suffixes,
respectively), suffixed pseudowords in the two frequency sets were
matched for mean interpretability values derived from participants’ empirical ratings.
The lexical decision results by Burani et al. (1997) showed that the interference effect which is usually found on pseudowords that include real
affixes (see, e.g., Caramazza, Laudanna and Romani 1988; Taft and Forster
1975; see also, for derivational suffixes, Jarvella and Wennstedt 1993) is
conditioned by the frequency of the embedded suffixes: Longer reaction
times and higher error rates were found, with respect to control
pseudowords, only when pseudowords included high-frequency suffixes.
By contrast, pseudowords with low-frequency suffixes took no longer to be
rejected than control pseudowords. From these results on suffixed
pseudowords, Burani et al. (1997) concluded that the probability that suffixes will affect processing is conditioned by their frequency (see also
Laine 1996, for Finnish productive derivational suffixes causing interference effects on pseudoword lexical decision).
1.3. Suffix frequency, suffix numerosity, and productivity
In considering the frequency of suffixes, two main quantitative measures
can be adopted. On the one hand, frequency in the proper sense is calculated on word tokens, by summing up the cumulative frequency in a given
corpus of all the word tokens in which a given suffix occurs. On the other
hand, suffix frequency can be measured by calculating the number of word
types in which a given suffix occurs in a given language. This second
measure could be named numerosity of the suffix (as proposed by Burani
et al. 1995).
There could be reasons for considering numerosity (i.e., suffix typefrequency) as a better quantitative characterization for suffixes and a
stronger predictor of performance in access tasks. Suffix numerosity is
closely related to suffix productivity thus allowing the suffix to “emerge”
as a separate processing unit (see, e.g., Baayen 1989; 1992; Bybee 1995a).
However, there is a strong link and a complex interplay among suffix type
The interplay of root, suffix and whole-word frequency
161
and token frequency, productivity and probability of morphemic parsing
(Hay and Baayen 2002). In the study by Burani et al. (1997), suffix numerosity and suffix frequency were not disentangled because, after inspection
of frequency distributions, it was found that suffix token-frequency and
suffix numerosity tended to be highly correlated. Suffix frequency was
used in a broad sense to subsume the two quantitative measures that could
affect processing. Consequently, suffixes were either high or low on both
dimensions, frequency and numerosity, calculated on a corpus of Italian
written language (Istituto di Linguistica Computazionale CNR 1989).
1.4. Other properties of suffixes relevant for word processing
Some recent research has investigated the role of properties of derivational
suffixes in lexical access to words (see Bertram, Laine and Karvinen 1999,
for Finnish; Bertram, Schreuder and Baayen 2000, for Dutch). For both
Finnish and Dutch, properties like suffix productivity and suffix homonymy (i.e., suffix ambiguity in serving more than one semantic function)
were found to affect processing, with words including productive and nonhomonymous suffixes being more likely to induce morpheme-based processing (see also, for Japanese, Hagiwara et al. 1999).
In the studies by Bertram, Laine and Karvinen (1999) and Bertram,
Schreuder and Baayen (2000), no information was given on the frequency
values of the productive vs. unproductive suffixes, and the issue of suffix
frequency/numerosity was not assessed directly. A variation in productivity
usually corresponds to a variation in frequency/numerosity. However, although very related to suffix productivity, suffix frequency and numerosity
do not necessarily correspond to productivity. There may be differences in
suffix numerosity that do not correspond to differences in suffix productivity. At the same time, it is not always the case that differences in productivity correspond to differences in suffix frequency or numerosity. 2 Thus there
are reasons for investigating suffix frequency/numerosity in derived words,
without identifying these quantitative measures with productivity.
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2. The present study
While there is evidence that root frequency affects access to printed suffixed derived words, evidence for a role of quantitative properties of suffixes in visual processing comes almost exclusively from pseudowords.
The present study aimed at assessing simultaneously the roles of both root
and suffix frequency in Italian derived words, by testing different combinations of roots and suffixes with differing frequency. If the role of quantitative properties of morphemes have to be assessed per se, derived words
with morphemic constituents of different frequencies should be matched
for a number of factors, including orthographic/phonological transparency,
semantic transparency, and whole-word frequency.
Italian derivation occurs mostly through agglutination of suffixes to
roots which are not occurring words themselves (see Peperkamp 1995).
Orthographic/phonological transparency of derived forms with respect to
their roots is quite common, wide-spreading across different frequency
ranges of both words and morphemes, and can be easily controlled for.
Semantic transparency can also be kept under control, while varying suffix
frequency/numerosity. Suffix numerosity, i.e., the number of word types in
which a given affix occurs, is one determinant of semantic transparency,
but it does not identify with it (see Bybee 1995a). Moreover, in intramodal
tasks there might be reasons for expecting effects of morphological constituency also in derived words that are less transparent for meaning or in
semantically opaque words (see, e.g., Bentin and Feldman 1990; Feldman
and Soltano 1999; Plaut and Gonnerman 2000; Schreuder, Burani and
Baayen 2002; Stolz and Feldman 1995; Vannest and Boland 1999; but see
also, for contrasting evidence in cross-modal tasks, Marslen-Wilson et al.
1994).
Given the basic prediction that low-frequency words with two highfrequency constituents should be the best candidates for access through
morphemes, which predictions could be made for low-frequency words
that include only one high-frequency constituent (either the root or the
affix)? Would lexical access be equally sensitive to the higher frequency
constituent? Would it be differentially sensitive to the frequency of the root
and the affix, respectively? In some studies the assumption has been made
that root frequency effects should manifest themselves in low-frequency
derived words with frequent and productive suffixes. To our knowledge,
there were no investigations of whether root frequency effects would show
up in the context of low-frequency suffixes. Similarly, no study has inves-
The interplay of root, suffix and whole-word frequency
163
tigated whether high-frequency suffixes may affect the probability of morpheme-based access in the context of low-frequency roots. In synthesis, no
study has addressed the issue of whether low-frequency derived words that
include either one or both low-frequency constituents were likely to activate morphemic units at all.
Our predictions were developed in the framework of the model proposed first by Schreuder and Baayen (1995) (see, for recent updates,
Baayen and Schreuder 1999; 2000; Baayen, Schreuder and Sproat 2000).
This is a race model for the recognition of morphologically complex words
in which there are two parallel access routes, one based on whole-form
information, and the other based on morphemic decomposition. One assumption of the model is that, for the visual modality, the complete input is
available from the start. Thus in principle, for low-frequency derived
words, both root and suffix frequency should affect processing at the stages
in which morphemic access representations are activated over time by the
sensory input.
In the framework of this race model, it is crucial to assess the complex
balance between access through storage (whole-word activation) and access through computation (morphemic activation). An open issue is how
processing proceeds for low-frequency words which include low-frequency
constituent morphemes. This implies assessing the relation existing, in
terms of processing costs and benefits, between components in which morphemic units are segmented and activated, and subsequent components in
which they are re-combined in order to derive meaning.
So far, the probability of faster access through whole-word activation
has been suggested for high-frequency derived words that tend to be highly
lexicalized (Baayen and Neijt 1997; Burani and Laudanna 1992; Bybee
1995b; Chialant and Caramazza 1995; Frauenfelder and Schreuder 1992;
3
Schreuder and Baayen 1995). Additionally, whole-word storage has been
proposed for English derived words which include non-neutral affixes and
whose stems tend to cluster around recurring patterns thus constituting
“gangs” (Alegre and Gordon 1999b), or for derived words which include
unproductive suffixes (Bertram, Laine and Karvinen 1999; Bertram,
Schreuder and Baayen 2000; Hagiwara et al. 1999).
However, the possibility should be conceived that also low-frequency
derived words which include low-frequency morphemic constituents –
even if phonologically transparent – are more likely to be accessed as
whole forms through direct whole-word access. For these words, the reduced probability of access through morphemic decomposition would de-
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rive from the fact that the slight difference between the frequency of morphemes and whole-word frequency is not large enough for morphological
processing to result in benefits relative to whole-word based lexical access.
The following visual lexical decision experiments addressed the latter
issues by combining evidence from pseudoword and word processing. Experiment 1 was conducted on pseudowords, whereas both Experiments 2
and 3 involved words. Experiment 1 on pseudowords aimed at replicating
and extending results on the role of suffix quantitative properties in nonlexical contexts. It addressed issues that should help in interpreting results
from the two following experiments on words. By including suffixes in
pseudoword contexts in which the initial orthographic sequence did not
correspond to an existing root, the role of suffix frequency/numerosity
could be differentiated from its consequences on the semantic transparency
or interpretability of a newly derived form with respect to its base. At the
same time, by investigating stimulus contexts in which the lexical morphemic unit (the suffix) occurred in the rightmost part of the stimulus in
the absence of a morphemic unit on its left side, we aimed at providing
evidence for a role of morphemic units which is independent of sequential
left-to-right processing. Experiments 2 and 3 addressed the issue of the
interplay of root, suffix and whole-word frequency in access to derived
words, by orthogonally varying high- and low-frequency roots and suffixes
in low-frequency transparent derived Italian words. In order to specify the
balance between the processing routes based on whole-word and morphemic units, respectively, the derived words were contrasted with nonderived
words of analogously low frequency (Experiment 3).
3. Experiment 1
In Experiment 1, we aimed at replicating, with three sets of suffixes, the
effect of suffix frequency in lexical decision to pseudowords found by
Burani et al. (1997). In that study, suffixes were combined with real roots
to form pseudowords. In the present experiment, the pseudowords were
obtained by combining suffixes of varying frequencies with orthographic
sequences that did not correspond to real roots. If suffix frequency effects
were to occur in lexical decision to pseudowords of this sort, strong evidence for the role of suffixes in visual processing would be provided. If
activation of the morphemic units comprising a stimulus occurs irrespective of their sequential positions within the stimulus, provided they are
The interplay of root, suffix and whole-word frequency
165
frequent enough, the prediction could be made that high-frequency suffixes
are activated and play some role also when affixed after nonroots.
The expected result has twofold implications. On the one hand, if highfrequency suffixes delay lexical decisions to pseudowords even when they
occur in stimuli that do not contain real roots, it could be concluded that
the effects of frequency/numerosity of suffixes occur at a processing stage
in which affix morphemes are available independently of their semantic
content. When suffixes are combined with nonroots, no interpretability of
the combination should be expected, because of the absence of a meaningful component in first position (for the effects of interpretability of new
root-suffix combinations in lexical access, see Burani et al. 1999; see also,
for the effects of interpretability on novel Dutch compounds, Coolen, van
Jaarsveldt and Schreuder 1991; van Jaarsveldt, Coolen and Schreuder
1994).
On the other hand, if we were to show a frequency effect induced by a
morphemic unit located in the rightmost position of the stimulus, within an
orthographic context in which no lexical or morphemic unit occurs in left
position, we would challenge a sequential search model, which predicts
that the frequency of the second constituent should not affect lexical processing (Taft and Forster 1976). Evidence against this sort of model has
been provided by studies which used both compound nonwords (Lima and
Pollatsek 1983), and real compound words (Andrews 1986; Andrews and
Davies 1999; Pollatsek, Hyönä and Bertram 2000). The main finding of
these studies, which mainly employed lexical decision, but also the recording of eye movements in sentence reading (Pollatsek, Hyönä and Bertram
2000), was an effect of the lexical status or of the frequency of the second
constituent. Evidence for a frequency effect of the second constituent when
this is a suffix is still lacking. However, even in a theoretical framework
which incorporates principles of interactive activation (Taft 1994), it is still
assumed that, while inflectional endings would be stripped off in word
processing, derivational suffixes would not, because of their different role
in processing. Within the latter framework, all the pseudowords that are
tested in our experiment, provided they are equated in their leftmost nonlexical part on purely orthographic grounds, should be rejected equally
fast, irrespective of the presence of a suffix on their rightmost side. In contrast with these predictions, if interference effects on nonword lexical decision do arise when the stimulus includes a high-frequency suffix in combination with a nonroot orthographic sequence, a model in which the
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processing system activates frequent morphemic units, irrespective of their
relative locations within the word, would be supported
In Experiment 1, three sets of Italian derivational suffixes were selected. The three sets, matched for length in letters and phonemes, and for
orthographic/phonological structure, differed only for frequency, calculated both on word tokens and on word types. Suffixes in the three sets could
be considered of high, medium and low frequency, respectively, by considering the overall distribution of frequency values of Italian suffixes of the
same length. The main prediction was that high-frequency suffixes should
cause more interference on nonword decision when included in
pseudoword contexts, relative to low-frequency suffixes. Suffixes of medium frequency might either not constitute sufficiently activated processing
units for interference to occur, or they might show interference effects of a
smaller size than high-frequency suffixes.
3.1. Method
3.1.1. Materials and design
Nine suffixes were selected, equally subdivided in three experimental sets,
of high, medium and low frequency, respectively. Frequencies, in this experiment and in all the following experiments, were derived from a corpus
of Italian written language of 1.5 million tokens (Istituto di Linguistica
Computazionale CNR 1989). The mean suffix frequencies in the three sets,
calculated on word tokens, were 1,060 per 1.5 million (range: 639-1,557);
68.3 (range: 55-90), and 12.3 (range: 7-18), for the three sets, respectively.
Differences in mean suffix numerosity between the three sets, calculated
on word types in the corpus, paralleled differences in frequency. The mean
number of word types in which suffixes occurred were 165 (range: 145187), 20.6 (range: 11-39), and 6.3 (range: 2-10) for the three sets, respectively.
There were both nominal and adjectival suffixes. No suffix was homonymous with another Italian suffix. All suffixes were four-letter long and
were matched across sets for length in phonemes and for syllabic structure.
For each suffix, a control sequence with similar orthographic and syllabic structure was selected. The sequences corresponding to a suffix and
the control sequences were matched for orthographic frequency in word
final position in each set. The mean frequencies of control sequences in
The interplay of root, suffix and whole-word frequency
167
word final position were: 1,538 per 1.5 million for the first set; 472 for the
second set; 64 for the third set. These values were matched to the mean
frequencies of the orthographic strings corresponding to the selected suffixes, calculated in word final position and including both real suffixes and
pseudosuffixes: 1,335 per 1.5 million for the high-frequency set; 411 for
the medium-frequency set, and 62 for the low-frequency set, respectively.
The suffixes were combined with orthographically legal letter sequences that did not correspond to any existing root. Each suffix was combined
with four different pseudoroots, for a total of twelve pseudowords in each
set. The length of pseudowords fell within the length range of Italian words
including the same suffix, and respected as much as possible the distribution of word length for each suffix in the Italian language (calculations
were based on Ratti et al. 1988). Mean lengths in letters of the
pseudowords were 9.1, 8.6, and 8.7 for the three sets, respectively.
Each suffixed pseudoword was matched with a control pseudoword that
included the same pseudoroot in combination with the orthographic sequence that constituted the control sequence for the suffix. Thus
pseudowords in each suffixed-control pair had the same length, the same
syllabic structure, similar orthographic/phonological structure, and similar
orthographic frequency of the final part, either corresponding to a suffix or
to a nonsuffix. Pseudowords including suffixes and control sequences were
also matched for bigram frequency. Mean bigram frequencies, calculated
on the base of the natural logarithm, were: 10.49, 10.57, and 10.60 for
pseudowords in the three suffixed sets; they were 10.80, 10.55, and 10.44
for pseudowords in control sets. In combining initial letter strings with
suffixes and control letter sequences, we avoided the presence in the
pseudowords of embedded real words. Pseudowords in the six sets were
also matched for their overall degree of orthographic similarity to a real
word, i.e., for the number of orthographic neighbors. Adopting the N-count
measure (Coltheart et al. 1977), i.e., the total number of words that can be
obtained from each pseudoword by replacing one letter at a time with another letter, while preserving the other letters’ positions, we determined
that the great majority of pseudowords had a null N-count (with a few exceptions of N-count = 1, balanced across sets), i.e., we obtained
pseudowords that were equally dissimilar from existing words, according
to the N-count metric.
In synthesis, there were six sets of pseudowords, arranged in a 2x3 design, in which the main factors were the presence vs. absence of a suffix,
and the high vs. medium vs. low frequency of the orthographic sequence
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corresponding either to a suffix or to a nonsuffix. In each of the six sets,
there were 12 pseudowords (4 for each suffix or control sequence), for a
total of 72 experimental stimuli, 36 suffixed and 36 controls. The experimental items, with the mean RT and percent error for each item, are reported in Appendix A.
In order to avoid presenting the same pseudoroot to the same participant
both in the suffixed and in the nonsuffixed control condition, each experimental set was split in two subsets of 6 items each. Each participant was
presented with 36 experimental pseudowords, 18 suffixed and 18 pseudosuffixed, in which no pseudoroot was repeated. In each subset there were
two instances of the same suffix or final control sequence. For each set of
suffixed and control pseudowords, the entire set of single scores was provided by two participants presented with two complementary sublists.
In each sublist, the 36 experimental pseudowords were presented together with 66 filler pseudowords and 102 filler words. Each participant
was presented with a total of 204 stimuli. Filler stimuli were the same in
each of the two sublists: Words included medium/low frequency singular
nouns and adjectives, either derivationally suffixed or nonsuffixed, in a
proportion that reflected the composition of the Italian basic dictionary in
the medium/low frequency range (see Thornton, Iacobini and Burani 1994;
1997). Each suffix and each control final sequence that occurred in experimental pseudowords was also included in the same number of filler words.
Filler pseudowords were drawn from words analogous to the filler words
by changing one or two letters in different positions. Mean length was the
same for words and pseudowords (range: 6-11 letters).
The list was presented to participants in a single experimental session,
arranged in three randomized blocks of 68 items each. For each block,
participants were assigned to one of two different randomizations of items.
Each experimental list was preceded by a practice list of 50 items, 25
words and 25 pseudowords, assigned in the same proportion to two randomized blocks.
3.1.2. Procedure
Participants were tested individually in a soundproof experimental booth.
They received standard lexical decision printed instructions in which they
were asked to decide as quickly and as accurately as possible whether a
presented letter string was an Italian word or not. If it was a word (YES
The interplay of root, suffix and whole-word frequency
169
response), they had to press the right one of two response keys, otherwise
(NO response) the left one. For left-handed participants, the order of the
response buttons was reversed.
Each trial started with the presentation of a fixation mark (a cross) in
the center of the screen for 400 ms, followed after 300 ms by the stimulus
centered at the same position. Stimuli were presented on a monitor in white
uppercase letters on a dark background and remained on the screen until
the participant pressed one of the two response buttons. They disappeared
after a time period of 1,500 milliseconds if no response was given. A new
trial began 1,200 ms after responding or time-out. If a participant responded more slowly than the preset limit of 1.5 sec, the words FUORI TEMPO
(‘out of time’) appeared on the screen. If the participant gave the wrong
response, the word ERRORE (‘error’) appeared on the screen. This signal
was displayed for 500 ms. The interval between the disappearance of the
feedback and the next warning signal was 1,200 ms. There was a pause
after each block of stimuli. The total duration of the experimental session
was approximately 20 minutes.
3.1.3. Participants
Forty-eight participants, mostly University students, were paid to participate in the experiment. All were native speakers of Italian.
3.2. Results and discussion
The data of four participants, whose mean reaction times for correct responses or whose error rates were more extreme than 2 s.d from the mean
of all participants, were excluded from further analysis. Using the remaining forty-four participants, the mean reaction times and error rates for all
items were obtained and one pair of items in the medium-frequency set was
removed because the number of errors for one of the two members of the
pair (crofusso) was more than 2.5 s.d. above the mean. When means for
length, bigram frequency and N-count were recalculated after removing the
two paired items, the sets were still balanced. The remaining observations
were used to calculate participants’ and items’ mean reaction times and
error scores. Mean reaction times by items and percentages of errors for
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the three experimental categories and their respective controls are shown in
Table 1.
Table 1. Experiment 1. Mean reaction times by items in ms. and % error.
Suffixed and control (nonsuffixed) pseudowords, with high-frequency
(HF), medium-frequency (MF), and low-frequency (LF) final sequences
Suffixed
Control
Difference
HF
Mean RT
% Error
739
13.6
700
6.1
+39
+ 7.5
MF
Mean RT
%Error
701
4.1
701
7.4
0
- 3.3
LF
Mean RT
%Error
680
4.6
679
4.2
+1
+ 0.4
Results were submitted to a mixed three-way analysis of variance with two
within-participants factors: Suffixedness (suffixed vs. nonsuffixed
pseudowords) and frequency of final sequence, both suffix and control
(high vs. medium vs. low). The third between-participants factor was list
(first vs. second sublist, each administered to one half of participants).
The ANOVAs were performed both by participants and by items and
showed interaction between suffixedness and frequency on both reaction
times (F1(2,84) = 7.59, p<.001, MSE= 1,412.1; F2(2,58) = 3.34, p=.04,
MSE= 977.3) and errors (F1(2,84) = 5.92, p=.004, MSE= 117.2; F2(2,58)
= 5.97, p=.004, MSE= 1.48). Results differed across the three experimental
sets when suffixed pseudowords were compared to their respective controls. Comparisons between suffixed-control pairs based on the Duncan
test on means by items revealed that suffixed pseudowords in the highfrequency set were significantly (39 ms) slower (p=.03) and gave rise to
significantly (7.5%) more errors (p=.003) with respect to controls. By contrast, suffixed pseudowords were equally fast relative to their controls in
both the medium-frequency and the low-frequency sets (p>.1 in both cases). Percent errors on suffixed pseudowords were 3.3 less and 0.4 more in
the medium-frequency and in the low-frequency sets, respectively. These
differences were not significant (p>.1 in both cases).
An effect of frequency was found on both reaction times (F1(2,84) =
19.78, p<.001, MSE= 1,505.6; F2(2,58) = 10.12, p<.001, MSE= 977.3),
The interplay of root, suffix and whole-word frequency
171
and errors (F1(2,84) = 5.76, p=.004, MSE= 122.5; F2(2,58) = 6.28, p=.003,
MSE= 1.48). The main effect of suffixedness (suffixed vs. nonsuffixed
pseudowords) was found on reaction times by participants only (F1(1,42) =
6.57, p=.013, MSE= 900.46; F2(1,58) = 2.56, p>.1, MSE= 977.3). No main
effect of suffixedness was found on errors (F1(1,42) = 2.03, p>.1, MSE=
72.23; F2(1,58) = 1.27, p>.1, MSE= 1.48).
As revealed by the strong interaction between suffixedness and frequency of final sequence, and by post-hoc comparisons, response latencies
and percentages of errors to suffixed pseudowords were higher, relative to
their controls, only when the pseudowords included a high-frequency suffix. By contrast, pseudowords that included either medium-frequency or
low-frequency suffixes did not reveal longer reaction times nor lower accuracy with respect to matched orthographic controls. These results confirm
those obtained by Burani et al. (1997): High-frequency suffixes activate
corresponding morphemic access units in pseudoword contexts. By contrast, no access unit seems to be available for suffixes that are either medium- or low-frequency, at least not in pseudoword contexts and within the
time required to perform lexical decision.
The present results allow us to build on the findings by Burani et al.
(1997). In the present experiment, the interference effect caused by highfrequency suffixes occurred with suffixes that were combined with nonexisting roots. Hence, activation of morphemic lexical units corresponding to
suffixes occurred in the absence of a real root on their left side. This finding hardly seems compatible with sequential search accounts (Taft and
Forster 1976), and with recent reformulations (Taft 1994), which predict
that the frequency of the second constituent, the derivational suffix, should
not affect lexical processing in the absence of a lexical unit as first constituent.
4. Experiment 2
Experiment 1 provided evidence for a role in processing of suffix frequency, with high-frequency suffixes significantly affecting rejection latencies
in visual lexical decisions to pseudowords. In Experiment 1 there was no
evidence that suffixes of medium/low frequency which extended up to a
frequency of 90 per 1.5 million constituted effective processing units: No
interference arose in lexical decision, when a suffix was either medium- or
low-frequency.
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Burani and Thornton
The role of suffix frequency in lexical decision to real words was assessed in Experiment 2, by varying both root and suffix frequency in transparent derived words of low surface frequency. Derived words included
suffixes belonging to two sets of differing frequencies. Suffixes of high
frequency were contrasted with suffixes that were of medium/low frequency. In Experiment 1 there was no evidence for differences between medium- and low-frequency suffixes. Hence, suffixes from both the latter frequency ranges were pooled together in a single set. For simplicity,
hereafter we will refer to medium/low- frequency suffixes as lowfrequency suffixes.
All low-frequency derived words should in principle be accessed
through constituent morphemes – even when both the root and the suffix
are low-frequency, the derived word is nevertheless lower in frequency
than its constituent morphemes. Hence, for low-frequency derived words
that are equated for all the relevant properties except for frequency of the
two constituent morphemes, either high or low, predictions were that both
reaction times and error rates should not be function of whole-word frequency, but should rather reflect differences in the frequency of morphemic constituents.
Words including higher-frequency morphemes were expected to be accessed more quickly and more accurately than words including lowerfrequency morphemes, with words including both root and suffix of high
frequency being the fastest and the most accurate, and words with lowfrequency root and suffix being the slowest and the least accurate. Derived
words in which only one morpheme, either the root or the suffix, is of high
frequency, were expected to show intermediate reaction times and error
rates. If for printed stimuli simultaneous parallel activation of both root and
affix is assumed, irrespectively of their relative positions within the word,
words in which the high-frequency constituent is either the root or the suffix were not expected to differ in activation times.
4.1. Method
4.1.1. Materials and design
Four sets of equally low-frequency suffixed derived words were selected.
In the four sets, root and suffix frequency varied orthogonally: The first set
included high-frequency roots and high-frequency suffixes (HH); the sec-
The interplay of root, suffix and whole-word frequency
173
ond set included low-frequency roots and high-frequency suffixes (LH);
the third set included high-frequency roots and low-frequency suffixes
(HL); the fourth set included low-frequency roots and low-frequency suffixes (LL). Suffixes were either high- or low-frequency on both tokens and
types, i.e., on both frequency tout court and numerosity. The root frequency measure included the cumulative frequency of both the inflected and the
derived forms of the base.
Thirteen words (nouns and adjectives) were included in each set, for a
total of nine different suffixes in each set. No suffix was homonymous with
a different Italian suffix. The same suffixes were included in the two highfrequency suffix sets and in the two low-frequency suffix sets, respectively. Suffixes were three to five letters long. High-frequency suffixes and
low-frequency suffixes were matched for length and syllabic structure.
Roots were different in the four sets. Root length was balanced across sets.
The roots belonged to different grammatical categories (i.e., nouns, adjectives and verbs) that were balanced across sets. All the derived words were
presented in singular citation form. They were orthographically and phonologically transparent with respect to their bases, i.e., there was no orthographic/phonological assimilation at the boundary between root and suffix.
Across the four sets, words were matched for surface frequency, length,
syllable structure and bigram frequency. The 52 experimental words were
presented together with 108 filler words and 160 filler pseudowords, for a
total of 320 stimuli. Any suffix that occurred in experimental words occurred also in the same number of filler pseudowords. Filler pseudowords
were drawn from words analogous to the filler words by changing one or
two letters in different positions in the word. Filler words included medium/low-frequency singular nouns and adjectives, either morphologically
complex or simple, in a proportion that reflected the composition of the
Italian basic dictionary in the medium/low frequency range (Thornton,
Iacobini and Burani 1994; 1997). Mean length was the same for words and
pseudowords (range: 6-11 letters).
The list was presented to participants in a single experimental session,
arranged in four randomized blocks of 80 items each. Each participant was
presented with a different block randomization and with a different randomization of items within each block. Each experimental list was preceded by a practice list of 40 items, 20 words and 20 pseudowords, assigned in
the same proportion to two randomized blocks.
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Burani and Thornton
4.1.2. Procedure
The procedure was the same as in Experiment 1. The experimental session
lasted about 30 minutes.
4.1.3. Participants
Forty-five participants, mostly University students, were paid to participate
in the experiment. All were native speakers of Italian.
4.2. Results and discussion
The data of ten participants, who made more than 15 percent errors on the
experimental words, were excluded from further analysis. Using the remaining thirty-five participants, the mean reaction times and error rates for
all items were obtained. We removed four experimental words that showed
error rates exceeding 40% from the data set. One word (tenerume) was
removed in set HL, two words (aratore and larvale) in set LH, and one
word (ameboide) in set LL. One item (rimanenza) was removed in set HH
because it was the only word which included a prefixed bound root of an
irregular verb. Removal of these items did not affect the matching of the
four sets for the relevant variables.
In Table 2 the mean values with standard deviations for the variables in
each experimental set are reported. The list of the experimental items, with
root frequency, suffix frequency, word frequency, mean RT and percent
error for each item, are reported in Appendix B.
The remaining observations were used to calculate participant and item
mean reaction times and error scores. Mean reaction times by items and
percentages of errors for the four experimental sets are shown in Table 3.
The interplay of root, suffix and whole-word frequency
175
Table 2. Experiment 2. Mean values and standard deviations (s.d.) for the relevant
variables.
HH = Derived words with high-frequency root and high-frequency suffix
HL = Derived words with high-frequency root and low-frequency suffix
LH = Derived words with low-frequency root and high-frequency suffix
LL = Derived words with low-frequency root and low-frequency suffix
HH
Root frequency
Family size
Suffix frequency
Suffix numerosity
Semantic relatedness
Familiarity
Bigram frequency
Word length in letters
Root length in letters
Suffix length in letters
Word frequency
HL
LH
LL
Mean
s.d.
Mean
s.d.
Mean
s.d.
Mean
s.d.
501
412.1
507
409.8
33.5
19.1
33.3
21.9
15.7
1,859
246
3.77
6.57
10.79
8.2
4.4
3.8
3.1
8.05
1,515
123.6
0.43
0.78
0.4
1.5
1.4
0.6
2.8
10.20
57
17.3
3.47
6.05
10.69
8.2
4.3
3.9
3.5
3.82
33.7
10.8
0.89
1.03
0.3
1.1
1.1
0.5
3.2
4.4
1,636
217
3.66
6.15
10.56
8.4
4.5
3.9
2.2
2.5
1,260
101.39
0.68
0.9
0.3
1.0
1.0
0.5
2.3
4.2
58
17.7
3.45
5.75
10.60
8.2
4.4
3.8
1.7
1.7
32.5
10.6
0.95
1.01
0.3
0.9
0.8
0.6
1.2
Table 3. Experiment 2. Mean reaction times by items in ms and % error.
Suffixed derived words with high-frequency root and high-frequency suffix (HH); high-frequency root and low-frequency suffix (HL); lowfrequency root and high-frequency suffix (LH); low-frequency root and
low-frequency suffix (LL).
HH
HL
Mean Reaction Time
% Error
597
2.5
LH
624
5.9
LL
Mean Reaction Time
% Error
634
6.7
670
12.2
Results were submitted to two-way analyses of variance, with root frequency (high vs. low) and suffix frequency (high vs. low) as the two factors. There were main effects of both root frequency and suffix frequency
on both reaction times and error rates. For root frequency, F1(1,34)=77.83,
p<.001, MSE= 771.3; F2(1,43)= 7.96, p<.01, MSE= 2,551.55 on reaction
times; F1(1,34)= 13.96, p<.001, MSE= 68.9; F2(1,43)= 6.08, p<.025,
MSE= 6.59 on error rates. For suffix frequency, F1(1,34)= 28.92, p<.001,
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Burani and Thornton
MSE= 1,088; F2(1,43)= 4.77, p<.05, MSE= 2,551.55 on reaction times;
F1(1,34)= 11.00, p=.002, MSE= 63.59; F2(1,43)= 4.38, p<.05, MSE= 6.59
on error rates. There was no interaction between the two factors (p>.1 in
all the analyses).
Results on both reaction times and error rates strictly paralleled differences in frequency of constituent morphemes, with words including highfrequency constituents determining quicker and more accurate performance. No differential role of root frequency with respect to suffix frequency was apparent in the data. Hence, results seemed to confirm the
hypothesis of access through activation of morphemic constituents for lowfrequency derived words.
We controlled post-hoc for possible residual asymmetries in the properties of the experimental words that could have contributed to the effect.
Three properties of the derived words were considered: the semantic relatedness to the base, the word’s morphological family size, and the word
familiarity.
4.2.1. Ratings of semantic relatedness with the base
According to some authors, effects of morphological structure should be
found preferentially in derived words that are semantically transparent (or
related) with respect to the base (Marslen-Wilson et al. 1994; but see also,
for contrasting data and accounts, Bentin and Feldman 1990; Feldman and
Soltano 1999; Plaut and Gonnerman 2000; Schreuder, Burani and Baayen
2002; Stolz and Feldman 1995; Vannest and Boland 1999). In selecting
stimuli, we aimed at balancing words in the four sets for the degree of semantic transparency. We controlled for semantic transparency of the derived words with respect to their bases by excluding semantically opaque
words, and by including in each set approximately the same number of
suffixes that could be considered either productive or unproductive on the
basis of different measures of productivity. In each frequency set there
were suffixes that could be considered productive because they had been
used to coin a substantial number of neologisms in the last fifty years, or
could be rated as productive on the basis of the quantitative measure of
productivity proposed by Baayen (1989; 1992). Analogously, in each set
there was a similar number of suffixes that could be considered scarcely
productive or unproductive on either one or both the latter measures.
The interplay of root, suffix and whole-word frequency
177
However, it could not be excluded that, independently of productivity
rated in the latter ways, derived words including high-frequency suffixes
might result in greater semantic transparency with respect to their bases by
virtue of suffix numerosity itself. High suffix numerosity is related to a
greater number of derived words which tend to share a similar part of
meaning, namely the meaning carried by the suffix. Analogously, it could
not be excluded that words might have different semantic transparency
values due to specific idiosyncrasies.
Derived words were submitted to empirical ratings for semantic relatedness with their base. Each derived word was paired with its base word.
The printed list of word-pairs was presented in different random orders to
thirty-eight University students who had not participated in the lexical
decision experiment. Participants had to rate, for each pair, on a five-point
scale ranging from “Very unrelated” to “Very related”, how “related in
meaning” they thought the first word (the derived word) was to the second
word (the base word).
Mean ratings of semantic relatedness with the base were 3.77 (s.d. 0.43)
for HH words; 3.47 (s.d. 0.89) for HL words; 3.66 (s.d. 0.68) for LH
words; 3.45 (0.95) for LL words, respectively. A two-way ANOVA with
root frequency (high vs. low) and suffix frequency (high vs. low) as factors
was performed on semantic relatedness rating means both by participants
and by items. A suffix frequency effect was found, by participants only (F1
(1,37) = 15.65, p<.001, MSE= 195.1; F2 (1,43) = 1.35, p=.25, MSE=.55),
with words including high-frequency suffixes being rated as significantly
more related for meaning to their base words (mean semantic relatedness:
3.71) than words including low-frequency suffixes (mean semantic relatedness: 3.46). Neither root frequency nor the interaction were significant
(F<1 in both cases).
In order to assure that the suffix frequency effect was not confounded
with the fact that words with high-frequency suffixes were more transparent for meaning than words with low-frequency suffixes, two further analyses were carried out. First, the results of lexical decision were reanalyzed
by excluding from the two sets with low-frequency suffixes the least transparent items (four items in all), thus obtaining new sets that were perfectly
matched for semantic transparency. After matching sets for semantic transparency, the results of ANOVAs did not change, but showed even stronger
effects of both root and suffix frequency (F2 (1,39) = 7.3, p<.025, MSE=
2,314.56; F2 (1,39) = 9.46, p<.005, MSE= 2,314.56 on reaction times for
root and suffix, respectively; F2 (1,39) = 6.08, p<.025, MSE= 6.36; F2
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Burani and Thornton
(1,39) = 7.88, p<.01, MSE= 6.36, on error rates for root and suffix, respectively), and no interaction (p>.1). Furthermore, post-hoc correlation analysis did not reveal significant correlation (one-tailed test) of reaction time
with semantic relatedness (r = -.14, t(45)=0.92, p>.1). Hence we could
exclude that semantic transparency was responsible for the effects found
(see also, for evidence that semantic transparency itself cannot explain why
some suffixes induce decomposition while others do not, Vannest and Boland 1999).
4.2.2. Morphological family size
Recently, Bertram, Baayen and Schreuder (2000) reported evidence for the
role, in the lexical processing of Dutch complex words, of morphological
family size, i.e., the type count of derived words and compounds with a
given base word as a constituent. This type count of the number of morphological family members, that has been found to be a strong independent
co-determinant of response latencies for Dutch monomorphemic and inflected words (de Jong, Schreuder and Baayen 2000; Schreuder and
Baayen 1997), also affected latencies to derived words. Bertram, Baayen
and Schreuder (2000) suggested that a large family size of the base word
facilitates lexical processing for most suffixed derived words. According to
the authors, the facilitatory effect of a large family size is due to semantic
activation spreading from a complex word to its family members.
The family size of the base root – i.e., the root numerosity – could in
principle affect processing of Italian derived words. In our study, a larger
morphological family size should be expected in both sets with high root
frequency, relative to the sets with low root frequency. For each target
word, the number of word types that share the same root in the corpus was
counted. The obtained mean number of morphological family members
was 15.7 (s.d. 8.05) for HH words, 10.2 (s.d. 3.82) for HL words, 4.4 (s.d.
2.5) for LH words, and 4.2 (s.d. 1.7) for LL words, respectively. A twoway ANOVA with root frequency (high vs. low) and suffix frequency
(high vs. low) as the two factors was performed on family size values in the
four sets. As expected, a difference in the numerosity of the morphological
family between words with high and low frequency roots was found
(F(1,43)= 39.01, p<.0001, MSE= 22.5). A difference in morphological
family size between words with high and low frequency suffixes was also
found (F(1,43)= 4.24, p<.05, MSE= 22.5), and a marginally significant
The interplay of root, suffix and whole-word frequency
179
interaction (F(1,43)= 3.43, p=.07, MSE=22.5). A two-tailed t-test between
HH and HL sets revealed a significant difference in family size between
the two sets with high-frequency root (t(22)= 2.11, p<.05).
The differences in family size among the experimental sets were in the
same direction as the differences in response times, with HH words having
a mean larger number of family members (15.7) than HL words (10.2), and
words with high-frequency suffixes a mean larger number of family members (10.1) than words with low-frequency suffixes (7.2). Hence we assessed whether these differences could be responsible for part of the effect
that was found in lexical decision.
Two further analyses were made. First, we reanalyzed the results of lexical decision by excluding two items in each of the two sets with highfrequency roots, to obtain new sets that were matched for mean family size.
After matching sets for family size, the results of ANOVAs did not change,
but still showed effects of both root and suffix frequency (F2(1,39)= 7.82,
p=.008, MSE= 2,602.1; F2 (1,39) = 4.31, p<.05, MSE= 2,602.1, on reaction times for root and suffix, respectively; F2 (1,39) = 6.7, p=.01, MSE=
6.75; F2 (1,39) = 4.54, p= .04, MSE= 6.75, on error rates for root and suffix, respectively), and no interaction (p>.1). Furthermore, post-hoc correlation analysis did not reveal any correlation of reaction time with family
size (r=.04, t(45)=0.27, p>.1). Thus the hypothesis that differences in family size were responsible for part of the effects found in lexical decision
could be rejected.
4.2.3. Familiarity ratings
Words from the low-frequency range of a corpus may differ in familiarity,
and familiarity is usually a good predictor of lexical decision performance
(Connine et al. 1990; Gernsbacher 1984). Although our derived words
were matched for whole-word frequency, we made a post-hoc check for
familiarity.
The derived words were submitted to twenty-seven University students
for familiarity ratings. Participants had to rate the printed words on a seven-point scale ranging from “Unknown” (1) to “Very well known” (7). All
the derived words received high familiarity ratings. However, there were
differences between the four groups. Mean familiarity ratings were: 6.57
(s.d. 0.78) for HH words; 6.05 (s.d. 1.03) for HL words; 6.15 (s.d. 0.9) for
LH words; 5.75 (s.d. 1.01) for LL words.
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Burani and Thornton
A two-way ANOVA with root frequency (high vs. low) and suffix frequency (high vs. low) as the two factors performed on familiarity rating
means both by participants and by items showed significant effects of both
factors, by participants only (F1(1,26) = 15.03, p<.001, MSE= .51;
F2(1,43) = 2.56, p>.1, MSE= .88 for root frequency; F1(1,26) = 44.11,
p<.001, MSE= .46; F2(1,43) = 1.74, p>.1, MSE= .88 for suffix frequency),
and no interaction (F<1).
Results on familiarity ratings paralleled results on reaction times and
accuracy, with words including high-frequency roots and high-frequency
suffixes being rated as more familiar than words with low-frequency roots
and suffixes. Differences in rated familiarity were so clean that we could
not select post-hoc a subset matched for familiarity. Moreover, post-hoc
correlation analysis revealed a strong correlation of reaction time with
familiarity (r = -.66, t(45) = 5.83, p<.0001).
4.2.4. Ad interim considerations
In synthesis, the results of post-hoc controls on three possible factors contributing to the effects found at lexical decision (i.e., semantic relatedness
with the base, morphological family size, and word familiarity) evidentiated word familiarity as a possible determinant of lexical decision performance. There could be reasons for adopting differences in rated familiarity
of morphologically complex words as evidence per se for access to morphemic constituency (see Bertram, Baayen and Schreuder 2000; Schreuder
and Baayen 1997). However, it could also be the case that word familiarity
provides a different source of explanation for the effect we found. In Experiment 3, we tried to disentangle the role of morphemic frequency from
that of word familiarity, while addressing further processing issues.
5. Experiment 3
The aim of Experiment 3 was twofold. First, we aimed at detailing the
effects found in Experiment 2 with different and larger sets of derived
words, better balanced for properties like semantic relatedness with the
base, morphological family size and rated familiarity. Second, we assessed
whether slower reaction times and higher error rates to words including
both a root and a suffix of low frequency (LL words) were a function of
The interplay of root, suffix and whole-word frequency
181
the low frequency of constituent morphemes, or whether performance was
merely a function of low whole-word surface frequency. The latter possibility would imply that, for low-frequency derived words with both constituents of low-frequency, the output of lexical decision does not result
from morphological processing, but from whole-word processing. For lowfrequency derived words whose constituents are both low-frequency, the
moderate difference between the frequency of morphemes and whole-word
frequency (with root and suffix only slightly higher in frequency than the
whole-word) might not be large enough for morphological processing to
result in benefits relative to access based on the whole-word.
To address the latter issue, a set of nonderived words (ND) was
matched for frequency to four new sets of low-frequency derived words
that included morphemes of differing frequencies. Analogously to Experiment 2, the first set of derived words included high-frequency roots and
high-frequency suffixes (HH); the second set included low-frequency roots
and high-frequency suffixes (LH); the third set high-frequency roots and
low-frequency suffixes (HL); the fourth set low-frequency roots and lowfrequency suffixes (LL). Words in the five sets (the four sets of derived
words and the set of underived words) had the same mean low surface frequency and were matched for all the relevant variables, including familiarity. The only difference was that words in the fifth (nonderived) set did not
4
include any derivational suffix.
Predictions were the following. If LL derived words with both lowfrequency constituents are accessed preferentially as whole-words and no
morpheme-based access succeeds because of including exceedingly lowfrequency roots and suffixes, LL derived words should show similar results
to nonderived (ND) words: For both LL and ND words, reaction times and
error rates should be function of surface frequency only. If, by contrast,
activation of morphemes is involved in access to LL derived words, and if
morphemic activation implies processing advantages because of accessing
a root and a suffix which are, although slightly, higher in frequency than
the whole-word, LL derived words should be quicker than nonderived
words. The latter do not benefit in fact from any constituent morpheme of
higher frequency.5 If the closer matching for familiarity, semantic relatedness and morphological family size obtained for words in the experimental
sets of Experiment 3 does not make any contribution to results, HL and LH
derived words which include one high-frequency constituent (either the
root or the suffix), should show intermediate reaction times and error rates
relative to LL words on the one hand, and HH derived words on the other.
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Burani and Thornton
Accordingly, HH derived words with both constituents of high-frequency
should be the most quickly and most accurately recognized.
5.1. Method
5.1.1. Materials and design
The five experimental sets included seventeen words each, nouns and adjectives in analogous proportions in each set. In the four derived sets, there
were nine different high-frequency suffixes, and ten different lowfrequency suffixes, with analogous distributions in the two high-frequency
suffix sets, and in the two low-frequency suffix sets, respectively. No suffix was homonymous to a different Italian suffix. Suffixes were three to
five letters long. High-frequency suffixes and low-frequency suffixes were
matched for length and syllabic structure. Roots were different in the four
sets, and belonged to different grammatical categories (i.e., nouns, adjectives and verbs) that were balanced across sets. Root length was balanced
across sets. Analogously to Experiment 2, suffixes were either high- or
low-frequency on both word tokens (suffix frequency) and word types
(suffix numerosity), and the root frequency included the cumulative frequency of both the inflected and the derived forms of the base. The highfrequency root words had also a larger mean family size than lowfrequency root words. Words were matched for mean morphological family size across sets with the same root frequency. All the derived words
were orthographically and phonologically transparent with respect to their
bases.
All words in the five sets were presented in the citation form. Words
were matched, across the five sets, for surface frequency, length, syllabic
structure and bigram frequency. The five sets were also matched for rated
familiarity (familiarity ratings were obtained on a seven-point scale from
twenty-four participants, see Experiment 2 for details about the method),
and the four sets of derived words were matched for semantic relatedness
with the base (semantic relatedness ratings were obtained on a seven-point
scale from twenty-four different participants; see Experiment 2 for details
concerning the method). The mean values with standard deviations for the
relevant variables in each experimental set are reported in Table 4. The list
of stimuli, with root frequency, suffix frequency, word frequency, mean
6
RT and percent error for each item are reported in Appendix C.
The interplay of root, suffix and whole-word frequency
183
The 85 experimental words were presented together with 115 filler
words and 200 filler pseudowords, for a total of 400 stimuli. Any suffix
that occurred in the experimental words occurred also in the same number
of filler pseudowords. The filler pseudowords were drawn from words
analogous to the filler words by changing one or two letters in different
positions in the word. The filler words included medium/low-frequency
singular nouns and adjectives, either morphologically complex or simple,
in a proportion that reflected the composition of the Italian basic dictionary
in the medium/low frequency range (Thornton, Iacobini and Burani 1994;
1997). The mean length was the same for words and pseudowords (range:
6-11 letters).
The list was presented to participants in a single experimental session,
arranged in five randomized blocks of eighty items each. Each participant
was presented with a different block randomization and with a different
randomization of items within each block. Each experimental list was preceded by a practice list of 40 items of 20 words and 20 pseudowords, assigned in the same proportion to two randomized blocks.
Table 4. Experiment 3. Mean values and standard deviation (s.d.) for the relevant
variables.
HH = Derived words with high-frequency root and high-frequency suffix
HL = Derived words with high-frequency root and low-frequency suffix
LH = Derived words with low-frequency root and high-frequency suffix
LL = Derived words with low-frequency root and low-frequency suffix
ND = Nonderived words,
Freq: Frequency; Num: Numerosity; Rel: Relatedness
HH
Root Freq.
Family Size
Suffix Freq.
Suffix Num.
Semantic Rel.
Familiarity
Bigram Freq.
Word Length
Root Length
Suffix Length
Word Freq.
Mean
547
12.3
2,119
247
5.41
6.42
10.72
8.2
4.4
3.8
5.3
HL
s.d.
536.5
8.81
1,653
141.2
0.56
0.34
0.44
1.29
1.06
0.66
4.04
Mean
554
11.1
75
21
5.01
6.24
10.74
8.6
4.5
4.2
4.6
LH
s.d.
526.2
4.05
37.26
12.6
0.77
0.6
0.25
1.22
1.23
0.64
4.94
Mean
38
4.6
1,892
227
5.34
6.22
10.58
8.1
4.3
3.8
3.1
LL
s.d.
16.72
1.94
1,479
127.33
0.65
0.46
0.52
1.20
1.22
0.66
2.68
Mean
31
4.1
68
21
5.24
6.15
10.47
8.8
5.0
3.8
3.1
ND
s.d.
22.9
2.11
43.9
12.5
0.82
0.48
0.27
0.88
0.94
0.66
3.53
Mean
9.5
1.8
—
—
—
6.21
10.75
7.9
—
—
0.4
s.d.
7.98
0.97
—
—
—
0.68
0.29
0.83
—
—
3.47
5.1.2. Procedure
The procedure was the same as in Experiment 2. The experimental session
lasted about 30 minutes.
184
Burani and Thornton
5.1.3. Participants
Fifty participants, mostly University students, were paid to participate in
the experiment. All were native speakers of Italian.
5.1.4. Results and discussion
The data of three participants, whose mean reaction times for correct responses or whose error rates were more extreme than 2 s.d. from the mean
of all participants, were excluded from further analysis. Using the remaining forty-seven participants, the mean reaction times and error rates for all
items were obtained. Mean reaction times by items and percentages of
errors for the five experimental sets are shown in Table 5.
Table 5. Experiment 3. Mean reaction times by items in ms and % error. Suffixed
derived words with high-frequency root and high-frequency suffix (HH);
high-frequency root and low-frequency suffix (HL); low-frequency root
and high-frequency suffix (LH); low-frequency root and low-frequency
suffix (LL); nonderived words (ND).
HH
HL
LH
LL
ND
Mean
Reaction
Time
603
605
641
645
640
% Error
5.4
8.6
14.1
17.1
13.6
Results on the five sets were submitted to one-way ANOVAs. Additionally, two-way analyses of variance, with root frequency (high vs. low) and
suffix frequency (high vs. low) as the two factors were performed on the
four derived sets.
Results of one-way ANOVAs showed a significant difference among
experimental categories, on both reaction times (F1(4,184) = 35.77, p
<.0001, MSE= 483.08; F2(4,80) = 4.05, p<.005, MSE= 1,816.13) and errors (F1(4,184) = 21.09, p<.0001, MSE= 1.43; F2(4,80) = 2.84, p<.03,
MSE= 29.35). Post-hoc comparisons based on the Duncan’s test on the
The interplay of root, suffix and whole-word frequency
185
means by items showed that both HH and HL derived words gave rise to
significantly faster reaction times than words in the other three sets (for all
comparisons involving HH or HL words, p<.025).
Additionally, HH and HL derived words did not differ from one another
(p>.1). Analogously, no differences were found among LH, LL and ND
words (always p>.1). A similar pattern was found on errors, with significant differences between HH words on the one hand, and LH, LL, and ND
words, on the other (always p<.05), and between HL and LL words
(p=.05).
The two-way ANOVAs on the four derived sets, with root frequency
(high vs. low) and suffix frequency (high vs. low) as the two factors, confirmed a root effect only, by both participants and items, on both reaction
times and errors (F1 (1,46) = 129.3, p<.0001, MSE= 438.24; F2 (1,64) =
14.59, p<.0001, MSE= 1,740.71 for reaction times; F1 (1,46) = 66.38,
p<.0001, MSE= 1.53; F2 (1,64) = 9.14, p<.004, MSE= 30.66 for errors).
On reaction times, no suffix effect was found (F<1), and no interaction
(F<1). A suffix effect was found on errors, in the analysis by participants
only (F1 (1,46) = 9.83, p<.003, MSE= 1.35; F2 (1,64) = 1.20, p>.1, MSE=
30.7), with words with low-frequency suffixes giving rise to more errors
than words with high-frequency suffixes. No interaction was found on
errors (F<1).
Results of Experiment 3 confirmed morpheme-based processing for HH
words. As expected, these derived words showed faster reaction times and
higher accuracy because of including high-frequency morphological constituents. The outcomes of Experiment 3 also suggested whole-word processing for LL derived words – the latter words, whose constituent morphemes were low-frequency, did not show any advantage with respect to
nonderived words of the same surface frequency.
The results of Experiment 3 were not in accordance with the predictions
made for HL and LH derived words. Differently from Experiment 2, in
which the two sets of derived words which include one high-frequency
constituent did not differ from each other, and showed intermediate reaction times and accuracy with respect to words including two highfrequency constituents on the one hand, and words including two lowfrequency constituents on the other, in Experiment 3 HL and LH words
gave rise to contrasting results. Apparently, the imperfect balance in rated
familiarity among word sets was responsible for part of the effects found in
Experiment 2. A better matching among experimental sets led to a different
pattern of results in Experiment 3. While words with high-frequency root
186
Burani and Thornton
and low-frequency suffix (HL words) were as fast as words with both root
and suffix of high frequency (HH words), words with a high-frequency
suffix but a low-frequency root (LH words) did not differ either from
words in which both constituents were low-frequency (LL words), nor
from words with no morphological constituency, i.e., nonderived (ND)
words.
From these results it could be argued that the major determinant of lexical decision performance to suffixed derived words is the root frequency,
with no role for the frequency of the suffix. In the General discussion a
processing account will be discussed, that reconciles these results on words
with the apparently contrasting results on suffixed pseudowords, including
results of Experiment 1, in which a strong role for suffix frequency was
found.
6. General discussion
Three lexical decision experiments investigated how the frequency of morphemic constituents, namely roots and suffixes, affects the visual processing of low-frequency derived stimuli. In Experiment 1, pseudowords
made up of Italian derivational suffixes of various frequencies and meaningless pseudoroots were contrasted to pseudowords in which the same
pseudoroots were combined with control orthographically legal final sequences. These final sequences were matched to the suffixes for frequency
and for other relevant variables, but were not suffixes themselves. There
were three sets of suffixed/control pseudowords, differing in the frequency
of the final sequences, either high, medium or low. Only pseudowords that
included high-frequency suffixes showed interference, namely longer decision times and higher error rates, with respect to their matched non suffixed controls. Neither pseudowords including medium-frequency suffixes
nor pseudowords with low-frequency suffixes differed from their respective controls. These results are in accordance with previous results by Burani et al. (1997), and extend them to pseudoword contexts in which no
root is present. The results provide further evidence that the activation of
morphemic access units corresponding to suffixes is constrained, in visual
tasks, by the quantifiable characteristics of the suffixes themselves (see
also Laudanna and Burani 1995; Laudanna, Burani and Cermele 1994).
Experiment 2 and 3 explored whether the frequency of the root or the
suffix affected lexical decision to low-frequency suffixed derived Italian
The interplay of root, suffix and whole-word frequency
187
words. Four sets of derived nouns and adjectives were contrasted in Experiment 2. All of the words in the four sets had a low frequency, but differed
with respect to the frequency of their morphemic constituents, either high
or low with orthogonal variation. The results showed that reaction times
and accuracy to derived words were affected by the frequency of both roots
and suffixes. Lexical decisions were faster and more accurate when the
derived words included two high-frequency constituents, they were the
slowest and the least accurate when both constituents had low frequency,
and had intermediate times and error rates when the derived words included only one high-frequency constituent, either the root or the suffix. No
differential effects of root and suffix frequency were found. However,
post-hoc controls showed that the effects of morphemic frequency on lexical decision performance were possibly confounded with effects of wordfamiliarity, which differed among the four sets in a way that paralleled
differences in the frequency of morphological constituents.
Four new sets of low-frequency derived words were tested in Experiment 3. The derived words differed in the frequency of the constituent
roots and suffixes, which were orthogonally varied as in Experiment 2.
However, the derived words were also matched for ratings of familiarity. In
this experiment, the sets of derived words were contrasted with a set of
low-frequency nonderived words, matched to the derived words for all the
relevant variables, including word familiarity. When word familiarity was
controlled, lexical decisions to derived words were found to be a function
of the frequency of the root only, irrespective of suffix frequency. Decision
latencies to the two sets of derived words with high-frequency roots, irrespective of suffix frequency, were faster than to the two sets of derived
words with low-frequency roots. Moreover, with low root frequency items,
there was no effect of suffix frequency, either high or low. Finally, performance to words with low-frequency roots did not differ from performance
to nonderived words, thus suggesting analogous processing for derived
words with low-frequency constituents and nonderived words.
Collectively, these findings reveal effects of suffix as well as root units
in the processing of derived stimuli. They also indicate that results may be
affected by word familiarity. We will discuss first the results on real
words, then we will show how they could be reconciled with results on
pseudoword processing, in which an effect of suffix frequency was found.
Experiment 3 showed that, when low-frequency derived words were
equated for ratings of familiarity, only those that included a high-frequency
root resulted in faster access relative to nonderived words of similar fre-
188
Burani and Thornton
quency/familiarity. Thus access through activation of morphemes is beneficial only for derived words with high-frequency roots. By contrast, suffixed derived words that did not include any high-frequency constituent, or
only included a high-frequency suffix, did not show any processing advantage with respect to derived words of similar low-frequency. Hence,
lexical decision latencies to words with low-frequency roots, irrespective
of suffix frequency, seem to be a function of surface (whole-word) frequency, and are analogous to words with no morphemic constituency. Thus
the main result of Experiment 3 is that access to low-frequency derived
words is not always obtained via morphological parsing. The full-form
access route is also involved, and in some cases it determines response
latency.
How could this pattern of results be interpreted? In the framework of a
parallel dual-route model, whole-word activation would start simultaneously and proceed with analogous time courses for all the five categories of
words considered in Experiment 3 because of their similarly low surface
frequency. However, different outcomes are expected for the different
words, due to the different probability of morphemic access. That words
with high-frequency roots and high-frequency suffixes (HH words) should
result in faster and more accurate performance with respect to the other
words is an expected finding, because the higher frequency of morphemes
with respect to the frequency of the whole-word combination should affect
positively both the speed and accuracy of access through morphemic activation. The result for derived words in which both the root and the suffix
are low-frequency (LL words) is also expected, on the assumption that the
slightly higher frequency of the constituents might not be large enough to
result in advantageous morphemic processing with respect to whole-word
processing.
However, the asymmetrical results between words with high-frequency
root and low-frequency suffix (HL words), and words with low-frequency
root and high-frequency suffix (LH words) call for some refinement of a
model in which whole-word activation and morphemic activation are assumed to occur in parallel. Some suggestion comes from studies that have
investigated how, in silent sentence reading, eye fixations on compounds
are affected by component morphemes. In these studies, it has been shown
that words composed of eight letters or more, like our derived words, typically require more than one eye-fixation. When (at least) two eye-fixations
are involved, the frequency of the first morphemic constituent strongly
influences the duration of the first fixation on the target word (Hyönä and
The interplay of root, suffix and whole-word frequency
189
Pollatsek 1998). The frequency of the second morpheme influences gaze
duration, but its influence is not immediate, and only affects relatively later
processing (Pollatsek, Hyönä and Bertram 2000). Furthermore, second
constituent effects may overlap in time with whole-word effects: The frequency of the whole word influences eye movements at least as early as the
frequency of the second constituent, and can have an effect even before
access of the second constituent (Pollatsek, Hyönä and Bertram 2000). In
the framework suggested by these authors, the identification of morphologically complex words involves parallel processing of both morphological
constituents and whole-word representations. The two morphological constituents each have an effect but differ in the time course. While the probability of whole-word processing would be the same for all the derived
words with similar frequency/familiarity, a head start to access through
morphological segmentation might be available only for words with a highfrequency first constituent (in our case, the root). A high-frequency second
constituent (here, the suffix) would not result in a significant advantage,
with respect to whole-word access.
In a framework in which no different head start is assumed for morphemes occurring in different word positions, not even when they are of
relevant length (Baayen and Schreuder 2000; Baayen, Schreuder and
Sproat 2000), the present results could be interpreted as arising at stages
following segmentation, in which the morphemes are combined and the
result of composition is checked for licensing. The model proposed by
Baayen, Schreuder and coworkers distinguishes, in the route for morphological processing, a number of successive processing stages. According to
Baayen and Schreuder (1999) (see also Baayen and Schreuder 2000;
Baayen, Schreuder and Sproat 2000), access representations are activated
over time by the sensory input through the stages of perceptual identification and segmentation. Access representations are assigned resting activation levels that are proportional to their frequency of occurrence, with
high-frequency morphemes reaching a pre-set activation threshold more
8
quickly than low-frequency morphemes. Once an access representation for
a root or an affix reaches the threshold activation level, it is copied to a
short-term memory buffer. Once the representations provide full, nonoverlapping spannings of the input, they are passed on to the following
processing stages of licensing (the checking for subcategorisation compatibility), composition (the compositional computation of the meaning of the
whole from its parts) and semantic activation of semantically related representations in long-term memory.
190
Burani and Thornton
In this model, derived words with different morphological constituents
should result in different processing times. The access representations of
words whose constituents are both high-frequency (HH words) would be
passed on to the processing stages of licensing, composition and semantic
activation more quickly than the other words. For words in which only one
constituent is high-frequency (HL and LH words), the access representation corresponding to the high-frequency constituent is quickly copied to
the short-term memory buffer. However, the full segmentation of the input
would be delayed by the slow activation of the access representation corresponding to the low-frequency morpheme.
At the segmentation stage, at least one frequent constituent should be
easily identifiable for effective segmentation to occur, in that identification
of one highly activated morpheme should leave the remainder as a prime
candidate for a second constituent. When no morphemic access representation can be easily segmented, like in LL words in which both constituents
are low-frequency, additional time consuming procedures have to be called
upon. Thus, there might be some extra segmentation cost involved for
morphemic access to LL words, which would give an advantage to wholeword access.
At the segmentation stage, HH words would be favoured by morphological processing with respect to both HL words and LH words. However, at
the composition and licensing stages, a main role for the root morpheme
could be assumed. At these stages, for both HH and HL suffixed words, a
highly activated root is available. In both cases, the root representation
activates the set of derivational affixes that are compatible with it. The
amplitude of this set is similar for both HH and HL words, which have the
same mean derivational family size (see Table 4). Thus little evidence from
the orthographic input is needed in both cases, in order to activate the correct suffix among the set of pre-activated ones: Independently of its frequency, the presented suffix should be activated, combined, and the combination checked for licensing, among the same (small) number of possible
suffixes. In the case of LH words, no highly activated root is available
from the start. The representation that is highly activated at the composition and licensing stages is the one corresponding to the suffix. At these
stages, the representation corresponding to a high-numerosity suffix is
compatible with a large number of representations corresponding to roots
(as many as 240 root types on average, if calculated in the corpus; about
650 root types if calculated in the dictionary). Hence, the orthographic
evidence required from the input should be large, in order to be correctly
The interplay of root, suffix and whole-word frequency
191
activated, composed and finally licensed. But this is not the case when the
stimulus includes a scarcely activated low-frequency root, as in the case of
LH derived words. The process of composition and licensing would be
long for LH words, thus allowing for processing through whole-word to
win the race. In summary, for both LH and LL words, for which activation
via morphemes is so drastically slowed down in different processing components, whole-word processing would be faster in providing access to the
lexicon, not differently from nonderived (ND) words, for which wholeword processing is the only possible route.
The results on suffixed pseudowords that were obtained in Experiment
1 can now be reconciled with results on suffixed words. In Experiment 1,
pseudowords made up of a pseudoroot and a high-frequency/numerosity
suffix resulted in longer reaction times and lower accuracy with respect to
matched pseudowords in which the same pseudoroots were combined with
pseudosuffixes. Pseudowords made up of a pseudoroot and a highfrequency suffix are in a way not that different from LH words, which include a low-frequency root and a high-frequency suffix. Therefore, analogously to suffixed LH words, pseudowords of this sort are subject to morphemic segmentation because of the very high frequency/numerosity of
one constituent, namely the suffix. After reaching the threshold activation
level and being copied to the short-term memory buffer, the access representation corresponding to the suffix cannot be passed on to the subsequent
stages of composition and licensing because no full spanning of the input is
provided. However, the very same attempt at morphemic segmentation
causes delay or interference in the process of nonword decision, thus resulting in slower decision times and higher error rates. By contrast, neither
delay nor interference would occur in the case of pseudowords made up of
a pseudoroot and a medium/low-frequency suffix, because here no morphemic constituent would be frequent enough to trigger morphemic segmentation (at least not within the deadline for lexical decision).
The results obtained by Burani et al. (1997) can find a similar account.
The pseudowords investigated by Burani et al. (1997) were made up of a
real root of medium/low frequency and a suffix that could be either highor low-frequency. Pseudowords with medium-frequency root and highfrequency suffixes activate two access representations that are both likely
to be passed on to the composition and licensing stages. Thus they were
subject to (morpho-)lexical interference in nonword decision. However,
interference was not found in lexical decision to either pseudowords made
up of a (medium-frequency) root and a low-frequency suffix, or to
192
Burani and Thornton
pseudowords made up of a (medium-frequency) root and a pseudosuffix. In
the latter cases no morphemic constituent was frequent enough to trigger
morphemic segmentation that would leave the remainder as a prime candidate for a second constituent.
In summary, the results reported in the present study on both suffixed
derived words and suffixed pseudowords, together with previous results on
morphological pseudowords, point to the conclusion that the assumption of
a higher probability of morphemic parsing for low-frequency derived
words (Burani and Laudanna 1992; Frauenfelder and Schreuder 1992)
needs to be further specified. Not all low-frequency derived words might
be similarly subject to be accessed via morphological parsing. In formulating predictions for access through morphemic decomposition, the complex
balancing between root and affix properties, including quantitative properties like frequency and numerosity, are to be taken into account.
The complex balancing of root and suffix quantitative properties should
be relevant for expecting costs of morphological parsing, as well as benefits. In the studies by Bertram, Laine and Karvinen (1999) and by Bertram,
Schreuder and Baayen (2000), conducted on Finnish morphologically
complex words, it has been proposed that some derived words (those with
unproductive or homonymous suffixes) are accessed on the basis of storage, thus are as quick as monomorphemic Finnish words. This prediction
finds confirmation in the lexical decision to our derived words with lowfrequency root and low-frequency suffix (LL words), which did not differ
from nonderived (ND) words. However, this same prediction would be too
simplistic in the case of derived words with a low-frequency/numerosity
suffix and a high-frequency root (HL words) on the one hand, and for derived words with a high-frequency/numerosity suffix but a low-frequency
root (LH words) on the other hand. Apparently, neither Bertram, Laine and
Karvinen (1999), nor Bertram, Schreuder and Baayen (2000) specifically
investigated the differences between these cases. The present results on
Italian suffixed derived words provide some evidence for the processing of
derived words of this sort.
The interplay of root, suffix and whole-word frequency
Appendices
Appendix A
Experiment 1
Suffixed pseudowords and their controls with mean RT and % Error.
HF = Pseudowords with high-frequency final sequence
HF
Suffixed
Control
ITEM
RT
Prucezza
723
matirezza
757
accogezza
%E
ITEM
RT
%E
13.6
prucondo
638
0
9.1
matirondo
699
13.6
748
9.1
accogondo
759
18.2
sillerezza
734
13.6
sillerondo
709
4.5
feldismo
768
22.7
feldanca
624
0
rovollismo
714
4.5
rovollanca
683
0
rachenismo
718
13.6
rachenanca
704
13.6
cabilismo
771
22.7
cabilanca
806
9.1
cempenista
788
22.7
cempenosto
693
0
livonista
754
18.2
livonosto
662
4.5
ascobista
744
9.1
ascobosto
711
0
pirgista
655
4.5
pirgosto
718
9.1
MEAN
739
13.6
700
6.1
193
194
Burani and Thornton
Experiment 1
Suffixed pseudowords and their controls with mean RT and % Error.
MF = Pseudowords with medium-frequency final sequence
MF
Suffixed
Control
ITEM
RT
lengardo
710
elbirardo
725
fozzardo
mevinardo
%E
ITEM
RT
%E
9.1
lengerta
660
0
0
elbirerta
721
4.5
681
0
fozzerta
747
9.1
674
9.1
mevinerta
737
22.7
varbesco
757
0
varbanna
649
13.6
orcittesco
742
0
orcittanna
683
4.5
sicoresco
728
9.1
sicoranna
748
4.5
dolmibesco
664
0
dolmibanna
707
9.1
stemigno
719
13.6
stemusso
702
0
trudigno
686
0
trudusso
676
9.1
seltigno
622
4.5
seltusso
684
4.5
701
4.1
MEAN
701
7.4
The interplay of root, suffix and whole-word frequency
Experiment 1
Suffixed pseudowords and their controls with mean RT and % Error.
LF = Pseudowords with low-frequency final sequence
LF
Suffixed
Control
ITEM
RT
gurnense
713
adricense
685
tirfense
%E
ITEM
RT
%E
4.5
gurnombe
653
4.5
0
adricombe
634
4.5
633
0
tirfombe
686
0
enovense
614
0
enovombe
660
9.1
siramigia
735
13.6
siramegio
687
0
amittigia
718
13.6
amittegio
678
4.5
furnigia
662
0
furnegio
684
9.1
davelligia
691
0
davellegio
765
4.5
parcinoide
739
4.5
parcinaudo
647
0
balmoide
688
4.5
balmaudo
701
4.5
taripoide
642
9.1
taripaudo
672
4.5
cettoide
643
4.5
cettaudo
676
4.5
MEAN
680
4.6
MEAN
679
4.2
195
196
Burani and Thornton
Appendix B
Experiment 2
Experimental items with mean RT and % Error
HH = Words with high-frequency root and high-frequency suffix
HL = Words with high-frequency root and low-frequency suffix
HH
WORD
HL
Root
Suf-
Word
Freq.
fixFreq
Freq.
RT
%E
WORD
Root
Suffix
Word
Freq.
Freq.
Freq.
RT
%E
.
bassezza
414
1,557
1
665
0
umanoide
324
12
1
683
giornalismo
307
639
9
588
0
pazzoide
175
12
1
631
2.9
centrismo
501
639
2
652
5.7
ferrigno
369
55
2
739
14.3
acquario
17.2
1,120
1,177
3
540
0
testardo
698
60
4
548
0
nudista
253
984
1
613
0
donnesco
1,556
90
2
658
11.4
macchinista
305
984
8
600
0
guerresco
630
90
1
623
8.6
amatore
603
2,074
3
563
8.6
levatoio
927
102
5
606
0
tiratore
524
2,074
1
601
2.9
spogliatoio
108
102
1
590
0
goloso
117
1,335
2
539
2.9
violaceo
126
13
5
677
14.3
dentale
250
888
1
622
5.7
pacifico
475
53
10
547
2.9
ottimale
125
888
1
573
0
frutteto
335
46
9
622
0
credibile
1,485
262
5
603
2.9
roseto
363
46
1
567
0
501
1,859
3.1
597
2.5
MEAN
507
57
3.5
624
5.9
MEAN
The interplay of root, suffix and whole-word frequency
Appendix C
Experiment 3
Experimental items with mean Rt and % Error.
HH = Words with high-frequency root and high-frequency suffix
HL = Words with high-frequency root and low-frequency suffix
HH
WORD
HL
Root
Suffix
Word
Freq.
Freq.
Freq.
RT
%E WORD
Root
Suffix Word
Freq.
Freq.
RT
%E
Freq.
liberismo
877
639
1 661
14.9 donnesco
1,556
90
2 651
27.7
carnoso
329
1,335
4 619
0 campestre
646
59
5 604
4.3
godibile
187
956
3 620
19.1 guerresco
630
90
1 603
2.1
scenario
244
1,177
13 559
4.3 muraglia
510
184
17 580
6.4
numerale
475
4,942
1 642
6.4 sanguigno
540
55
10 575
0
consumismo
160
639
2 628
0 pacifico
475
53
10 549
0
temibile
223
956
6 600
6.4 spogliatoio
108
102
1 585
0
pensatore
2,204
2,074
1 613
0 parlatoio
2,075
102
2 687
12.8
ordinanza
773
1,485
8 568
0 bambinesco
693
90
1 610
6.4
erboso
236
1,335
6 605
4.3 onorifico
215
53
1 664
17.0
piccolezza
937
1,557
5 600
0 pazzoide
173
12
1 620
21.3
2.1
serale
1,266
4,942
11 604
12.8 romanzesco
109
90
1 606
velocista
150
984
3 575
0 testardo
698
60
4 571
0
bruttezza
228
1,557
3 605
4.3 alpestre
187
59
5 651
34.0
bestiale
233
4,942
8 573
0 canneto
grossezza
391
1,557
2 610
navale
394
4,942
13 573
MEAN
547
2,119
5.29 603
204
46
13 597
8.5
17 roseto
363
46
1 576
4.3
2.1 poliziesco
238
90
3 549
0
5.4 MEAN
554
75.3
4.6 605
8.6
197
198
Burani and Thornton
Experiment 3
Experimental items with mean Rt and % Error.
LH = Words with low-frequency root and high-frequency suffix
LL = Words with low-frequency root and low-frequency suffix
LH
WORD
LL
Root
Suffix Word
Freq.
Freq.
RT
%E WORD
Freq.
Root
Suffix Word
Freq.
Freq.
RT
%E
Freq.
limatura
22
1,482
2 696
31.9 luridume
10
23
2 679
42.5
astrale
68
4,942
3 616
10.6 zingaresco
33
90
2 636
2.1
flautista
26
984
3 677
23.4 bugiardo
77
60
13 535
2.1
maestoso
25
1,335
10 611
66
90
1 730
14.9
igienista
30
984
1 635
14.9 beffardo
49
60
5 608
12.8
gaiezza
33
1,557
2 660
14.9 viscidume
8
23
2 743
40.4
rozzezza
33
1,557
2 653
14.9 orinatoio
10
102
1 702
31.9
rugoso
21
1,335
3 610
2.1 agrumeto
22
46
1 660
23.4
intuibile
32
956
3 692
40.4 cupidigia
20
7
6 645
14.9
rudezza
33
1,557
2 607
2.1 brodaglia
44
184
1 700
46.8
doganale
22
4,942
1 660
4.3 gigantesco
72
90
10 576
0
schedario
31
1,177
8 620
6.4 lerciume
11
23
2 690
36.2
punibile
69
956
1 600
14.9 fiabesco
10
90
1 564
2.1
lagnanza
45
1,485
1 641
27.7 serbatoio
29
102
1 576
2.1
lanoso
69
1,335
2 659
19.1 burlesco
12
90
1 608
6.4
fenomenale
54
4,942
1 651
8.5 sudiciume
22
23
2 629
0
pessimismo
35
639
7 602
0 prolifico
28
53
1 679
12.8
38.1
1,892
3.1 641
31
68
3.1 645
17.1
MEAN
4.3 serpentesco
14.1 MEAN
The interplay of root, suffix and whole-word frequency
199
Experiment 3
Experimental items with mean Rt and % Error.
ND = Nonderived words
ND
WORD
avezzo
Root
Word
Freq.
Freq.
RT
%E
18
6
670
12.8
caparbio
9
2
684
14.9
damigiana
6
2
692
31.9
sbilenco
8
4
702
31.9
cospicuo
12
4
651
19.1
giaguaro
2
1
661
12.8
aragosta
8
2
602
8.5
scirocco
12
8
561
2.1
farabutto
8
4
631
14.9
inerme
9
7
682
25.5
ascesso
1
1
649
6.4
collasso
3
3
559
0
scarlatto
35
15
668
17.0
laringe
3
2
668
25.5
calunnia
14
7
605
2.1
rimorchio
9
4
630
4.3
trapezio
4
3
570
2.1
MEAN
9.5
4.4
640
13.6
Notes
*
We are indebted to Emanuela Rellini for running Experiment 2, and to Alberto Spuntarelli for his precious contribution to the various phases of Experiment 3. We also thank Harald Baayen, Rob Schreuder, Alessandro Laudanna,
Daniela Traficante, Lisa S. Arduino, Francesca M. Dovetto and Sergio Carlomagno for valuable discussions. Finally, we thank the referees, Laurie
Feldman, Jen Hay and Harald Baayen, whose revisions and comments helped
to improve the paper.
200
1.
2.
3.
4.
5.
6.
7.
Burani and Thornton
An exception is Bradley’s (1979) study, in which words involving different
suffixes with different effects on the orthographic/phonological characteristics
of the stem were contrasted (see also Tsapkini, Kehayia and Jarema 1998;
1999; Vannest and Boland 1999).
For instance, the three Italian suffixes -ista, -ezza and -oide could be compared. While the first two have high frequency and high numerosity in a corpus (frequency: 984 and 1,557/1,500,000, respectively; numerosity: 145 and
187, respectively), they differ in productivity, if we take as indicator of
productivity the number of words containing these suffixes found in five Italian dictionaries of neologisms. While -ista appears in as many as 417 neologisms, -ezza appears in only 3 neologisms. These data can be further compared
with those concerning the suffix -oide, which has a very low frequency and
low numerosity in the corpus (frequency: 12/1,500,000; numerosity: 10), but
appears in 11 neologisms, i.e., in four times as many as the neologisms in
which the very frequent suffix -ezza appears.
If the higher probability of storage (or whole-word access) vs. computation (or
morphemic access) is determined by high whole-word frequency, also inflected high-frequency words should be likely to be accessed as whole-forms. Recent evidence for storage of high-frequency regularly inflected English words
comes from Alegre and Gordon (1999a). Related evidence can be found in
Baayen, Dijkstra and Schreuder (1997), and in Baayen, Burani and Schreuder
(1997), for Dutch and Italian regularly inflected words, respectively.
Although nonderived words did not include any derivational affix, they included, like the derived words and like almost any Italian word, an inflectional
suffix for number and gender. For this reason we name them "nonderived", not
"monomorphemic". We selected nonderived words with very low cumulative
root frequency, in a way that the cumulative root frequency was as close as
possible to surface frequency.
Any contribution of the frequency of the inflection to morphemic access would
be the same for all the five word sets.
The total number of selected items was not as large as we had aimed at. It
turned out that in trying to match items for all the variables, we had exploited
all the possible words in our corpus. Specifically, derived words in the sets
with low-frequency suffixes (HL and LL), that were already very few in the
corpus, had to be further reduced in number in order to be matched with the
other words. Many LL words were excluded because they had lower familiarity with respect to words in the other sets. Additionally, the inclusion of nonderived words made even more difficult to match words across sets, because
of the tendency of nonderived words to be shorter than derived words (see
Campos 1993).
Interestingly, matching derived words for rated familiarity left the robust root
effect unchanged, while suffix frequency effects were completely washed out.
The interplay of root, suffix and whole-word frequency
8.
201
This suggests that familiarity rating is a task that is much more sensitive to
properties of the suffix than to properties of the root. Recent evidence from
our laboratory (Burani, Bimonte and Barca, in preparation) has shown that, on
a larger sample of low-frequency suffixed derived words (N=122), familiarity
ratings had a significant correlation with (log) suffix frequency (r = .43,
p<.0001), while they had no correlation with (log) root frequency (r = -.06).
Further research is required in order to investigate why should this be case.
This "segmentation-through-recognition" approach should avoid the objections raised by Andrews and Davis (1999) to the interactive activation accounts of morphological decomposition, by assuming that "The activation
weights of access representations are increased only for constituents that are
aligned with the left or right edge of the word, or that are aligned with access
representations that have reached threshold and that themselves are edgealigned, either with the word edge itself or with another edge-aligned constituent in the short-term-memory buffer." (Baayen and Schreuder 2000: 5).
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