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      <title-group>
        <article-title>Effects of processing complexity in perception and production. The case of English comparative alternation</article-title>
      </title-group>
      <contrib-group>
        <contrib contrib-type="author">
          <string-name>Gero Kunter English Language</string-name>
          <email>gero.kunter@uni-duesseldorf.de</email>
          <xref ref-type="aff" rid="aff0">0</xref>
          <xref ref-type="aff" rid="aff1">1</xref>
        </contrib>
        <contrib contrib-type="author">
          <string-name>Linguistics</string-name>
          <xref ref-type="aff" rid="aff0">0</xref>
          <xref ref-type="aff" rid="aff1">1</xref>
        </contrib>
        <aff id="aff0">
          <label>0</label>
          <institution>Copyright c by the paper's authors. Copying permitted for private and academic purposes. In Vito Pirrelli, Claudia Marzi, Marcello Ferro (eds.): Word Structure and Word Usage. Proceedings of the NetWordS Final Conference</institution>
          ,
          <addr-line>Pisa</addr-line>
        </aff>
        <aff id="aff1">
          <label>1</label>
          <institution>Heinrich-Heine-Universita ̈t D u ̈sseldorf</institution>
        </aff>
      </contrib-group>
      <fpage>32</fpage>
      <lpage>36</lpage>
      <abstract>
        <p>This paper discusses the effect of processing complexity on the English comparative alternation. The reported experiments show a processing advantage of the synthetic comparative in perception, but a preference of the analytic comparative in sentence production if the base adjective is cognitively complex. These results imply that perceptual complexity and complexity in production have diverging effects on the English comparative alternation. More generally, the paper calls for a fine-grained look at the role of processing complexity in areas of morphosyntactic variation.</p>
      </abstract>
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    <sec id="sec-1">
      <title>1 Introduction</title>
      <p>
        Most English comparatives are formed using
either a synthetic form (e.g. easier) or an analytic
form (e.g. more important). While most
adjectives clearly prefer either the synthetic or the
analytic comparative, there is a considerable
number of adjectives which frequently take both forms,
e.g. more friendly vs. friendlier. The decision
for either form is influenced by several
phonological, morphological, syntactic and semantic factors.
For example, the probability of analytic
comparatives increases with the number of morphemes in
the adjective base. It is also higher if the
comparative is in predicative than in attributive
position, and it decreases with an increasing
comparative/positive ratio
        <xref ref-type="bibr" rid="ref12 ref6 ref9">(see Szmrecsanyi 2005, Hilpert
2008 and Mondorf 2009 for detailed discussions)</xref>
        .
      </p>
      <p>Mondorf (2009) argues that these factors are all
part of a more general, audience-oriented
compensatory mechanism called more-support: if the
cognitive complexity of the adjectival base or its
environment increases, speakers prefer the
analytic comparatives, because they have a processing
advantage over the corresponding synthetic form.
For instance, an adjective that is morphologically
complex is assumed to be also cognitively more
complex than a simplex adjectives, and in order to
compensate for this increased cognitive
complexity, speakers may prefer the analytic comparative
over the synthetic alternative.</p>
      <p>Yet, there is only little psycholinguistic research
that investigated this assumed processing
advantage of analytic forms. A notable exception is
Boyd (2007, ch. 2) who conducted a self-paced
reading experiment to investigate processing
differences between synthetic and analytic
comparatives. Indeed, he reports shorter reaction times for
the sentences containing analytic comparatives,
but due to the experimental design, this evidence
is only indirect and allows for alternative
interpretations. As yet, then, there is only limited
empirical evidence for the assumption that analytic
comparatives are easier to process than synthetic
comparatives. In addition, as pointed out by Mondorf
(2014, 201), it is still an unresolved issue whether
more-support is a response to increased processing
loads in production or in perception.</p>
      <p>This paper addresses these two issues. First,
it presents the results from a perception
experiment which tested whether analytic comparatives
are indeed easier to process for listeners.
Contrary to this hypothesis, the reaction times show
that analytic comparatives have a processing
disadvantage in perception. Then, a production
experiment is discussed which elicited spoken
sentences containing a comparative construction. The
analysis reveals that the processing complexity is
a significant predictor of the comparative
alternation: with increasing complexity of the base
adjective, the probability of analytic comparatives
increases. Thus, the paper argues that speakers and
listeners process the English comparative variants
differently, and that it is the speaker who benefits
from a compensatory use of more comparatives.</p>
      <sec id="sec-1-1">
        <title>Method</title>
        <p>
          Comparative variation in perception
31 native speakers of Canadian English
participated in an auditory decision task in which they
had to decide whether the acoustic stimuli was an
existing English form. The set of stimuli contained
the analytic and synthetic comparative form for 60
adjective types with at least 5 attestations for both
forms in the Corpus of Contemporary American
English
          <xref ref-type="bibr" rid="ref5">(Davies 2008-)</xref>
          . The stimuli were
produced by a male speaker of Canadian English with
phonetic training. He was instructed to produce
the stimuli in citation form with a single accent on
the primary stressed syllable of the base adjective
in both types of stimuli. Accordingly, more was
produced stressed, but unaccented.
        </p>
        <p>Alongside the 2 × 60 = 120 synthetic and
analytic comparatives, the set of stimuli also included
360 distractors. Some of the distractors combined
more with non-existing words, others combined
the adjective bases with the illegal suffix -ic. In
addition, the set of distractor items contained
nonexisting words ending in -er as well as existing
words and complex words. Examples of the test
stimuli are given in (1a), and distractor examples
are given in (1b).
(1) a. colder, happier, yellower</p>
        <p>more cold, more wealthy, more yellow
b. ∗coldic, more ∗gorsty, ∗rilker</p>
        <p>on wire, chasting
2.2</p>
      </sec>
      <sec id="sec-1-2">
        <title>Results</title>
        <p>
          The density estimate suggests that reaction
times are, in general, higher for analytic
comparatives than for synthetic comparatives. This
visual interpretation is supported by a linear
mixedeffects regression model with reaction times as
the dependent variable
          <xref ref-type="bibr" rid="ref4">(in order to fulfill the
linearity assumption of the linear model, the
reaction times were power-transformed with λ = -1.52,
see Box and Cox 1964)</xref>
          . The main predictor was
the factor Class (with values Synthetic and
Analytic). Additional predictors addressed several
influences that may be expected affect the reaction
times: the subject-specific variables Handedness,
Sex, and Age, the experimental variables Trial
number and Reaction time in previous trial,
          <xref ref-type="bibr" rid="ref1">(Preceding RT, see Baayen and Milin 2010 for a
discussion)</xref>
          , phonological variables (Metrical
structure of base, residualized Number of phonems),
and the lexical variables Number of phonological
neighbours, Mean RT of base adjective,
residualized Phonological Levenshtein distance
          <xref ref-type="bibr" rid="ref2">(PLD20,
all three from Balota et al. 2007)</xref>
          , Age of
acquisition
          <xref ref-type="bibr" rid="ref7">(from Kuperman et al. 2012)</xref>
          , Frequencies
of base, Analytic comparative, Synthetic
comparative (from COCA), Inflectional entropy
          <xref ref-type="bibr" rid="ref11">(cf.
Moscoso del Prado Mart´ın et al. 2004)</xref>
          . With the
exception of the three Subject predictors, the
initial model contained interactions between Class
and the other predictors. Finally, random
intercepts were included for the factors Subject and
Adjective base.
        </p>
        <p>After removal of insignificant predictors, the
final model reports significant interactions between
stimulus Class and Preceding RT, PLD20, Number
of phonemes, Synthetic frequency, and Analytic
frequency. Figure 2 displays the partial effects
for these interactions. The vertical axis shows the
transformed reaction times; higher values
correspond to longer reaction times.</p>
        <p>In agreement with figure 1, the partial effects
reveal significantly lower estimates for the
synthetic stimuli (solid lines) than for the analytic
stimuli (dashed lines). This is true even in the
most adverse conditions (e.g. in cases in which
the synthetic comparative of a comparative is
attested only very rarely in a linguistic corpus, left
edge of lower right panel in figure 2).</p>
      </sec>
    </sec>
    <sec id="sec-2">
      <title>Comparative variation in production 3</title>
      <p>3.1
41 native speakers of Canadian English
participated individually in a spoken sentence
completion task. The task used the same set of 60
adjectives as in the perception experiment above, but
none of the participants in the production
experiment had also participated in the previous task.
Participants were first shown a context sentence
containing the adjective in the positive. After a key
press, an incomplete target sentence containing a
blank and one or more target words appeared also
on the screen. The participants were instructed to
use the target words to fill the blank in the
sentence. If necessary, they could also use additional
words to complete the sentence. The sentences
were constructed in such a way that a comparative
construction was the most likely target for
completion, but participants were not explicitly instructed
to use comparatives. The structure of the
incomplete sentences was the same in all trials. The
subject was a simple noun phrase, followed by a
copula verb. The blank to be filled followed in
predicative position. This design ensured that the
context-dependent factors reported in the literature
such as the increased probability of analytic
comparatives in predicative position were held
constant for all adjectives. Example (3) shows the
experimental trial for the target adjective wealthy.
(2) The duke is wealthy.</p>
      <p>Yet, the king is
WEALTHY
.</p>
      <p>The experiment also contained 105 distractor
trials that had a similar structure, but which did
not contain adjectives as the target words.
3.2</p>
      <sec id="sec-2-1">
        <title>Reaction times</title>
        <p>In order to be able to investigate the effect of the
processing complexity of the base adjective on the
preferred comparative variant, the same 41
speakers first participated in a visual lexical decision
task that gathered reaction times for the 60 target
adjectives, as well as 150 other existing and
nonexisting distractor items. The participants were
not informed about the purpose of this task, and
there were at least 14 days for each participant
between the lexical decision task and the production
experiment. The reaction times obtained in this
task were pooled for each adjective, and the
median was calculated.
3.3</p>
      </sec>
      <sec id="sec-2-2">
        <title>Results</title>
        <p>For most of the adjectives, the completion task
was successful in obtaining comparative responses
from the 41 speakers. However, two participants
produced hardly any comparative in the task, and
were therefore excluded from the data set. 6 out
of the 60 adjectives were excluded because the
responses contained almost exclusively synthetic
or analytic comparatives, or because the context
sentence did not elicit a considerable number of
comparative responses. 747 out of the
remaining 39 × 54 = 2106 responses contained a
synthetic comparative (35 %), 843 contained an
analytic comparative (40 %). The remaining 516
responses (25 %) did not contain a comparative
construction, and were discarded. There was notable
variation between the two variants both across and
within items, which indicates that English
comparative variation is indeed a highly non-deterministic
field that is apparently affected by both
speakerdependent and adjective-dependent factors.</p>
        <p>
          Logistic general additive mixed-effects models
          <xref ref-type="bibr" rid="ref13">(cf. Wood 2006)</xref>
          were used to investigate the
relation between the median RTs and the individual
responses. These models have the advantage of
revealing statistically significant effects of the
independent variable on the dependent even if the
relation between them is not a linear one. For instance,
there could a threshold in the reaction times up to
which speakers strongly prefer the synthetic
comparative, but beyond which they shift to analytic
comparatives in a nearly categorical way. In such
a case, a linear model might fail to detect this
nonlinear effect of RTs on the responses.
        </p>
        <p>Two models were fitted: a null model which
contained only a random effect for speaker, and</p>
        <p>Discussion and conclusion
a model with an additional smooth term for the
effect of the median RTs. If processing
complexity has a notable effect on speaker responses, the
smooth term should turn out to be statistically
significant, and the predictive accuracy of the model
should improve by the addition of the term. As
table 1 shows, this is indeed the case. While the
null model has a total predictive accuracy of about
69 %, the addition of the smooth term for median
RTs increases the accuracy by 5.6 %. There is a
larger increase of predictive accuracy for analytic
responses than for synthetic responses (7.1 % vs.
3.9 %).</p>
      </sec>
    </sec>
    <sec id="sec-3">
      <title>Acknowledgments</title>
      <p>This work was supported by the Deutsche
Forschungsgemeinschaft (grant KU 2896/1-1). I wish
to thank Ben Tucker (University of Alberta,
Edmonton) for making available to me the facilities
of the Alberta Phonetics Laboratory for the
experiments reported in this paper.</p>
    </sec>
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