LANGUAGE AND COGNITIVE PROCESSES, 2003, 18 (3), 335–362
Morphological structure in the lexical representation
of prefixed words:
Evidence from speech errors
Alissa Melinger
Max Planck Institute for Psycholinguistics, Nijmegen, The Netherlands
The present study aims to determine whether semantic relatedness plays a
role in the production of speech errors involving derivational morphemes. A
word order competition technique was used to induce morpheme and
syllable exchange errors. Semantic relatedness was manipulated by contrasting error rates for prefixed words derived from free stems to those derived
from bound roots. Significantly more morpheme errors were elicited in the
two prefixed conditions compared with the control condition, replicating
prior findings in French. Crucially, the two prefixed conditions elicited equal
numbers of morpheme errors and there was no correlation between semantic
relatedness and error rates. Taken together, the results strongly support a
model of speech production in which derivational morphemes are
represented at the form level and are not influenced by the degree of
semantic relatedness within a morphological family.
INTRODUCTION
One goal of morphological theory is to characterise the knowledge that
speakers possess about the morphological structure and relatedness of
words in their language. The ability to understand and create new words
composed of familiar parts, clearly an important component of linguistic
Requests for reprints should be addressed to Alissa Melinger, Max Planck Institute for
Psycholinguistics, Postbus 310, 6500 AH, Nijmegen, The Netherlands, Email: [email protected].
This research was supported (in part) by research grant 1 RO1 MH60133-01 from the
National Institute of Mental Health, National Institutes of Health awarded to Gail Mauner
and Jean-Pierre Koenig. I would like to thank Jean-Pierre Koenig, Karin Michelson, Gail
Mauner, Paul Luce, Wendy Baldwin, Eve Ng, Anne Vestergaard, Breton Bienvenue, Asifa
Majid, Karin Humphreys and two anonymous reviewers for their helpful comments and
support.
c 2003 Psychology Press Ltd
http://www.tandf.co.uk/journals/pp/01690965.html
DOI: 10.1080/01690960244000072
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MELINGER
competence, draws on the knowledge of a language’s morphology. While
morphological theories aim to characterise what speakers know about the
relationships between words, models of speech processing continue to
debate whether morphological information plays any role in producing or
recognising words.
One debate within the processing literature is whether a morphological
level of representation is needed; many researchers argue that form and
meaning levels, which are independently required, can accommodate all
the apparent morphological effects without postulating an additional
explicit morphological level of representation. Most morphologically
related words have both formal overlap, sharing some phonological form,
and meaning overlap, sharing some meaning components. It is well known
that words with only form similarity (Tanenhaus, Flanigan, & Seidenberg,
1980) or only meaning similarity (Neely, 1976; Swinney, Onifer, Prather, &
Hirshkowitz, 1979) do produce facilitative effects independent of
morphological relatedness. Therefore, it is possible that purported
morphological effects emerge as the result of the combination of the
independent form and meaning effects and not as the result of a
morphological relationship, per se. Indeed, several researchers have
argued that experimental effects which are attributed to morphological
processes can also be explained by differences in degrees of semantic
similarity (Plaut & Gonnerman, 2000) or phonological overlap (Rueckl,
Mikolinski, Raveh, Miner, & Mars, 1997). While the debate swings back
and forth in the speech recognition literature, within the speech production
literature, arguments for an independent morphological level of processing
have only recently been addressed (Pillon, 1998; Roelofs, 1996; Roelofs &
Baayen, 2002; Zwitserlood, Bölte, & Dohmes, 2000). The aim of the
current study is to provide additional support for an explicit level of
morphological representation as well as to examine the role of semantic
relatedness to morphological processing in speech production using an
experimental elicitation of speech errors.
Speech errors have been used for decades to form inferences about the
nature of linguistic representations (Fromkin, 1971). The distribution of
various types of errors was a primary source of evidence for the formation
of speech production models (Dell, 1986; Garrett, 1980, 1982). For
example, error data were central to the now widely accepted proposal for a
separation between a level of semantic/syntactic representation and a level
of form representation. Misordering errors such as in (1a) and (1b) occur at
the stage of production when the phonological form of the word is being
retrieved and assembled. These errors also provide external evidence for
linguistic notions such as phonological features, segments, syllables, etc.
Errors involving the mis-selection of a semantically related word, such as
in (1c)–(1e), occur at an earlier level of processing when the appropriate
MORPHOLOGICAL STRUCTURE OF PREFIXED WORD
337
lemma is selected to express a particular concept. Errors of this type argue
for a semantic organisation of the mental lexicon.
(1) a. skip one stage Õ stip one skage
b. Pity the new teacher Õ mity
the due teacher
c. Blond hair Õ blond eyes
d. My dissertation is too short
. . . long
e. She’s a real [swKp] chick
Segmental error respecting
syllabic position
Featural error
Semantic error
Semantic word substitutions
Semantic blend between
swinging and hip
Speech errors can also involve the misordering or mis-selection of
morphemic units, most frequently inflectional morphemes. Inflectional
morphemes can be mis-selected, as in (2a), or they can be stranded when
their stems are misordered, as in (2b).
(2) a. he had to have it Õ he haved to have it
b. a floor full of holes Õ a hole full of
floors
Derivational morpheme errors have also been reported, however they
are much less frequent than inflectional errors (Cutler, 1980; Fromkin,
1973; Garrett, 1980; MacKay, 1980; Stemberger, 1985). Despite the
prevalence of morphological errors in the literature, the interpretation of
morphological slips, especially derivational errors, remains unclear.
Derivational morpheme errors, such as those in (3), are difficult to
interpret as necessarily involving morphological units. For example, in (3a)
the error could be an example of a phonological word blend, perhaps
between grouping and arrangement. Likewise, in (3b) the error could be
the result of a phonological word blend between the target inquisitive and
a competitor exquisite. Under this interpretation, the errors are no
different from other word blends between two non-morphologically
complex words, such as in (4). In (3c), it is possible that the speaker
incorrectly applied a word formation rule when the existing word was
temporarily unavailable, creating the error derival rather than retrieving
derivation. While this error does inform us that words can be productively
produced on-line, it tells us nothing about the representation of derivation
or of the role of morphemes as units in speech production.
(3) a.
b.
c.
Intended
grouping
inquisitive
derivation
Produced
groupment
exquisitive
derival
338
(4) a.
b.
MELINGER
Intended
public/popular
person/people
Produced
poplic
perple
One way to differentiate between a morphological explanation and a
phonological word blend explanation for errors that appear to involve
morphemes is to investigate the distribution of naturally occurring errors.
For example, there is evidence to suggest that inflectional suffixes pattern
differently in errors than other non-morphemic word endings, which
supports a morphological interpretation of inflectional errors (Bybee &
Slobin, 1982; MacKay, 1976; Stemberger & MacWhinney, 1986). Unfortunately, the same sorts of distributional and probabilistic evidence for
derivational affixes is sparse.
Another way to discriminate between the two possible explanations is to
experimentally induce errors. For example, MacKay (1978) induced errors
by eliciting derived forms of simple words from speakers. Speakers often
produced an error which involved the over-generalisation of a morphological rule, such as in (5). However, critics have argued that this elicitation
method is artificial and does not reflect the same processes involved in
naturally occurring errors since these errors do not involve the retrieval
and blending of existing words. As a result, MacKay’s findings may not
bear on the lexical representations of existing complex words but
potentially only on the production of new words via rule application.
(5) collide Õ collidement, not collision
The existence of naturally occurring derivational errors such as in (3)
have been used as evidence that roots and derivational affixes are stored
and accessed separately (Fromkin, 1973:236). However, the alternative
interpretation which denies the active involvement of derivational
morphemes in errors is still possible; strong conclusions cannot be drawn
from the data that come from naturally occurring errors. To provide
stronger support for a morphemic analysis of derivational errors, Pillon
(1998) demonstrated that derivational units participate in errors more
frequently than non-morphological units. Pillon conducted a Word Order
Competition (WOC; Baars & Motley, 1976) study to elicit derivational
morpheme errors. Originally, the WOC technique had been used to induce
spoonerisms (e.g., darn bore becomes barn door; Baars & Motley, 1976),
syllable exchanges (e.g., horrible miracle becomes horracle mirible; Baars,
Matteson, & Cruickshank, 1985) and word exchanges between phrases
(e.g., He fixed his trousers and dropped his watch. Italicised words are
exchanged; Baars & MacKay, 1978). Pillon used the WOC task to elicit
morphological and phonological errors to determine whether morphemic
MORPHOLOGICAL STRUCTURE OF PREFIXED WORD
339
units were more likely to participate in speech errors than non-morphemic
units.
Pillon (1998) presented word pairs consisting of a French noun þ
adjective. Her presentation word pairs were either both suffixed, such as in
(6), or both monomorphemic words with phonologically matched
pseudosuffixes, as in (7).
(6) a.
a.
b.
(7) a.
b.
c.
troupeau traı̂nard
penseur hautain
crochet mural
cadeau bâtard
auteur soudain
chalet rival
‘flock straggler’
‘thinker haughty’
‘hook wall’
‘gift hybrid’
‘author unexpected’
‘chalet rival’
These word pairs were presented to participants who were instructed to
pronounce the words either in the order in which they appeared or in the
reverse order. The ordering uncertainty gives rise to a high proportion of
speech errors (Baars & Motley, 1976). In the case of morphological-type
errors, ordering uncertainty should produce exchange errors such as in (8)–
(9). The expected errors in (8) produce one real word, an intruding word, and
one nonsence word; Pillon also used examples that produced two nonsense
words, such as in (9). In each of these errors, the (pseudo)roots are exchanged
and the (pseudo)affixes are stranded. Pillon hypothesised that ‘‘derived word
pairs should give rise, more often than control ones, to such stranding errors, if
lexical retrieval actually entails the selection of intermediate morphemelevel units between words and phonemes’’ (1998:472).
Presented pair
(8) a. troupeau traı̂nard
‘‘flock straggler’’1
b. cadeau bâtard
‘‘gift hybrid’’
(9) a. chaton froussard
‘‘kitten cowardly’’
b. flacon standard
‘‘bottle standard’’
Expected error
traı̂neau *troupard
‘‘sleigh’’
bâteau *cadard
‘‘boat’’
*frousson *chatard
*standon *flacard
Pillon reported significantly more stranding errors for morphologically
complex words than for monomorphemic control words. She concluded
that ‘‘morpheme units like roots and derivational suffixes are handled at
some stage of the real-time speech production process’’ (1998:487) and
that derivational structure needs to be represented in the speech system.
1
Literally ‘‘slow coach’’.
340
MELINGER
Pillon’s study, together with the naturally occurring derivational errors,
provides compelling evidence for the inclusion of derivational morphological structure in the lexicon. However, one alternative explanation for
Pillon’s results is that semantic relatedness mediated the production of
morphological errors. It is well known that word substitutions are more
common when target and error are semantically and phonologically similar
compared with just being phonologically similar (e.g., I thought Westerns
were where people ride horses instead of cars Õ . . . instead of cows;
Fromkin, 1973; Dell & Reich, 1977, 1980). Given the very nature of
morphemes, words which share a stem or an affix will have more semantic
similarity than two words sharing a syllable. The presentation and
intruding words in Pillon’s suffixed condition had more semantic overlap
than in the pseudosuffixed condition. Therefore, it is possible that the
elicited ‘morpheme’ errors were actually phonological blends whose
frequency of occurrence, or probability of occurring, was enhanced by
the additional semantic relatedness between the presentation and
intruding words.
The possibility that Pillon’s exchange errors could have been influenced
by semantic factors is supported by the fact that the biased pairs, those
designed to produce errors consisting of one real word, such as in (8)
above, produced significantly more errors than the unbiased pairs,
designed to produce errors consisting of no real words, as in (9) above.
Errors that produce real words are more common than errors which do
not; thus, the difference in exchange error rates between her biased and
unbiased pairs is not surprising (cf. Baars, Motley, & Mackay, 1975).
However, given that a semantic explanation for the errors is strongest
when at least one intruding word is competing for selection, this difference
adds to the uncertainty about the mechanism and representation underlying these errors.
Pillon maintains that semantic relationships between presentation and
intruding words do not influence the observed morpheme exchange errors
because many of her words were, in fact, not semantically related.
However, her measure of semantic relatedness was intuitive, not objective.
Intuitive judgements of semantic relatedness, especially from non-naive
speakers, are problematic and often differ greatly from objective
judgements obtained with ratings studies. In fact, pairs that Pillon
intuitively classified as having ‘‘at best only a loose semantic and
morphological relationship’’ were classified by several native French
informants as transparently related (J.-P. Koenig, personal communication, May 18, 2002). Thus, the role of semantic relations in influencing
morpheme exchange errors remains open.
To determine whether morpheme errors occur independent of a
semantic relationship, a Word Order Competition (WOC) study was
MORPHOLOGICAL STRUCTURE OF PREFIXED WORD
341
conducted comparing morpheme exchange errors produced for English
prefixed words with different degrees of semantic relatedness. Specifically,
errors were elicited to English prefixed words derived from free stems
(e.g., reload ~ unload), which have a relatively high degree of semantic
relatedness within a morphological family, and from words derived from
bound roots (e.g., induce ~ reduce), which have a relatively low degree of
semantic relatedness within a morphological family. The number of
exchange errors produced for these two types of complex word, as well as
the number of phonological and lexical errors, were compared with the
number produced in a phonological control condition. Only semantic
relatedness, as a function of the type of base the word is derived from, was
systematically manipulated. If semantic relatedness plays no role in the
production of morpheme exchanges, then both prefixed words derived
from free stems and bound roots should produce more exchange errors
than the control condition and they should not differ from each other. In
contrast, if semantic similarity is a component which underlies the
production of exchange errors, then only the free stem words should
produce more exchange errors than the control condition. This result
would argue against the retrieval of explicitly represented morphological
constituents during speech production.
EXPERIMENT
In the WOC technique, pairs of words are presented to participants for a
naming response. Exchange errors involving word components are elicited
by randomly changing the response instructions such that participants are
unaware when reading the words which order they will have to be named.
The ordering uncertainty induces high error rates.
The number of exchange errors in three conditions of presentation
words are compared: free stem words, bound root words, and phonological
control words. Because there is a strong lexical bias in error corpora, i.e.,
errors that result in actual words are more frequent than errors that
produce nonsense strings, only materials that produce real word errors
were included (Baars et al., 1975). Unfortunately, the constraint against
nonsense errors restricts the possible construction of morphologically
simple words with matching pseudoprefixes. Therefore, unlike Pillon’s
monomorphemic control group which was phonetically matched to the
complex group, as shown above in examples (6)–(7), the current control
condition consists either of morphologically simple words (without
pseudoprefixes), as in (10), or suffixed words, as in (11), with exchangeable
syllables. The disadvantage of this design is that the items in the control set
are not phonologically matched to particular complex word sets. The
advantage, however, is that the entire set of stimuli can contribute to an
342
MELINGER
effect since they all respect the strong lexical bias for errors. Crucially, for
the suffixed simple words, the exchangeable syllables are not co-extensive
with morphemes.
(10) a.
b.
(11) a.
b.
Presented pair
socket pallid
rattle morbid
scanty pedal
certify forgery
Expected error
solid packet
mortal rabid
scandal petty
surgery fortify
To evaluate the influence of semantic similarity on experimentally
induced morphological exchange errors, the number of morphological
exchange errors produced by prefixed words derived from free stems was
compared with the number produced by prefixed words derived from
bound roots. As a baseline measure of syllable exchanges, the number of
syllable-level errors produced in the control condition was also compared.
Only errors involving the relevant subportions of words, namely
morphemes and syllables, should be influenced by the manipulation of
word type; all other errors should be produced at equal rates across
conditions.
METHOD
Participants. Forty-two native English speaking undergraduates from
the University at Buffalo, State University of New York received partial
course credit for their participation.
Materials. Thirty-three experimental word pairs were constructed for
presentation in a Word Order Competition (WOC) study.2 Complex word
pairs consisted of two prefixed words, derived either from free stems or
bound roots. Control word pairs consisted of two non-prefixed words. The
words in each presentation pair were semantically, morphologically, and
phonologically unrelated to each other. An example set of presentation
word pairs along with the expected intruding errors are presented in (12).
To increase the rate of morpheme and syllable exchanges, all word pairs
were designed to produce real word errors. All intruding word errors in the
prefixed conditions were morphologically complex.
(12)
Free
Bound
Control
Presentation pairs
enfold react
reject induce
rattle morbid
Possible error
enact refold
reduce inject
rabid mortal
2
Originally, 13 item sets were constructed for each condition. However, two sets in the
control condition were found to not meet the necessary criteria for inclusion in the study.
Therefore, those item sets, as well as two randomly selected item sets from each of the other
conditions, were excluded from all analyses.
MORPHOLOGICAL STRUCTURE OF PREFIXED WORD
343
In the two prefixed conditions, the word components targeted for the
exchange error correspond to English morphemes, namely, prefixes and
bases. A variety of prefixes were used. The free stem condition included
seven different prefixes and nine different prefix combinations (only the
pair dis - re was repeated). The bound root condition included 12 prefixes
(14 different prefix allomorphs) and 11 prefix combinations. Between the
two prefixed conditions, three common prefixes were used.3 For all words
in the two complex conditions, the splicing point, i.e., the point at which
the words can divide and exchange parts to produce real words, occurred
at the morpheme boundary. The morpheme boundary coincided with a
syllable boundary in 10 of the 22 word pairs.
All of the control condition words conformed to the following criteria:
(1) the two exchangeable word fragments which remain after the word has
been divided do not constitute real words in English nor do they constitute
roots or affixes that are semantically related to the meaning of the whole
word; (2) the two word fragments correspond to the syllables of the
presentation and intruding words, not just possible English syllables.
The control condition consisted mostly of monomorphemic words;
seven of the 22 words in this condition contained a derivational suffix
and one contained an inflectional suffix. Furthermore, one pair
included two complex words; the remaining 10 word pairs consisted
either of two simple words or of one simple and one suffixed word.
Importantly, when a control word was suffixed, the splicing point
always occurred at the syllable boundary, not at the morpheme
boundary; the exchangeable syllables were not coextensive with
morphemes. Additionally, the exchange of morphemes between two
words in the control condition did not result in a legitimate word (e.g.,
certify forgery Õ *certery *forgify) while an exchange of syllables did
(e.g., certify forgery Õ surgery fortify). In an attempt to control for
syllable frequency, the words in the control condition often consisted
of high frequency word endings. Of the monomorphemic words in the
control condition, 14 ended with (pseudo)suffixes and the remaining
eight were composed of high frequency endings such as -ow, -le, or -el.
In 6 of the 11 word pairs, the potential errors were phonologically but
not orthographically matched (e.g., fashion setter Õ fatter session and
certify forgery Õ surgery fortify). Evidence from prior studies using this
3
Most prefixes could not be used in both conditions because they are restricted in their
distribution. Certain affixes, which are sometimes termed ‘‘level 2’’ affixes like un- and mis-,
only occur with free stems while ‘‘level 1’’ affixes, like ad- and per-, only occur with bound
roots.
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MELINGER
task suggests that conflicting orthography should not affect error rates
as long as the phonological representations are consistent (Baars &
Motley, 1976).
Of the 66 words that comprised the 33 pairs across conditions, 54 were
bisyllabic, and 12 were trisyllabic. Baars et al. (1985) showed that syllable
exchanges are more likely to occur between words that have the same
number of syllables and stress patterns. Each word within a pair had an
equal number of syllables and the same stress pattern.
Each word pair in all conditions met the following criteria: (1)
exchanging morphemes/syllables results in the production of actual
English words; and (2) no target or expected error was produced by
exchanging only a single phoneme (i.e., the prefixes pre and re were never
paired since a prefix exchange and a segment exchange would be
indistinguishable).
In addition to the 33 experimental word pairs presented, 72 distractor
word pairs were interspersed with the experimental items. Distractors
consisted of random word combinations as well as rhyming words (e.g.,
heel kneel), alliterative words (e.g., greedy green), semantically associated
words (e.g., yellow white), and words standing in unusual syntagmatic
relationships (e.g., man hairy). All items were distributed within a single
list, resulting in a fully within-subjects design.
Conditions were matched on two measures of word frequency: the raw
(and log) frequency summed across a presentation word pair and the
difference between the presentation pair’s summed frequency and the
intruding (or error) word pair’s summed frequency. A one-way analysis of
variance revealed no difference in word frequencies across conditions, F 5
1, but a marginal difference when comparing the difference in frequency
between presentation and intruding word pairs, F(2, 30) ¼ 3.2, MSe ¼
1102, p 5 .06. This marginal difference was due to higher intruder
frequencies in the bound root (61.7) and control conditions (37.1)
compared with the free stem condition (17.5). Because word frequency
influences word-form retrieval times (Jescheniak & Levelt, 1994),
intruding words were designed to have higher word frequencies than the
presentation words to induce higher rates of exchange errors in all three
conditions. Since intruders in the bound root and control conditions have
higher frequencies, it is possible that the number of errors in these
conditions will be enhanced. This possibility will be addressed in the
discussion.
The overall phonological similarity between the two words forming a
presentation pair was balanced between conditions. The phonological
similarity was measured grossly, in terms of shared segments, not shared
features. A segment was counted as shared if it was common to both words
of a presentation pair and held the same syllabic position in both words.
MORPHOLOGICAL STRUCTURE OF PREFIXED WORD
345
For example, the words insist conclude have one segment overlapping,
namely the [n] in the coda of each initial syllable. In contrast, the words
concede profess have no segmental overlap despite the fact that both words
contain an [s]. Since the [s] in concede is in a syllable onset and the [s] in
profess is in a syllable coda, they are not coded as overlapping. Given this
coding system, the average number of overlapping segments within a
condition was calculated. A one-way analysis of variance revealed no
significant difference between conditions, F 5 1.
It was impossible to fully match string length across conditions. There
was a significant difference in the graphemic string length between
conditions, F(2, 30) ¼ 9.43, MSe ¼ 3.3, p 5 .01. This difference was
graded between the three conditions, the free stem condition being the
longest with 7.7 graphemes per word, followed by the bound root
condition with 6.65 graphemes per word, and the control condition with 6
graphemes per word. Additionally, while the two words in a pair always
had an equal number of syllables and the same stress pattern, there was
some variation in the number of syllables between item sets. The free
stem condition had an average of 2.5 syllables per word, the bound root
condition had an average of 2 syllables per word, and the control
condition had an average of 2.1 syllables per word. This difference,
carried by the length of the free stem words, was also significant, F(2, 30)
¼ 5.25, MSe ¼ 0.12, p 5 .05.
Free stem and bound root words are used in this study as a method of
comparing error rates for prefixed words with differing degrees of semantic
relatedness. However, while bound root words generally do not have
strong semantic consistency across their morphological families, they may
still have more semantic overlap than the control words. For example,
while the relatives receive and deceive are semantically unrelated, the
relatives increase and decrease are highly related. Likewise, despite having
a clearer semantic composition, free stem words can also have opaque
relations to morphological relatives. For example, recharge and discharge
are not as clearly related in meaning as reappear and disappear. Therefore,
a semantic rating study was conducted to ensure that the conditions
differed in their degree of semantic relatedness.
Sixty-six word pairs were constructed for a semantic relatedness rating
study. Each individual presentation word for the WOC study was paired
with its predicted intruder word. For words from the prefixed conditions,
the intruder word was composed of the shared stem or root and the prefix
from the other word in the relevant presentation pair. For the control
condition, the intruder was a rhyming word with the first syllable taken
from the other word from the relevant presentation pair. Examples are
given in (13). In addition to the 66 experimental word pairs, 180 distractor
word pairs were presented.
346
(13)
MELINGER
Condition
Free
Presentation pairs
Recharge Displace
Bound
Insist Conclude
Control
Miller Parcel
Rating study pairs
Recharge Discharge
Displace Replace
Insist Consist
Include Conclude
Miller Parlor
Missile Parcel4
Rating
3.2
3.7
2.2
4.2
2.2
2.0
Average
3.45
3.2
2.1
Word pairs were centred on the computer monitor with a 7-point
Likert scale at the bottom of the screen. Participants were asked to rate
the degree to which the words were related in meaning.5 Lower ratings
signify that participants did not identify a clear meaning relationship
between the words while a high rating indicates that they did identify a
clear meaning relationship. Semantic similarity ratings were calculated
for each rating study pair and compared across conditions. Additionally,
a second measure of semantic similarity was calculated by averaging
together the two individual ratings to obtain a rating for each
presentation pair.
The rating study revealed that the conditions do differ in the degree to
which presentation words and intruding words are semantically related.
The free stem condition had the highest average rating, 4.15, followed by
the bound root condition, 3.5. The control condition had the lowest
average rating, 2.4. This difference was significant across the three
conditions by subjects, Friedman: w2(2, N ¼ 10) ¼ 14.6, p 5 .01, and
items, Kruskal–Wallis: w2(2, N ¼ 66) ¼ 32.59, p 5 .01. Paired comparisons
reveal that the gradient difference was significant between all three
conditions. The free stem words received higher relatedness ratings than
the bound root words, Wilcoxon Sign: z ¼ 2.5, p 5 .05; Mann–Whitney U:
z ¼ 2.5, p 5 .05, for subjects and items, respectively, and in turn the bound
root words received higher relatedness ratings than the control words,
Wilcoxon Sign: z ¼ 2.7, p 5 .01; Mann-Whitney U: z ¼ 3.7, p 5 .01, for
subjects and items, respectively.
Procedure. The procedure used was an adaptation of the Word Order
Competition (WOC) technique of Baars and Motley (1976). Each trial
began with the presentation of a word pair centred on the computer screen
in capital letters. Each pair of words remained on the screen for 900 ms.
After a 200 ms delay, a response cue was presented. There were two
4
In the mid-western and New York dialects spoken by the participants in this study, the
word missile has only two syllables, ['mI.s@l], and rhymes with parcel ['par.s@l].
5
In the instructions, participants were informed that words could be related in a number
of different ways such as synonymy (SOFA–COUCH), autonymy (HOT–COLD), or
associatively (TEACHER–STUDENT). They were instructed to decide for themselves
whether two words were related, or similar, in meaning and to rate the degree of relatedness.
They were also encouraged to use the entire range of the scale, not simply the two endpoints.
MORPHOLOGICAL STRUCTURE OF PREFIXED WORD
347
different response cues; REPEAT and REVERSE. When the response
cue was REPEAT, participants were instructed to name the words in their
presented order. When the response cue was REVERSE, participants
were instructed to name them in the reverse order. All experimental
targets were followed by the REVERSE response cue. Removing the word
pairs from the monitor before the presentation of the response cue
prevented participants from simply reading the words off the screen. The
response cue remained on the screen for 1 second after onset of response.
Following this interval, the next pair of presentation words was displayed.
Participants sat before a computer monitor and a microphone. There
was also a tape recorder in the room. Trials were recorded and responses
were transcribed by two raters, one of whom was blind to the hypotheses
of the study. The inter-rater reliability was 97%. Errors were then
classified into types.
RESULTS AND DISCUSSION
Classification of errors
The most common errors were skipped trials, incomplete responses, failure
to reverse the word order, mispronunciations (various phonological
errors), external intrusions, inflectional errors, and derivational exchange
errors. All but the exchange errors should be unaffected by the current
manipulation. Following the classification schema of Pillon (1998), errors
were classified either as contextual or non-contextual. Contextual errors
involve misorderings of segments present within the trial. Non-contextual
errors involve the omission or insertion of segments not present in the trial.
External intrusions, incomplete responses, and inflectional errors are
classified as non-contextual errors. Contextual errors were further
classified as within-word and between-word errors. Within-word errors
involve a misordering of segments within a word while between-word
errors involved a misordering of segments between words. For example,
rattle morbid Õ battle morbid is an example of a between-word contextual
error because features from the second word are anticipated in the first
word. In contrast, misnamed unused Õ misnamed unsued is a within-word
contextual error since segments from within the second word are
misordered; the first word plays no role in the error. Finally, betweenword contextual errors were further divided into critical and (sub)segmental errors. Critical errors involve the portions of the words that are
investigated in the current study, namely morphemes or syllables.
(Sub)segmental errors involve between-word exchanges of phonological
segments, features, etc. Thus, phonological exchanges involving single
features or segments, such as in rattle morbid Õ battle morbid, are classified
as (sub)segmental between-word contextual errors while an exchange of
348
MELINGER
Figure 1. Hierarchy of error type classification.
prefixes, such as in reject induce Õ reject reduce, is classified as a critical
between-word contextual error. Critical errors not consisting of two full
words were further classified as incomplete errors. The hierarchy of error
types is depicted in Figure 1. Examples of the different error types with
their classifications are presented in Table 1.
Distribution of errors
The manipulation of word type is predicted to only affect the production of
critical between-word contextual errors. The distribution of non-critical
errors, i.e., all errors that do not involve the critical components of the
words under investigation, is predicted to be unaffected by the current
manipulation. There are three types of critical errors: prefix/initial syllable
spreading, where both words are produced with the same word onset, such
as in (14), stem/final syllable spreading, where both words share the same
word ending, such as in (15), and total exchanges, where both word onsets
and offsets are swapped, such as in (16). All spreading errors can occur by
perseveration or anticipation of the morpheme or syllable. In order for a
speech error to be included in the analysis of critical errors, the production
of the word pair must be complete. Partial errors and incomplete
responses, even those that clearly include a morphological error (reject
induce Õ reject re . . . or reject induce Õ reduce . . .), were not included in
the analysis.
Correct response
(14) reject induce
(15) reject induce
(16) reject induce
Error
reject reduce
reject inject
reduce inject
Error type
Prefix spreading
Stem spreading
Total exchange
349
reject induce
dispose propel
reject induce
rattle morbid
remit advise
misnamed unused
dispose propel
unordered discounted
insist conclude
perturb dissuade
misprint prejudge
reject induce
reject induce
reject induce
Failure to reverse word order
Failure to complete the pair
Inflectional errors
Derivational errors
External intrusions
Phonological errors
Target utterance
Error type
induce reject
dispose
reduce
battle morbid
remit admise
misnamed unsued
dispose [próp@l]
unordered discouraged
interest conclude
perturbed dissuade
misprint prejudice
reject reduce
reject inject
reduce inject
Produced error
TABLE 1
Examples of errors organised by error type
Non-contextual
Non-contextual
Contextual, between, critical, incomplete
contextual, between words, (sub)segmental
contextual, between words, (sub)segmental
contextual, within words
Non-contextual
Non-contextual
Non-contextual
Non-contextual
Non-contextual
contextual, between words, critical, complete
contextual, between words, critical, complete
contextual, between words, critical, complete
Classification
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MELINGER
Each of the 42 participants contributed a maximum of 33 responses,
creating 1386 opportunities for error, 462 per condition. Because the task
was fast-paced, participants were occasionally unable to make a response.
In total, 54 trials (less than 4% of all experimental trials) were skipped by
participants, and 79 trials (5.7%) were incomplete (without an error). Most
incomplete responses consisted of only one of the two response words.
There were an additional 32 partial completions which included a
morphological error, 23 from the free condition, 7 from the bound
condition and 2 from the simple condition. In total, 12% of the trials were
lost due to incomplete responses.
In total, 43% of the responses had some type of error. The overall
distribution of errors by condition is presented in Table 2. The distribution
of errors by complete critical error type is presented in Table 3. As can be
seen, all three types of morpheme and syllable exchanges were observed in
all three conditions.
For the analysis, one factor (WORD TYPE) with three levels was
included. Two dependent variables, the number of elicited complete
critical errors and the number of all non-critical errors, were measured.
Included in the set of non-critical errors are (sub)segmental between-word
errors, within-word contextual errors, and non-contextual errors. The
mean number of complete critical and non-critical errors were calculated
for each participant and for each word pair in a condition. Across
conditions, participants made an average of 2.2 critical errors and 11.2 noncritical errors. Each participant produced an average of 1.0 critical error
and 3.9 non-critical errors in the free stem condition, 0.98 critical errors
and 3.6 non-critical errors in the bound root condition, and 0.2 critical and
3.6 non-critical errors in the control condition. The number of complete
critical errors produced for each word pair is given in the Appendix.
When examining the distribution of non-critical errors, no main effect of
word type was observed by subjects, Friedman: w2(2, N ¼ 42) ¼ 2.25, p 5
.32, or items, Kruskal–Wallis: w2(2, N ¼ 11) ¼ 0.27, p 5 .87. When
TABLE 2
Error distribution by condition
Error type
Free
Bound
Simple
Total
Non-contextual errors
Contextual within-word errors
Contextual between-word errors
(Sub)segmental errors
All Non-critical errors
Critical errors
Complete
Incomplete
150
6
132
3
122
1
404
10
11
167
18
153
29
152
58
472
43
23
41
7
9
2
93
32
MORPHOLOGICAL STRUCTURE OF PREFIXED WORD
351
TABLE 3
Total number of complete critical speech errors per condition divided into error types
Error type
Prefix spreads
recharge displace Õ recharge replace
Stem spreads
disorder recover Õ discover recover
Total exchanges
recharge displace Õ discharge replace
Total errors
Free stem
Bound root
Control
12
4
2
12
15
5
19
22
2
43
41
9
examining the distribution of critical errors, a difference between the two
prefixed conditions and the control condition was found. The main effect
of word type for critical errors was reliable across subjects, Friedman: w2(2,
N ¼ 42) ¼ 20.302, p 5 .01, and items, Kruskal–Wallis: w2(2, N ¼ 11) ¼
9.936, p 5 .01. The distribution of critical errors compared with noncritical errors across the three experimental conditions was also
significantly different, w2(2) ¼ 18.99, p 5 .001. Thus, we see that
participants produced more critical errors when naming prefixed words
than control words but an equal number of non-critical errors across
conditions, as predicted.
The crucial question under investigation is whether the bound root
condition, which consisted of words with a relatively low rate of semantic
relatedness, patterned with the free stem condition or the control
condition. Pairwise comparisons reveal no difference in the distribution
of critical errors between the free stem and bound root conditions by
subjects, Wilcoxon Sign: z ¼ 0.043, p ¼ .96, and items, Mann–Whitney U: z
¼ 0.562, p ¼ .61.6 In contrast, significantly more critical errors were
produced in the free stem condition, by subjects, Wilcoxon Sign: z ¼ 4.1,
p 5 .01, and items, Mann–Whitney U: z ¼ 3.08, p 5 .01, compared with
the control condition. Likewise, more critical errors were produced in the
bound root condition, by subjects, Wilcoxon Sign: z ¼ 3.42, p 5 .01, and
items, Mann–Whitney U: z ¼ 2.27, p 5 .05, compared with the control
condition.
Since the two prefixed conditions differed significantly in semantic
relatedness but not in the number of critical errors produced, it is unlikely
that semantics played a large role in inducing the errors. However, there
was a great deal of variation between items both in the elicited ratings and
6
Furthermore, there were no significant differences in the type of critical errors produced
between the free stem and bound root conditions, Mann–Whitney U: zs 5 1; comparisons
within stem spreading errors, prefix spreading errors and total exchanges revealed no
significant differences between the two complex word types.
352
MELINGER
in the number of errors produced. As a result, it is possible that items with
higher semantic ratings produced the most errors. If true, then there
should be a significant correlation between the semantic ratings of word
pairs and the number of critical errors produced. There are two ways in
which this possibility can be investigated. First, the number of critical
errors produced by a presentation pair can be correlated with the averaged
similarity rating for that pair. Second, rather than averaging the similarity
ratings for the two related word pairs together, the ratings for each
individual pair of related words can be used for the correlation.
Correlating error rates with the semantic ratings from individual related
word pairs gives the greatest sensitivity to differences in semantic
relatedness ratings. However, it only allows inspection of a subset of the
error data, namely the stem exchange errors. Since prefix spreading errors
and total exchanges involve the stems/roots from both words, this measure
of semantic similarity is inappropriate for them. But, averaging across the
individual rating pairs to produce a mean rating for each presentation pair
allows one to test whether semantic ratings correlate with the production
of all three types of critical errors. Since the interesting comparison is
between the two prefixed conditions, only the two prefixed conditions were
included in the correlation. The scatter plot in Figure 2 shows the
relationship between error rate and averaged semantic rating.
Figure 2 shows the relationship between the average semantic rating a
presentation word pair received in the rating study and the number of
critical errors produced in the WOC task for the bound root and free stem
words. As can be seen, there is no correlation between semantic rating and
the number of morphological errors produced, Spearman’s Correlation:
r ¼ .263, p 5 .237. The lack of a significant correlation suggests that error
rates were not influenced by the semantic relationship between a
presentation word and its intruding word but rather were due to structural
characteristics of the presentation words.
The correlation with the averaged similarity rating for each presentation
pair allows all critical error types, stem spreads, prefix spreads and total
exchanges, to be investigated. However, it loses sensitivity to the specific
degree of semantic relatedness of a single word pair, especially when the
two rating word pairs that compose a presentation pair receive very
different rating scores. To illustrate, consider the presentation pair insist
conclude. The two rating pairs for this item received quite different
similarity ratings; insist consist received a rating of 2.2 while include
conclude was rated much higher, 4.2. This difference in the semantic
relatedness within the presentation pair predicts that more errors should
be produced involving the root {-clude} than involving the root {-sist}.
Since the correlation with averaged semantic ratings cannot address this
prediction, a second correlation of semantic relatedness with only the stem
MORPHOLOGICAL STRUCTURE OF PREFIXED WORD
353
Figure 2. Distribution of critical errors and semantic ratings for the bound root and free stem
word pairs.
spreading errors was conducted. Again, only the bound root and free stem
words were considered. Stem spreading errors were identified as involving
one of the two available stems and the number of errors was correlated
with the semantic rating for that stem pair. The scatter plot in Figure 3
shows the relationship between stem error rates and semantic ratings.
Again, no correlation was found between number of stem spreading
errors and the semantic relatedness of the individual rating pairs,
Spearman’s Correlation: r ¼ .241, p 5 .115. As Figure 3 shows, most
words produced between zero and two stem spread errors, irrespective of
their semantic rating. There are, however, two clear outliers identified.
Two word pairs, realign misalign and implode explode, received both high
semantic ratings and a disproportionate number of stem spreading errors
(their presentation pair counterparts, misassign reassign and expose impose
produced stem spreading errors within the normal range). Thus, these two
words seem to belie the absence of a correlation between semantic
relatedness and error production. However, these two word pairs have
another interesting feature; the presentation pairs misassign realign and
expose implode have more phoneme overlap than average, three and two
segments, respectively. Although this factor was matched across condi-
354
MELINGER
Figure 3. Distribution of stem spreading errors and semantic ratings for the bound root and
free stem word pairs.
tions, there was still some variation between items. These two examples
suggest that phoneme overlap may also be a factor that partly predicts the
occurrence of critical errors. To ensure that overlap is not a strong
predictor of critical error production, a correlation between number of
errors produced in all three conditions and segmental overlap was also
conducted. This correlation produced a very weak, marginally significant
correlation, Spearman’s Correlation: r ¼ .317, p 5 .073. Thus, it seems that
phoneme overlap is very weakly correlated with critical error production.
While it cannot explain the differences found in critical error production
between the two complex conditions and the control condition, it may
provide a partial explanation for why certain item sets produced more
errors than others.
These results clearly indicate that morphological elements are more
likely to be exchanged or be substituted in word production than other
linguistic units such as syllables. They also suggest that both free stem and
bound root words are represented in a similar manner in the mental
lexicon; specifically, they are represented either as morphologically
decomposed, with each morpheme represented independently, or as whole
word forms which include internal morphological structure. If complex
MORPHOLOGICAL STRUCTURE OF PREFIXED WORD
355
words are represented as internally structured whole word forms, then this
suggests that morpheme boundaries are more salient or accessible to the
language production system than syllable boundaries.
As predicted, more critical errors were produced in the free stem
condition than in the control condition. Likewise, more critical errors were
produced in the bound root condition than in the control condition. An
equal number of critical errors were produced in the free stem and bound
root conditions and there was no correlation between semantic relatedness
ratings and the production of critical errors. The difference in error rates
for prefixed words compared with control words lends support to models of
the mental lexicon that include morphological structure in the representations of derivationally complex words. Since the intended utterances for
each error in this study are known, as they were prescribed by the task,
alternative analyses which classify morpheme errors together with other
word blends between simplex words are ruled out. Also, since the word
pairs in the control conditions produced significantly fewer errors, the
errors cannot be explained by referring to other levels of linguistic
representation such as the syllable. The difference in the number of
observed morphological errors in complex words compared with syllable
errors in the control words, found in an experimental setting, suggests that
the paucity of derivational errors in naturally occurring data may be due to
the rarity of clauses containing a derivational affix and two stems, both of
which can be concatenated with the affix to produce an actual word.
The differences in critical error rates can also not be easily attributed to
differences in the intruder word frequencies or string length. For all
material differences reported, the free stem condition stood out as
different from the other two conditions; the words in this condition were
longer and the intruders were less frequent than in either the bound root or
control conditions. If differences in critical error rates were attributable to
these differences, one would have expected the bound root words to
pattern with the control words rather than the free stem words. This is not
the observed pattern in error rates. Furthermore, a difference in string
length between conditions should have affected the number of non-critical
errors as well as critical errors but no difference in non-critical errors was
observed. Thus, it is unlikely that these differences had a significant
influence on the production of errors in this study.
Another difference between the two complex conditions and the control
condition in the present study is that the presentation words and intruders
consistently are from the same part of speech in the two complex
conditions but not in the control condition. In naturally occurring errors,
words tend to exchange with words of the same part of speech. However,
since naturally occurring errors are always produced in context, it is
unclear if a grammatical class constraint operates during lexical access or
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MELINGER
at the stage where words are associated to syntactic positions. If it applies
during lexical access, this could be another possible explanation for the
present difference in critical error rates. It does not appear, however, that
part of speech plays a large role in predicting critical errors in the control
condition. Several of the presentation word pairs do not have intruders
that are from different grammatical classes yet they still do not produce
any critical errors. Similarly, several word pairs that do have intruders from
a different grammatical class do produce errors. Thus, while this possible
explanation cannot be ruled out completely, the data do not conform
neatly to the predictions that arise.
The current findings for prefixed words replicate Pillon’s (1998) findings
for French suffixed words. One striking difference, however, is that English
speakers produced a much higher rate of non-contextual errors compared
with the French speakers. Pillon reported that participants rarely failed to
reverse the order of words for experimental trials and also rarely produced
incomplete responses. In contrast, 30% of responses from English
participants included some sort of non-contextual error. Since the rates
of non-contextual errors were constant across conditions, one cannot
attribute the high rates to the manipulation of word type. Rather, it is more
likely due to the differences in the orthographic characteristics of English
compared with French. French has a comparatively transparent mapping
from orthography to phonology; thus reading times may be faster and less
error prone. In contrast, the mapping from orthography to phonology in
English is notoriously complex and arbitrary; thus reading times are longer
and more error prone. Since the presentation time used in this study was
the same as the presentation time used in Pillon’s study, it is possible that
some participants were simply unable to fully prepare their response in the
time allowed.
GENERAL DISCUSSION
The results from the present study demonstrate that morphological errors
are more frequent than phonological or syllable level errors in laboratoryinduced settings. This replicates Pillon’s (1998) results using prefixed words
derived both from free stems and bound roots and it provides further
support for a morphological interpretation of naturally occurring
morpheme errors. When ordering uncertainty was introduced to the
naming task, higher levels of morpheme ordering errors were observed
than syllable ordering errors. In agreement with Pillon, this finding
suggests that morphemes and morpheme boundaries make up part of a
word’s form specification and that these words are treated as complex
by the production system in the course of phonetic and/or phonological
spell-out.
MORPHOLOGICAL STRUCTURE OF PREFIXED WORD
357
More interestingly, these results show that prefixed words derived from
free stems and bound roots are equally likely to produce a morpheme
exchange error. This finding emerged despite the differing degrees of
semantic relatedness in the two prefixed conditions and the differing
degrees of semantic relatedness within the morphological families. This
equivalency in error frequency suggests that the lexical representations of
free stem and bound root words are not qualitatively different. The lack of
a significant correlation between presentation pairs’ semantic relatedness
ratings and error frequency suggests that errors are due to morpheme misordering and not to the inappropriate selection of an intruder.
Taken together, these results support the inclusion of morpheme
boundaries in the lexical representation of complex words. This finding
has several implications for theories of morphology and models of speech
production.
Theories of morphology: How are words
represented?
Morphological theories differ with respect to whether morpheme
boundaries are explicitly included in the representations of complex
words. Current trends eschew defining the lexicon as the repository of
morphemes, preferring to view the lexicon as consisting only of stems or
words. Bound morphemes such as affixes have no explicit representation in
most current models of the lexicon but rather are expressed by word
formation generalisations in a morphological component where knowledge
of morphology is expressed. While this is a popular way of conceiving of
morphology, there is a great deal of variation between theories in how
word formation rules (WFR) are related to the lexical items they are
generalising over. In one of the early proposals for WFR use, Aronoff
(1976) states that his WFR serve to analyse existing words into their
component parts. Thus, in his model, a word’s lexical representation can
include morphological structure whether it was created by a WFR or
simply analysed by it.
Another early proposal for extracting morphology out of the lexicon
came from Jackendoff (1975). Jackendoff proposed that morphological
relations are expressed by Redundancy Rules (RR). RR are not processes
that create words but rather statements that express relationships between
words. As a result, Jackendoff’s (1975) model does not acknowledge that
words have internal structure. Each word is represented as a single
indivisible unit in the lexicon; RR express relations amongst words, but no
structure is imposed on words. More recently, Anderson (1992) and
Bochner (1993) have extended Jackendoff’s view of an unstructured lexical
representation of complex words to include both inflectional and
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MELINGER
derivational morphology using WFR or RR, respectively (but see
Carstairs-McCarthy (1992) for several arguments against morpheme-less
theories of morphology).
The obvious implication of unstructured lexical representations is that
they do not predict the type of morpheme errors observed in the current
study. The present data clearly suggest that morphemes are treated as units
by the speech production system. They can only be treated as component
units if lexical representations include information about the morphological make-up of words. Thus, these results argue strongly for the inclusion
of morphological structure within the representations of complex words. If
we adhere to the view that the lexicon consists of words, not morphemes,
these results are most compatible with a model which conceives of WFR as
an active part of the lexicon, functioning both to produce new words and to
analyse existing words into their constituent parts, and not simply
generalisations over an unaltered lexicon.
Speech production
The mechanism underlying the observed exchange errors was outlined
quite explicitly in Pillon’s (1998) general discussion. Specifically, she
suggests that when participants view a presentation pair, the words are in
the opposite order of how they eventually will have to be named. At this
early stage of preparing the response, the morphemes of the first word
should have higher levels of activation than the morphemes of the second
word. When the response cue informs participants to reverse the order of
the words, the activation levels of the words may not adjust quickly enough
to avoid misorderings. Thus, morphemes are anticipated, perseverated, or
fully exchanged. The present results are best accounted for by models of
speech production which include an explicit level of representation for
morphemes (Dell, 1986; Levelt, 1989). Production models which do not
include an explicit level of morphological representation are in no better
position to explain the data than morphological theories which do not
include morphological structure in the lexical representations of complex
words.
The observation that morphological errors are independent of semantic
relatedness supports a clear separation between the levels of semantic and
morphophonological processing rather than an interaction between them.
Discrete speech production models with a clear division between these
levels of processing (Levelt, 1989; Levelt, Roelofs, & Meyer, 1999) are
better positioned to explain this pattern than models which allow
interactions between the levels (Caramazza, 1997; Dell, 1986). Furthermore, the insensitivity of the error mechanism to semantics is also
consistent with the separation hypothesis from morphological theory (cf.
MORPHOLOGICAL STRUCTURE OF PREFIXED WORD
359
Beard, 1988). The separation hypothesis divides the form of an affix from
its function, instantiating them via separate rules.
Further evidence both for the inclusion of an explicit level of
morphological processing and for the insensitivity of that level of
processing to semantic transparency comes from recent reaction time
studies in speech production. Specifically, Roelofs & Baayen (2002)
conducted a reaction time study using the implicit-priming paradigm to
investigate the role of semantics to the production of morphologically
complex words. They constructed sets of three words with the same word
onset. They varied whether all three words were complex and semantically
transparent, or whether two complex and semantically transparent words
were combined with one phonologically matched simple word or a
phonologically matched morphologically complex word that was semantically opaque, such as in (17).
(17) a. input insight inflow
b. input insight insect
c. input insight invoice
They found that semantically opaque words patterned with the semantically transparent words while the morphologically simple words did not.
Thus, they interpret their results as additional evidence for a structure of
the language production system that strictly separates semantic information from morphophonological information (Levelt et al., 1999).
Why don’t we get naturally occurring morpheme
errors?
Given the frequency of morpheme exchanges observed in this study, as
well as Pillon’s (1998) study, the question remains as to why derivational
errors are so rare in naturally occurring data. There are several possible
explanations. First, there is a strong lexical bias in speech production.
Errors resulting in non-words are much less frequent than errors resulting
in actual words (as the biased vs. unbiased contrast in Pillon’s study
demonstrated). The speech production monitoring system (Levelt, 1989)
may catch non-lexical errors more easily than it catches lexical errors.
Most syllable and morpheme exchanges result in illegal combinations. As a
result, many possible morpheme errors are filtered out in the course of
speech production before they are ever uttered.
A second possible explanation is that many errors are uncorrected in
natural speech. Given the semantic relationship between words which
share a free stem (or in many cases even a bound root), the error may not
be clearly noticeable. For example, if a speaker says ‘‘I need to react
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MELINGER
quickly’’ when the intended utterance was ‘‘I need to act quickly’’, the
error may go uncorrected and unnoticed. This possibility exists for many
prefix þ stem combinations, especially since syntactic violations, which
clearly signal an error, do not result from errors involving English prefixes
since they do not change the target word’s part of speech. This is crucially
different from suffix exchanges, such as ‘‘I arrived at the hotel’’ Õ ‘‘I
arrival at the hotel’’, in which the error is clearly noticeable. Thus, the
frequency of morpheme errors in naturally occurring data may, in fact, be
somewhat underestimated, especially for prefixed words.
A third possibility returns to the original issue of interpretablity. Since
many morphological errors can alternatively be interpreted as phonological or semantic errors, many observed errors may be recorded but not
classified as morpheme errors. This would also lead to an underestimation
of morpheme errors in naturally occurring data.
In summary, the current results clearly demonstrate that morpheme
errors do occur more frequently than phonological errors involving
syllables, as was previously shown by Pillon (1998). More importantly,
the data show that the observed errors are purely morphological and not
semantic. Bound root and free stem words produce the same number of
errors suggesting that their lexical representations are not qualitatively
different. These results are best accounted for by models of morphology
that explicitly include morphological structure in the lexical representation
of complex words and models of speech production which explicitly
include a level of morphological processing that is insensitive to semantic
factors.
Manuscript received July 2002
Revised manuscript received November 2002
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APPENDIX
Free stem words
Recharge Displace
Misnamed Unused
Refold Enact
Unordered Discounted
Misassign Realign
Untitled Subconscious
Reappear Disunite
Misprint Prejudge
Enclose Distrust
Reload Unwind
Disorder Recover
a
No. of
errors
Bound root
words
No. of
errors
5
4
5
1
6
0
4
5
2
3
8
Insist Conclude
Detain Observe
Concede Profess
Infer Transduce
Expose Implode
Perturb Dissuade
Decrease Inflate
Induce Reject
Erect Corrupt
Dispose Propel
Remit Advise
1
1
0
6
13
2
5
2
4
0
7
Control words
Miller Parcel
Mugger Baffleda
Mellow Furnace
Socket Pallid
Rattle Morbid
Loyal Tower
Scanty Pedal
Defile Probate
Certify Forgery
Setter Fashion
Briar Tidal
Number of
errors
0
0
0
0
0
3
1
1
1
0
3
The intruding word bagger is an American term that refers to a person at a grocery store
who places your purchased items into a plastic or paper bag.