Running Head: PROCESSING-CENTERED REDUCTION
A Processing-Centered Look at the Contribution of Givenness to Durational Reduction
Jason M. Kahn and Jennifer E. Arnold
University of North Carolina at Chapel Hill
Author Note
Jason M. Kahn, University of North Carolina at Chapel Hill; Jennifer E. Arnold,
University of North Carolina at Chapel Hill.
This research was supported by: NSF grant BCS-0745627 to J. Arnold. We gratefully
acknowledge the assistance of Kellen Carpenter, Isaac Hellemn, Jennifer Little, Michael Parrish,
Giulia Pancani, Jennifer Tate, and Alyssa Ventimiglia, in both running the experiments and
transcribing the data.
Address correspondence to: Jason Kahn, CB#3270 Davie Hall, Chapel Hill, NC 275993270. Email:jmkahn@email.unc.edu
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Abstract
Givenness tends to lead to acoustic reduction in speech, but little is known about whether
linguistic and non-linguistic givenness affect reduction similarly, and there is little consensus
about the underlying psychological mechanisms. We examined speakers’ pronunciations of
target object nouns in an instruction-giving task, where speakers saw objects move and described
this to a listener. The target objects were linguistically or non-linguistically given (i.e. spoken
aloud or flashed). With predictability held constant, linguistic givenness resulted in more
reduction than non-linguistic givenness, while both elicited more reduction than control
conditions. We use these findings to consider two possible mechanisms of givenness effects: an
explicit information status-based trigger account and a facilitation-based account. We propose
that our findings are most naturally accounted for by a mechanism in which givenness leads to
facilitation of representations and processes in the production system, which leads to reduction.
Key words: reduction, predictability, givenness, acoustic prominence
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A Processing-Centered Look at the Contribution of Givenness to Durational Reduction
When a professor introduces the concept of neural network to her psychology class, she
pronounces the words clearly and distinctly: “nur-ral net-work,” perhaps pointing to a diagram
on the board. For the rest of the lecture, her pronunciation may more closely resemble “n’ral
netw’rk,” with the same words, although less clearly and with shorter duration. This variation in
pronunciation is ubiquitous, and is systematically related to properties of the word, its referent,
and the discourse context. Perhaps the most influential account of this phenomenon observes that
the professor’s use of “neural network” changes the information status of both the words and
their associated concept. The phrase enters the conversation with new status, but thereafter the
phrase and the concept are both given as a part of the shared discourse. In this paper, we examine
the role of linguistic and nonlinguistic givenness on acoustic reduction, with the goal of outlining
possible mechanistic accounts for why speakers reduce the duration of given words.
Speakers produce words along a continuum, ranging from acoustically prominent and
emphatic to reduced. Reduced tokens have relatively shorter duration, lower pitch and voweltarget articulation, less pitch variation, and/or incomplete segmentation (Aylett & Turk 2004,
2006; Bell, Jurafsky, Fosler-Lussier, Girand, Gregory & Gildea, 2003; Bell, Brenier, Gregory,
Girand, & Jurafsky, 2009; Jurafsky, Bell, Gregory & Raymond, 2001, Pluymaekers, Ernestus &
Baayen, 2005a, 2005b; inter alia). The reduction of pitch height and pitch movement may be
related to choices about whether to accent a word or not, but it has been demonstrated that
variations on acoustic clarity do not depend entirely on accenting (Aylett & Turk, 2004; Bard &
Aylett, 2004; Watson, Arnold, & Tanenhaus, 2007). All of these prosodic features contribute to
an utterance’s overall intelligibility (Arnold, Kahn & Pancani, in press; Bard, Anderson, Sotillo,
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Aylett, Doherty-Sneddon & Newlands, 2000; Galati & Brennan, 2010), i.e. how easily a listener
can identify the word out of context.
There is abundant evidence that speakers reduce words that are repeated or that refer to
given (previously evoked) information. However, there is little agreement about exactly how
speakers represent information status, or how these effects emerge from or within the
mechanisms of language production. Moreover, there are no psycholinguistic models of these
processes. In this paper we experimentally test how acoustic reduction is affected by different
kinds of “given” information status, focusing on the contrast between information that has been
mentioned linguistically and that which has been evoked non-linguistically. This provides one of
the first systematic explorations of how linguistically and non-linguistically presented
information affect production differently.
The comparison between two types of givenness is theoretically relevant to our broader
goal of investigating possible mechanisms that explain speakers’ tendency to reduce given
information. We specifically consider two types of mechanism. Under the traditional account,
speakers explicitly represent information status, and this representation triggers their use of
particular acoustic forms. This view predicts that the representation of the discourse must contain
any information relevant to acoustic form, such as its degree of availability, or its source (e.g.
linguistic vs. non-linguistic). In contrast, we propose a facilitation account, whereby the
facilitation of language production representations and processes determines acoustic form,
without necessarily referring to an explicit representation of information status. We begin with a
summary of the effects of givenness on prosody, and then outline each account before describing
the experiments.
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Information Status Effects On Acoustic Prominence
It is well established that linguistic form varies as a function of the information status that
it encodes. Most simply, many theorists mark a distinction between given and new information
status (Chafe, 1976; Clark and Haviland, 1977; Halliday, 1967; Prince 1989, 1992). Given
information has already been mentioned, or otherwise evoked, by the participants in a
conversation, whereas new information has not. More fine-grained categorizations of
information status provide better accounts than a simple given/new contrast (see Arnold, 2008),
but here we focus primarily on the given/new dichotomy for simplicity.
Given information status correlates with numerous aspects of linguistic form, including
accenting and acoustic prominence (Breen, Fedorenko, Wagner & Gibson, 2010; Halliday, 1967;
Venditti & Hirschberg, 2003), lexical choices (e.g. pronouns vs. more specified expressions;
Ariel 1990; Arnold, 2008, 2010; Chafe, 1976; Gundel, Hirschberg & Zacharski, 1993; Prince,
1992), word order (Birner & Ward, 1993), and constituent order (Arnold, Wasow, Ginstrom, &
Losongco, 2004; Bock & Irwin, 1980). Here we focus on acoustic variation, particularly word
duration.
Analyses of word pronunciations in running speech have demonstrated that references to
previously-mentioned information tend to be shorter and less intelligible than references to new
information (Brown 1983; Fowler 1988; Fowler & Housum 1987). For example, in a map
description task, speakers who have already produced a reference to a landmark on the map tend
to reduce its form on the second production (Bard & Aylett 2004, with data from Anderson,
Bader, Bard & Boyle, 1991). This phenomenon appears to have more to do with the act of
referring than the linguistic form itself, as non-co-referential repeated mentions do not get
reduced (Bard, Lowe & Altmann 1989; Fowler 1988). Comprehension experiments have also
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demonstrated that listeners tend to prefer reduced forms for given information (e.g., Arnold
2008; Baumann & Grice 2006; Bauman & Hadelich 2003; Dahan, Tanenhaus & Chambers
2002).
An open question in this domain is whether only the linguistic context can grant given
information status, or whether other contexts can as well, such as the environment or the
speaker’s goals. Some accounts of givenness suggest that information can be evoked nonlinguistically. Clark and Marshall (1981) propose that given status can result from either
linguistic or visual co-presence (see also Prince, 1981; 1992). I could say “neural network”, or I
could point to the words written on the board, and either way make the information salient. Yet
the canonical “given” status results from explicit linguistic mention, and this is the most frequent
experimental manipulation of given status (although cf. Brown-Schmidt, 2012; Horton &
Keysar, 1996). No current theory of givenness suggests that linguistic mention confers a
different status than non-linguistic evocation of the same information.
Few studies have explicitly examined the difference between linguistic and non-linguistic
sources of givenness. Baumann and Hadelich (2006) found that visual primes did not constrain
listeners’ accenting preferences as strongly as linguistic primes. They suggested that visual
primes may be less “given” than linguistic primes. By contrast, Brown (1983) found deaccenting
for both textually and situationally given information, and Bard and Anderson (1994) found that
visual givenness led to lowered intelligibility. However, neither experiment systematically
compared types of givenness.
In sum, there is substantial evidence that information status predicts referential forms, but
it remains unclear how the source of givenness contributes to this effect. In addition, there is
little consensus about the psychological mechanisms that underlie this correlation.
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Processing Mechanisms
We consider two possible mechanisms to explain the effects of information status on
acoustic prominence. Because it is beyond the scope of the current project to present a full model
of acoustic reduction, instead we provide a sketch of two general approaches. First we consider
the kind of psychological mechanism that would be most consistent with the traditional view,
that information status selects for acoustic forms. Although these theoretical positions are
typically not framed in a mechanistic way, we suggest that they are most consistent with a
Trigger account, in which information status is explicitly represented. We then propose an
alternative, a Facilitation account, in which acoustic forms result directly from facilitation of
production processes. These approaches are not mutually exclusive, but do make different
predictions with respect to elucidating different possible psychological mechanisms of reduction.
Our discussion draws heavily on recent work on the processes of language production.
There is widespread agreement among current models that language production includes several
planning and processing stages (e.g. Bock, 1982; Dell, 1986; Garrett 1980; Levelt, 1989; Levelt,
Meyer & Roelofs (1999)). A characteristic outline of one such model (Levelt, 1989) is presented
in Figure 1. In this model, as in most of the models mentioned here, speakers represent the
concepts and relations they wish to express at the conceptualization stage, non-linguistically. At
the formulation stage, the lexical, syntactic, and phonological forms are encoded, and at the
articulation stage, the system generates a phonetic plan for articulation.
The Information Status Trigger Approach. The standard linguistic view suggests that
acoustic prominence results from pragmatic specialization, e.g. rules such as “select a H* pitch
accent for discourse-new information” (see, e.g. Pierrehumbert & Hirschberg, 1990). On this
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view, some information statuses trigger reduced pronunciations, whereas some trigger fuller
pronunciations. Although psychological mechanisms for such models have not been explicitly
proposed, such theories seem to require that the speaker have a representation of the conditions
of selection, for example a distinction between given and new status.
This kind of information status-based selection of acoustic form has parallels in choices
between different referential forms, such as pronouns vs. more explicit expressions (e.g., Arnold,
1998; 2008; 2010; Gundel et al., 1993; Bard et al., 2000). For example, Schmitt, Meyer, and
Levelt (1999) propose a model of German pronoun production (see also van der Meulen, Meyer,
& Levelt, 2001). Their model is based on Levelt’s (1989), which, like other current models of
language production, assumes that speakers represent information status at the message or
conceptualization stage of language production. Schmitt et al. posit a single “focus”
representational unit at the conceptual level, described as a “discourse-dependent switch in the
processing model”. This focus unit serves as a gate that determines whether a pronoun or name is
selected (pp. 316-317). In fairly direct analog, this type of model could apply to choices about
reduction. It might select a reduced form if the focus node has sufficient activation, and an
unreduced form otherwise. Alternatively, the focus node might trigger an acoustic reduction rule
(e.g. ‘deaccent here,’ or ‘shorten this vowel’), as opposed to a categorical choice between forms.
Selection in this latter case would occur in addition to any other constraints on prosodic form
(e.g. coarticulation, prosodic or syntactic position, etc.).
Crucially, the trigger approach posits a categorical representation of information status,
and that the model selects a form or rule based on the information status category. Although the
Schmitt et al. (1999) model includes only a binary contrast between “focus” and “not focus,” it
could in principle include finer-grained information status differences. For example, Levelt
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(1989) proposes that speakers model the information status of referents with four categories: a)
inaccessible, b) accessible, c) in discourse model, and d) in focus. This view coheres with
literature on information status, and in particular with proposals that allow given information to
vary in accessibility or focus status (e.g. Ariel, 1990, Chafe, 1994, Gundel et al., 1993).
Likewise, if linguistic and non-linguistic givenness affect reduction differently, this approach
would need to include different nodes for each status type.
The Facilitation-Based Reduction Hypothesis (FRH). A second possible explanation
for acoustic reduction, which we propose here, is that it emerges from facilitation of the
mechanisms of production. We hypothesize that reduction results from some combination of 1)
activation of the conceptual and linguistic representations associated with a word, and 2)
facilitation of the processes associated with generating an articulatory plan from a concept. The
strong version of this view is that any stimulus that differentially facilitates processing associated
with a to-be-produced word or its environment should lead to some measurable amount of
reduction. Moreover, the degree of reduction should correspond to the degree of facilitation,
either within or across levels of processing, although not necessarily in a linear fashion.
Facilitation of the concept associated with an entity, for example, might lead to more reduction
when paired with facilitation of the appropriate word’s lexical or phonological representations.
Although this strong version may not hold, we can use it to generate testable predictions about
gradient effects of reduction due to language processing facilitation.
The FRH builds on other suggestions that processing facilitation may lead to reduction
(e.g., Balota, Boland and Shields, 1989; Bard et al., 2000; Bell et al., 2009; Lam & Watson,
2010). For example, Balota, et al. explain the priming of one word (e.g., cat) from an associated
word (e.g., dog) as the result of greater activation of the target lemma representation. This
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activation influences the rate at which phonemes are selected and motor codes are sequenced.
Their account builds in turn upon interactive models of production (e.g., Dell, 1986), which
allow the activation of representations at one level to influence the activation of representations
at another level in the production system. Bell et al. propose that speakers modulate word length
as a result of a coordination mechanism between planning and articulation. We extend these
ideas in two ways: 1) not just activation of representations, but facilitation of processing more
generally, should lead to reduction, and 2) facilitation at any level of representation should lead
to reduction.
Our proposal is critically based on a view of givenness as a category with multiple
features, each of which may facilitate processing independently. Givenness minimally includes
processing of the conceptual features of an entity, which in and of itself may facilitate later
reference to it. Often givenness also involves actual mention of the entity, and in situations
where it may be predictable or not. The phonological processes associated with the name may be
activated in other ways as well, potentially leading to independent facilitation. This view is
broadly similar with Bock and Irwin’s (1980) analysis of how givenness affects syntactic
choices. They propose that referential availability and lexical availability affect the speed of
lemma activation independently, thus each contributing to the speaker’s syntactic choices.
Facilitation may lead to durational reduction in a number of ways. One possibility is that
greater activation results in faster selection of the conceptual representation, which results in
faster selection of lexical representations. Likewise, activation of the lemma, phonemes, or
articulatory routine could speed their selection (Balota et al., 1989; Bell et al., 2009; Gahl, 2008),
although this view is not universal (for opposing views see Levelt, 1989; Jurafsky et al., 2001).
In running speech, this means that the subsequent word could be planned and produced earlier as
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well. Perhaps more importantly, speakers may experience priming of the processes associated
with producing a particular word or phrase. For example, phonological encoding includes not
only activating phonemes, but sequencing them as well (Levelt et al., 1999). Uttering a word or
phrase, or hearing it uttered, may facilitate this ordering process, as well as activate the
constituent representations (for further discussion see Arnold & Watson, under review).
One benefit of a facilitation-based approach is its consistency with known correlates of
acoustic reduction. In particular, it offers a natural account of the well-known tendency to
acoustically reduce information that is predictable or probable within context (Bell et al., 2009;
Gregory, Raymond, Bell, Fosler-Lussier & Jurafsky, 1999; Jurafsky et al., 2001; Lam & Watson,
2010; Lieberman 1963; Watson, Arnold, & Tanenhaus, 2008, inter alia; see also Levy & Jaeger,
2007). Although each of these studies finds slightly different results, and posits a slightly
different mechanism of action, the pattern of findings points to an effect of language production
processes on word duration.
Predictions about Linguistic and Non-linguistic Givenness
The Trigger hypothesis, as sketched above, critically differs from the FRH in that it
explicitly models information status, whereas the FRH suggests that reduction emerges as a
result of processing facilitation, without necessarily making use of a representation of
information status. To explore this difference, we examine how acoustic reduction is affected by
different kinds of givenness: linguistic and non-linguistic.
The trigger account represents a mechanistic instantiation of current theories of
givenness, which do not predict any different effects for linguistic and non-linguistic givenness.
Many accounts of givenness implicitly focus on linguistic givenness, which might suggest that
non-linguistic givenness does not lead to reduction at all. To the extent that non-linguistic
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sources of givenness are acknowledged, the source of givenness (linguistic vs. non-linguistic) is
generally considered irrelevant to the status of “given.” This account would thus predict an
equivalent degree of acoustic reduction for both linguistically and non-linguistically given
information, assuming both types of information make the entity given to the same extent (e.g.
familiar, or activated).
By contrast, the FRH predicts that the degree of facilitation throughout the production
system will determine the degree of reduction. If linguistically primed, for example by being
spoken aloud, reference to an object (e.g., “airplane”) should facilitate both the conceptual level
and lower-level linguistic representations, such as lexical and phonological information. Nonlinguistic priming of the same referent should activate the conceptual representation, but not
lower-level linguistic information to nearly the same extent. Although both sources of givenness
activate the entity, and make it a possible conversational referent, they act on different levels of
representation in the production system. Thus, the FRH contrasts with the trigger account, in that
it predicts that non-linguistic priming should lead to acoustic reduction, but less so than linguistic
priming.
Experimental Overview and Logic
In both experiments reported here, participants performed a variant of a referential
communication task developed by Watson and Arnold (2005; see also Lam & Watson, 2010).
Speakers issued instructions to listeners about the movements of three different pictured objects
from an array, as in Figure 2. For example, after seeing a picture of an airplane shrinking, the
speaker would tell the listener “the airplane shrinks.” The listener would then make the airplane
shrink on his or her screen. A second and then a third object movement and an instruction would
follow, with the same movement-utterance-execution sequence performed for a different object.
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The critical manipulation was whether the objects were a) linguistically primed (by having their
name previously mentioned), b) non-linguistically (i.e. visually) primed. Each of these
conditions was compared with a control condition, in which the objects were merely displayed,
with no special attention called to them.
One potential problem with examining givenness effects is that they are frequently
confounded with predictability at the referential level, which is also associated with the
frequency of lexical items. A referent’s becoming given increases its likelihood of reuse in a
conversation (Arnold, 1998, 2010; Givón, 1983). Indeed, some scholars define givenness in
terms of predictability (see Prince, 1981, p. 226). Observing reduction on a particular word
rarely allows one to reliably attribute the effect to givenness or predictability, even with
considerable knowledge about the spoken context. Instead of doing away with it entirely, our
experiments control for predictability, and assess the independent contribution of different types
of givenness. In Experiment 1, given referents are all completely predictable; in Experiment 2
they are all relatively unpredictable. The type of predictability we control differs substantially
from the type normally addressed in the literature (e.g. Bell et al., 2009). N-gram probability and
frequency refer to properties of words in a text, whereas our experiments control referential
predictability, the probability of referring to a particular entity.
In Experiment 1, we test two major predictions of the FRH, which stem from the
questions raised earlier: 1) Does non-linguistic givenness ‘count’ for the purposes of reduction?
2) Do linguistic and non-linguistic givenness elicit different degrees of reduction? In Experiment
2, we ask two questions that further clarify the effect of givenness: 3) Does givenness operate
independently of predictability for the purpose of producing reduction? 4) Does the same
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relationship between givenness and predictability hold for linguistic and non-linguistic
information?
There is an issue that is not addressed in the current study, namely the question of
whether acoustic reduction is triggered by the needs of the addressee (c.f. Arnold, Kahn, &
Pancani, in press; Bard et al., 2000; Bard & Aylett, 2004; Galati & Brennan, 2010; Halliday,
1967; Kahn & Arnold, under review; Lindblom, 1990; Rosa, Finch, Bergeson, & Arnold, under
review). Addressees can identify given and predictable referents more easily than new or
unpredictable ones, with the consequence that the speaker can produce a less explicit linguistic
form and still expect the addressee to identify the correct referent. The production system might,
as a consequence, include representations of the addressee’s knowledge, perhaps in parallel with
each of the levels of processing outlined above. Speakers and addressees often share a
considerable amount of information during a conversation, such that speaker-centric and
addressee-oriented processes make similar predictions in many situations.
In both of our experiments, the speaker gave instructions to a live addressee, who then
performed the action on their screen. All our manipulations of information status were identical
for both speaker and addressee. We discuss issues of audience design elsewhere (Arnold et al., in
press; Kahn & Arnold, under review, Rosa et al., under review; Rosa & Arnold, 2011)
These experiments provide the first (to our knowledge) systematic test of how linguistic
and non-linguistic givenness affect speakers’ durational reduction, while controlling for
predictability.
Experiment 1
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Method
Participants. A total of 15 female undergraduates participated in an instruction-giving
experiment as speakers for course credit. Females were not specifically recruited; however, for
homogeneity, females were asked to serve as speakers whenever possible. 3 were excluded due
to equipment failure, for a total of 12 speakers. 9 additional undergraduates (2 female)
participated in the experiment as listeners for course credit. The remaining 6 speakers were
paired with a lab assistant (3 with one of two female assistants, 3 with a male assistant).
Materials and Design. 221 colorized versions of the Snodgrass and Vanderwart (1980)
line drawings served as the stimuli (Rossion & Pourtois, 2001). These drawings were normed by
native French speakers for imageability, visual complexity, familiarity, as well as name
agreement in French, although this latter measure was not used here. The appendix lists the
names of the 221 experimental items. The English name of each picture, as reported in Rossion
and Pourtois (2001), was recorded by the first author for use in the linguistic priming condition.
All of these recordings were made on a Marantz professional solid-state recorder over an Audio
Technica professional microphone headset, using citation format (i.e. no distinguishing
inflection, and clear pronunciation).
On each trial, participants saw an array of 8 objects. Three of these objects were the
target objects, i.e. those that were to be mentioned by the speaker in spoken instructions (e.g.,
The windmill shrinks, the tomato rotates left, the candle fades). The third (last) object to be
mentioned was termed the experimental target (here: the candle). The other two instructions
referred to the non-experimental targets. Each target performed one of five actions (expand,
rotate left, rotate right, shrink, and fade), which were assigned randomly, with the condition that
each action could occur no more than once per trial.
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The critical manipulation in the experiment was whether within the trial the target objects
were linguistically given, non-linguistically given, or not made given explicitly. On linguistic
trials, the target objects’ names were spoken aloud (over computer speakers from the recordings
mentioned above) in random order, at a volume both participants could hear, before the
instruction-giving portion of the trial. On non-linguistic trials, all three target objects flashed
twice, simultaneously, on both participants’ screens, before the instruction-giving portion of the
trial. On control trials, nothing distinguished the target objects from the other objects, all of
which stayed on the screen for 2.5 seconds (the approximate mean time required to say three
objects’ names, or make the objects flash) before the instruction-giving portion of the trial.
A critical property of our design was that the experimental targets (i.e., the last objects to
be mentioned on a trial) were perfectly predictable in the priming conditions. In the control
condition they were not especially predictable, beyond the expectation that one of the 8 pictured
objects would be mentioned. Thus, the linguistic and non-linguistic givenness conditions were
identical in terms of referential predictability, and both differed from the control condition.
Following Arnold and Griffin (2007) and Watson, Arnold and Tanenhaus (2008), we
used a modified Latin Square design, in which each participant saw each item in all three
conditions. This allowed us to directly compare the production of a word across conditions for
each participant. The 24 experimental target items were organized into lists of 8 items, and each
list occurred three times, once in each condition. Each list had approximately equivalent mean
values of log frequency, syllables, imageability, familiarity, and visual complexity. One object
from the appropriate list was randomly selected on each trial to serve as the target object. The
other 7 objects in the array were selected at random. Two of these served as the nonexperimental targets.
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Thus, there was a total of 9 blocks, including three of each condition type (i.e. three
linguistic, three non-linguistic, three control). Conditions were organized into triads, such that
each condition had to appear once before another could appear again, and no condition could
appear twice in a row. Thus, the first three blocks represented a standard Latin Square design,
where each item was only viewed once. Six sequences in this format were created from Latin
Square combinations of the target item sets and the conditions. See Figure 3 for a schematic
example of a sequence. A separate analysis (not reported here) of the first blocks was performed
to test that our effects were not the result of repeated experience with an item over the
experiment. Each of the 6 sequences was seen by two speakers. Each speaker participated in 72
trials, for a total of 216 uttered instructions.
Procedure. The speaker and the listener each sat in front of a separate computer, at a
distance that permitted them to communicate but not see the other’s screen. Both participants
saw task instructions on their own screen. Participants were instructed that they would see arrays
of objects, and were given an example of such an array (Figure 2). The speaker was told that she
would simply issue instructions about the objects’ actions to her partner, who would mimic those
actions on his or her computer. Examples of the possible actions were then shown with random
stimuli, and a sentence frame was provided. For example, the speaker’s instructions might have
said “You might see [an airplane rotating left], and you might say ‘The airplane rotates left.’”
The listener would have simultaneously seen “You might hear ‘The airplane rotates left,’ and
you would click the airplane and then the ‘Rotates Left’ button.” The task goal of the participants
was simply to issue and follow instructions appropriately.
The participants were told that the experiment would be divided into sets of trials, and
that before each set they would know whether they would receive linguistic, non-linguistic, or no
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priming information about the target items. Six practice trials followed these instructions, two
from each condition. The objects on these practice trials were randomly selected, and did not
include any experimental items.
A customized Python script written by the first author controlled the experiment. The
speaker’s stimuli were presented on a laptop PC, and the listener’s were presented on a desktop
PC. Participants were offered an opportunity to take a break between blocks. The entire
experiment took approximately 45 minutes.
Analysis. Utterances were analyzed individually using Praat software (Boersma &
Weenink 2009). The first author examined the visual waveform and listened to the sound file to
identify the onset of each trial (indicated by a beep that co-occurred with each action onset), as
well as the onset and offset of the determiner the, the noun, and the action phrase.
We report analyses for the duration of each segment, across all three blocks. The latency
to speak for each instruction should reflect planning time, where shorter latencies indicate less
complex and/or demanding plans. The duration of the noun should most strongly reflect our
manipulation, i.e. whether the primed object had in fact become a good candidate for reduction.
Utterances were excluded if they were disfluent in any way (i.e. pauses longer than
250ms, coughs, false starts, disfluent ‘the’) or if the speaker used the wrong object or action
word. The error rates (pooled across all error types) for the third instructions were 8%, 12%, and
13%, in the linguistic, non-linguistic, and control conditions respectively.
For each segment, we built a multi-level model to assess the contribution of givenness.
The logarithm of each duration was taken to increase its linear relationship with the predictors.
Outlier exclusion was not necessary after this transformation. Models were constructed with the
lmer function from R’s lme4 package, which uses maximum likelihood estimation to obtain
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parameter estimates. We first constructed a baseline model to specify the random effects
structure and to identify the significant control variables. Each baseline model included random
intercepts for subject and item, as well as random slopes for the contrasts. If the slope for the
contrast correlated with the intercept, or the individual contrasts correlated with each other,
greater than .9, the redundant slope was removed to avoid overparametrizing the model. After
adding the random effects, each model was built stepwise to include the following control
variables: log frequency (based on the original Snodgrass & Vanderwart (1980) English names),
imageability, visual complexity, and familiarity of the experiment target (taken from Rossion &
Purtois (2001)), the number of syllables of the experimental target and of the action word, and
the trial number (to control for practice effects). Because of high correlations among these
control variables, the following two residualizations were performed by regressing one predictor
on one or more others, and using the residuals as the control variable: log frequency had
imageability, familiarity, and visual complexity residualized out; object syllables had log
frequency and imageability residualized out. We also included the durations of the other
segments of the utterance. The model for object noun duration, for example, included the onset,
article, and action word duration. Any predictor that did not approach significance in this
baseline analysis (a t value of approximately 1.5) was removed.
The predictor of interest, condition, had three values, and all pairwise contrasts were
relevant. To facilitate these comparisons, we constructed two sets of Helmert contrasts. These
compare the mean of one level against the means of all the previous levels of a categorical
independent variable. For the first set, we compared the control condition to the non-linguistic
condition, as well as the linguistic condition to a combination of the control and non-linguistic
conditions. The focus for this set was the comparison between the control and non-linguistic
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condition. For the second set, we reversed the levels and compared the linguistic condition to the
non-linguistic condition, and the control condition to a combination of the linguistic and nonlinguistic conditions. The focus for this set was the comparison between the two experimental
conditions. Because both sets of contrasts could not coexist in a single model, we fit one model
for each set, and doubled our significance criterion (from .05 to .025). Significance was assessed
under the assumption that a sufficiently large dataset (n = 770 for the critical analysis here) could
generate parameter estimates and standard errors whose sampling distribution approximates a zdistribution (Baayen, 2008).
Results
As shown in Table 1, both linguistic and non-linguistic givenness led to shorter target
nouns than the control condition, with more reduction in the linguistic than non-linguistic
conditions. Both given conditions also exhibited shorter onset latencies than the control
condition. There were no effects in the action word region, and determiners were only
marginally shorter in the linguistic condition. Tables 2 and 3 show the parameter estimates and
overall model designs for each segment of the utterance, separated by the two different contrast
sets.
Onset to Speak
We tested the significance of these patterns in two models, as described above. For the
first set of contrasts, the durations of the onset to speak in the linguistic condition differed from a
combination of the non-linguistic and control conditions (β = -.021, SE = .0028, t = -7.48, p <
.0001), and the non-linguistic condition differed from the control condition (β = .071, SE =
.0049, t = 14.49, p < .0001). The second set of contrasts reversed the comparison, and showed
that the linguistic condition and non-linguistic condition did not differ (β = -.004, SE = .0048, t =
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0.78, p > .44), and that the control condition differed from a combination of the linguistic and
non-linguistic condition (β = .046, SE = .0028, t = 16.13, p < .0001). The two models together
showed that the onset was shorter for both linguistic and nonlinguistic given conditions, relative
to the control condition, but there was no difference between types of givenness.
Determiner
The linguistic condition was somewhat shorter than the other two conditions, but there
were no other significant differences. In the first set of contrasts, the linguistic condition
marginally differed from the other conditions (β = -.007, SE = .003, t = -2.09, p < .037), but the
non-linguistic condition did not differ from the control condition (β = .0047, SE = .0092, t =
0.51, p > .69). In the second set of contrasts, the control condition did not differ from the
experimental conditions (β = .0058, SE = .0047, t = 1.23, p > .22), and the linguistic condition
did not differ from the non-linguistic condition (β = -.0081, SE = .0072, t = -1.12, p > .26).
Target Word
The target noun duration, in contrast to the onset to speak, displayed a three way contrast:
the non-linguistic condition was shorter than the control, and linguistic condition was even
shorter. For the first set of contrasts, the linguistic condition differed from the other two
conditions (β = -.0075, SE = .0016, t = -4.7, p < .0001), while the non-linguistic condition
differed from the control condition (β = .0106, SE = .0028, t = 3.82, p < .0002). For the second
set of contrasts, the control condition differed from the experimental conditions (β = .009, SE =
.0016, t = 5.63, p < .0001), and the linguistic condition differed from the non-linguistic condition
(β = .0059, SE = .0025, t = 2.42, p < .016).
Action Word
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The manipulation did not have any significant effect on the action word durations. For
the first set of contrasts, the linguistic condition did not differ from the other two conditions (β =
-.001, SE = .0016, t = -0.59, p > .56), nor did the non-linguistic condition differ from the control
condition (β = -.0054, SE = .0028, t = -1.9, p > .06). For the second set of contrasts, the control
condition did not differ from the experimental conditions (β = .0022, SE = .0016, t = -1.34, p >
.18), and the linguistic condition did not differ from the non-linguistic condition (β = -.0041, SE
= .0028, t = -1.48, p > .14).
Discussion
Our results demonstrated reduction for both given conditions compared with the control
condition, and more for the linguistic than the non-linguistic condition. These effects occurred in
three of the regions reported here: 1) latency to speak, which was equally reduced for both given
conditions, 2) the determiner duration, where the linguistic condition was marginally shorter than
control, but not the non-linguistic condition, and 3) the noun duration, which showed a three-way
distinction between linguistic, non-linguistic, and control conditions. Because the carrier phrase
was essentially identical across conditions, and the action words were not at all affected by the
manipulation, the differences observed here can be attributed to the planning and/or execution of
the noun.
The result of greatest theoretical interest is the increased reduction in the linguistic
condition relative to the non-linguistic condition. This difference appeared on the object noun
duration, but not the onset duration. The second result of interest was the effect of non-linguistic
givenness on reduction. Both the onset to speak latency and the object noun duration were
shorter in the non-linguistic condition, compared with the control condition. This provides
PROCESSING-CENTERED REDUCTION
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empirical evidence that given status does not have to be linguistically established to elicit
reduction, at least in a situation with a predictable referent.
Critically, our givenness manipulation had an effect over and above any effect of speech
rate. The models included the durations of the other segments of each utterance, and still
revealed a significant effect of condition. Notably, not all segments significantly predicted the
durations of the other segments, and neither were the durations of the segments very highly
correlated with each other (fixed effect correlations approximately .2 or less). Similarly, an effect
based entirely on speaking rate could reasonably be expected to have emerged on all regions of
the utterance, with the possible exception of the onset latency. Each segment displayed a slightly
different pattern of results, suggesting that speakers were not uniformly modifying their
utterance length by modulating their speaking rate.
A remaining question is whether the observed reduction was the result of the linguistic
and conceptual givenness per se, or whether it depended on the fact that both types of givenness
signaled strong referential predictability in the current task. This would be consistent with the
fact that given information status correlates with predictability (Arnold, 1998). We examine this
question in Experiment 2.
Experiment 2
We tested the contribution of predictability to the results observed in Experiment 1,
where all linguistically and non-linguistically given targets were 100% predictable in the task.
Using a similar paradigm, we reduced the predictability of the targets, and tested the linguistic
and non-linguistic givenness on acoustic reduction. In this experiment, participants saw primes
on all trials, but only some of the primes were congruent, making the target given on only 1/8th
PROCESSING-CENTERED REDUCTION
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of the trials. The rest were incongruent, such that the target was “new” for that trial. The task was
designed to mitigate the effects of predictability as much as possible by creating a situation
where using the priming information to predict the target on a particular trial would “pay off”
infrequently. Participants who rehearsed the names of the primed objects covertly would only
benefit from doing so on 1/8th of the trials.
Experiment 2 investigated two questions: 1) Does givenness lead to reduction even when
the referent is not highly predictable? 2) When the referent is not highly predictable, do nonlinguistic and linguistic information still differ in their propensity to produce reduction, as they
did in Experiment 1?
Methods
Participants. A total of 43 undergraduates participated in exchange for course credit.
We excluded 1 speaker due to technical difficulties, and 2 for not following instructions, for a
total of 22 speakers (11 female). 7 participants were paired with a lab assistant. 3 different lab
assistants (2 female) played this role. All other participants were paired with another
undergraduate.
Materials. The same materials, including the colorized line drawings, recordings, and
hardware were used as in Experiment 1. We chose the 16 two-syllable target words from
Experiment 1 that elicited the greatest amount of reduction in the linguistic condition, relative to
the control condition. We used this method partly to control for the number of syllables in the
nouns and partly to give speakers the greatest opportunity to reduce.
Design and Procedure. The design was similar to Experiment 1, except that each trial
consisted of only one instruction, and all trials were preceded by a prime. After the prime, and
the object’s action, the speaker issued an instruction, which the listener executed, just as in
PROCESSING-CENTERED REDUCTION
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Experiment 1. Half the trials had a linguistic prime, where subjects heard the name of one of the
objects on the screen; the other half had a non-linguistic prime, where subjects saw the primed
object flash.
We manipulated the given/new status of the target by controlling whether the prime was
congruent or not. Of all the trials, only 1/8th had congruent primes, such that the chance of a
congruent prime was identical to the chance of selecting one of the eight objects on screen. Thus,
the design was 2 (congruent vs. incongruent prime) x 2 (linguistic vs. non-linguistic prime).
The entire experiment consisted of 128 trials, with a break at the halfway mark. Four lists
were created that crossed which conditions a participant saw particular items in, 8 experimental
items appeared in the first half of the experiment, with half of these appearing as linguistically
primed. Half of the experimental items that appeared in the first half of the experiment were
congruently primed, while the other half were incongruently primed, for a total of 16 congruent
primes. Across all participants, each experimental item appeared an equal number of times in
each of the cells formed by the 2x2 condition pairings. Each participant saw all items twice, once
in each half of the experiment. If an item appeared in one condition pairing in the first half (e.g.
linguistically and congruently primed), it appeared in the exact opposite pairing in the second
half (i.e. non-linguistically and incongruently primed). The only congruent primes participants
saw were for experimental items.
Participants completed 12 incongruent practice trials prior to the experimental trials.
These were designed to familiarize them to a greater extent with the action words, which several
subjects in Experiment 1 struggled with. No experimental items appeared as moving objects in
the practice trials. Participants were offered an opportunity to take a break halfway through the
experiment, which took approximately 45 minutes.
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Analysis. The analysis took the same general form as in Experiment 1, with two
exceptions: the linguistic and non-linguistic conditions were first examined together to determine
the overall effect, and then separately to test simple effects. In the full models, binary contrasts
for congruence (congruent vs. incongruent) and prime type (linguistic vs. non-linguistic) were
used. These parameters were centered to reduce collinearity with the interaction parameter.
Effects were considered significant at a t value > 1.96, in accordance with Baayen (2008). This
differs from the first experiment because we were not making multiple simultaneous
comparisons.
Approximately 11% of the data in the linguistic condition and 13% of the data in the nonlinguistic condition were excluded due to disfluency, with the same criteria as in Experiment 1.
Results
We report on the duration of each segment of the utterances. An examination of the
means (Table 4) suggests that both linguistic and non-linguistic givenness led to shorter onsets
and nouns. However, the model suggests that only linguistic givenness had a significant effect in
this experiment, in contrast with Experiment 1. The parameter estimates for each segment’s
model are shown in Table 5.
Onset to Speak
There was a significant effect of congruence (β = -0.049, SE = 0.011, t = -4.37, p <
.0001), a marginal difference between the conditions (β = -0.02, SE = 0.011, t = -1.75, p > .08),
and a marginal interaction (β = -0.04, SE = 0.022, t = -1.83, p > .07). In planned comparison
analyses, there was a significant effect of congruence in the linguistic condition (β = -0.07, SE =
0.016, t = -4.38, p < .0001), but only a marginal effect in the non-linguistic condition (β = -0.027,
SE = 0.016, t = -1.74, p < .08).
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Determiner
There was a significant effect of condition (β = -0.033, SE = 0.012, t = -2.8, p < .005),
with shorter durations in the linguistic than non-linguistic condition. None of the other effects
approached significance, either in the full model or planned comparisons.
Target Word
There was a significant effect of congruence (β = -0.013, SE = 0.0052, t = -2.48, p < .01),
as well as a significant interaction between congruence and condition (β = -0.024, SE = 0.01, t =
-2.55, p < .01). The difference between conditions was not significant (β = -0.0084, SE = 0.0052,
t = -1.62, p > .11). Planned comparisons in each condition revealed significant differences due to
congruence in the linguistic condition (β = -0.026, SE = 0.0072, t = -3.57, p < .0004), but not in
the non-linguistic condition (β = -0.00044, SE = 0.0075, t = -0.06, p > .95).
Action Word
There was a significant effect of congruence (β = -0.013, SE = 0.056, t = -2.29, p < .02),
such that congruent primes elicited shorter durations. While the effect of condition was not
significant (β = -0.042, SE = 0.052, t = -0.82, p > .41), the interaction of condition and
congruence (β = -0.018, SE = 0.010, t = -1.72, p < .09) was marginal. In planned comparisons,
the non-linguistic condition revealed no effect of congruence (β = -0.0029, SE = 0.0076, t = 0.38, p > .7), whereas the linguistic condition was significantly affected by congruence (β = 0.018, SE = 0.0073, t = -2.52, p < .01).
Discussion
The results revealed shorter noun durations for linguistically primed words, just as in
Experiment 1. The non-linguistic prime condition also led to numerically shorter words than the
control condition, but in contrast with Experiment 1, this difference was not significant. Planned
PROCESSING-CENTERED REDUCTION
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comparisons suggested that these effects also extended to the onset latencies and action words,
although these effects were weaker. As in Experiment 1, our models indicated that the priming
manipulation had an effect over and above any effect of speech rate.
Surprisingly, we also found that the determiner was shorter following linguistic primes
than following non-linguistic primes, regardless of congruence. This effect was not predicted by
either account, nor is it inconsistent with either account, so it will not be discussed further here
(but see Kahn & Arnold, under review).
Critically, this experiment demonstrated that the effect of linguistic givenness on acoustic
reduction does not depend on the referent being entirely predictable, as it was in Experiment 1.
The results also reiterated the contrast between linguistic and non-linguistic givenness. While
linguistic givenness led to reduction, non-linguistic givenness did not.
General Discussion
The clearest result to emerge from these experiments was the difference between the
effects of linguistic and non-linguistic givenness on reduction. In Experiment 1, although both
conditions reduced planning time to the same extent, the linguistic condition elicited more
reduction on the object word than the non-linguistic condition. And in Experiment 2, the
linguistic condition led to reduction, both in the latency to begin speaking and the object word
itself, whereas non-linguistic givenness did not. Together, these results suggest a separate role
for each type of givenness in the determination of durational reduction.
Experiment 2 further showed that after reducing the potential influence of predictability,
the effect of givenness on the noun persisted. However, this pattern held only for the linguistic
condition. There as a numerical trend toward reduction in the non-linguistic condition, but this
effect was not significant for either the onset or word regions. This may have simply resulted
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from a lack of power; we know that the effect size is small (given the results of Experiment 1),
and thus should be difficult to detect. Unfortunately, methods of power estimation are not
currently available for multi-level models. We can safely conclude that non-linguistic givenness
leads to reduction when coupled with predictability, but more work is needed to confirm whether
predictability is necessary, and why.
These results contribute to our understanding of the information status of salient, visually
available information, which has heretofore received relatively little attention. While some
models suggest that visually-available information carries given status (Clark & Marshall, 1981;
Prince, 1981), few studies have examined visual givenness independent from linguistic
givenness. Bard and Anderson (1994; Experiment 2) report that pronunciations were less
intelligible when the referent was present than when it was not, suggesting that visual givenness
does lead to reduction. However, their tokens were extracted from a corpus of adult-child
interactions, and their linguistic context was not reported. Thus, some referents may have been
linguistically mentioned as well, or otherwise supported by the linguistic context. Bard et al.
(2000; Experiment 4) report the converse, that visual givenness does not lead to any additional
reduction over and above linguistic givenness. Our study adds to these findings, and shows that
a) a direct manipulation of non-linguistic givenness produces reduction relative to a less-given
control, and b) speakers reduce less for non-linguistic than linguistic givenness, with
predictability held constant.
It is worth noting that there are many ways in which information can be visually given.
The simplest and most common circumstance is mere visual co-presence (Clark & Marshall,
1981), which suggests that anything that is visible to all interlocutors should count as given. In
this sense, one could argue that all of our conditions made the objects visually given, even the
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control condition. Yet intuitively it seems that some objects are more visually salient than others.
We found support for this idea, in that speakers used shorter pronunciations for the nonlinguistically given condition in Experiment 1, in which the target was visually co-present but
also salient.
Our findings also demonstrate that the effect of linguistic givenness does not depend
entirely from the referential predictability. Our experiments manipulate the likelihood that a
prime would be the target across experiments, and find that linguistic givenness led to reduction
in both. This evidence converges with the results of Lam and Watson (2010), who reported
durational reduction for repeated words, regardless of predictability. By contrast, in their
experiment predictability affects only intensity.
The use of referential predictability differs from most studies, which focus on
probabilistic relationships at the word or structural level (e.g. Bell et al., 2009; Levy & Jaeger,
2007; Gahl, 2008; Gahl & Garnsey, 2004). Our manipulation thus underscores (along with Lam
& Watson, 2010; Watson et al., 2008) the importance of an additional, “real-world” variable that
affects reduction, especially inasmuch as most corpora do not contain all the situational
information necessary for drawing inferences about given and/or predictable references to
entities (such as the entities present in the environment, where the participants are directing their
attention, etc.). Our design controls for the n-gram and frequency information internal to the
utterances, with our use of identical sentence frames (The [object] [verbs]), and still
demonstrates an effect of both linguistic and non-linguistic givenness.
Our empirical results also serve as a basis for discussion of the psychological
mechanisms that are likely to underlie reduction. Here we consider how the FRH and traditional
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information-status accounts might explain them.
Facilitation-Based Reduction
The results of both experiments support the FRH, which predicts that facilitation of
language production processes should lead to a corresponding degree of reduction. Specifically,
we predict that both linguistic and non-linguistic givenness should facilitate the conceptual
processing of a referent, whereas only linguistic mention would directly facilitate processes
related to the linguistic representations of the word, such as lexical and phonological activation.
Thus, linguistic givenness should lead to greater facilitation than non-linguistic givenness, and
thereby to greater acoustic reduction. In addition, non-linguistic givenness should create some
degree of facilitation, and thus some degree of reduction. Our findings support both of these
predictions.
The FRH also predicts that predictability should lead to facilitation of production
processing, insofar as it facilitates utterance planning. This is consistent with the finding that
predictability modulated the effect of non-linguistic givenness, but the precise mechanisms by
which predictability affects facilitation await subsequent work. One possibility is that it leads to
partial activation of the predictable information, which speeds the planning of the utterance, after
the speaker recognizes the trial’s action. Another possibility is that strong referential
predictability leads speakers to initiate planning of the target reference before the movement is
even detected. Our results cannot distinguish between these two explanations.
The above interpretation suggests that non-linguistic givenness leads to reduction only
through facilitation of conceptual-level processes. However, we must consider an alternative: a
“lexical activation” version of the FRH, consistent with other proposals that lexical factors lead
PROCESSING-CENTERED REDUCTION
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to reduction (Bell et al., 2009; Gahl, 2008). It may be that the only type of facilitation that
matters is lexical/phonological processing. In the linguistic condition, participants hear the word
form, which facilitates the processing of the word and its phonological representation. When the
non-linguistic condition makes the primed objects predictable (in Exp. 1), speakers might name
the primes sub-vocally, similarly activating the words’ representations. If non-linguistic priming
facilitates lexical processes less reliably than linguistic mention, it might account for our results.
Even if this interpretation finds support in future research, it is nevertheless important to note its
consistency with the FRH, in that it explains reduction as the result of processing facilitation,
rather than an explicit representation of information status.
Implications for Traditional Information Status Accounts
Although the distinction between linguistic and non-linguistic givenness is consistent
with the predictions of the FRH, traditional information status models could account for this
finding as well, with some slight modifications. However, these modifications rest on some
potentially problematic assumptions. We have suggested that a model with a trigger mechanism
best approximates the effect of information status on reduction, and this requires, at the very
least, an explicit representation of information status. There are two variants of such a model that
could explain our findings.
One possibility is that speakers represent different kinds of givenness. Numerous theories
of givenness identify different categories (e.g., Chafe, 1994; Levelt, 1989; Prince, 1981; 1992).
Prince (1981) distinguishes between textually evoked and situationally evoked information,
which might correspond to our linguistic and non-linguistic conditions. If so, each category may
represent different triggering conditions for acoustic reduction. This approach faces the challenge
of identifying the givenness categories that people actually represent. Does this require explicit
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representation of all of Prince’s (1981) distinctions (e.g., brand new, unused, non-containing
inferable, containing inferable, textually evoked, situationally evoked)? The precise taxonomy of
kinds of givenness is an empirical question. Yet if too many distinctions prove necessary, such a
system is likely to pose intractable memory or processing constraints. Moreover, an account like
this would not include a number of linguistic variables that also affect durational variation,
including frequency measures, lexical co-occurrence probability, and referential predictability.
The model could represent these factors in some fashion, but they are not traditionally
considered part of givenness per se.
A second possibility is that speakers instead represent givenness along a single dimension
(Ariel, 1990; Gundel et al., 1993). If so, different degrees of accessibility could trigger different
degrees of reduction. Under this view, linguistic and non-linguistic givenness create different
degrees of accessibility. This is consistent with Baumann and Hadelich’s (2006) conclusion that
visual primes are “less given” than linguistic primes. An alternate version of this view is that
speakers represent givenness as a binary category, but categorize non-linguistic primes as given
less frequently or reliably, possibly because they are less memorable.1 However, both variants
would predict that the linguistic and non-linguistic conditions should differ on all measures of
accessibility. Evidence against this comes from two sources: 1) the onset times in Experiment 1
did not differ across the two given conditions, suggesting that speakers did not require more
planning time in either condition, and 2) the error rates across conditions in Experiment 1 were
about the same, which suggests that they had the same amount of difficulty with targets in both
conditions.
1
We thank an anonymous reviewer for this idea.
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A third possibility is that our results are not relevant to information-status models. One
might argue that our experimental contexts establish an impoverished discourse context. The
relationship between the prime and target is not particularly meaningful, especially in
Experiment 2. There, givenness is also stripped of referential predictability, a fundamental
characteristic of givenness in natural discourse (Arnold, 1998; Givón, 1983). This might suggest
that there are two independent effects – acoustic reduction that is triggered by information status,
which occurs in contexts with a rich discourse structure, and facilitation effects, which occur in
tasks like the one used here. Yet such an account would entail positing two parallel production
mechanisms to explain the reduction of given information. Moreover, if givenness in our task
results in facilitation, it is likely to also result in facilitation in natural discourse, even with a
richer discourse context.
Conclusions
Our empirical results show that 1) linguistic and nonlinguistic givenness both lead to
reduction, 2) linguistic givenness has a stronger effect, and 3) referential predictability supports
the effect of nonlinguistic givenness on reduction. These findings fit naturally with our proposal
that facilitation leads to durational reduction. On this basis, we argue that it is not necessary to
assume that reduction makes reference to an explicit representation of information status in order
to account for our results. The primary appeal of the FRH is that it explains the results reported
here, as well as results from the studies reviewed above, without having to posit any additional
connections among representations or processes used for language production.
The strongest version of the FRH, however, was not supported. The lack of an effect of
non-linguistic information in Experiment 2 stood in contrast to the claim that any facilitation
should lead to measurable reduction. This could merely suggest that there are floor effects, where
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weak facilitation does not result in measurable reduction, as would be predicted by a formulation
of the FRH that included non-linearities. Nevertheless, more work is needed to identify the
precise conditions under which facilitation leads to reduction.
The FRH supplies specific questions for future work, by specifying predictions about the
ways in which different types of stimuli should influence word duration. The idea that givenness
can facilitate levels of processing independently allows for a variety of distinctions. For example,
it predicts that any stimulus that facilitates both the lexical and phonological levels should
produce measurably more reduction than a stimulus that activates either only the lexical level or
only the phonological level (see also Gahl, Yao, & Johnson, 2012; Yao, 2011). It might also
predict that linguistic givenness could vary in the degree to which it facilitates conceptual
processes.2 A further prediction is that speakers do not always reduce for their listener (Arnold,
et al., in press; Bard & Aylett, 2004). This is consistent with Bard and Aylett’s (2004) claim that
the production system cycles too quickly to incorporate information about the listener into
prosodic choices. Arnold et al. (in press) go further, and suggest that audience behavior may
itself lead to production facilitation. Moreover, we have found that speaking a word aloud leads
to more reduction than naming it to oneself, suggesting that the articulatory level plays a role in
reduction (Kahn & Arnold, under review). This result, however, is confounded with the speaker
having heard the word at all, and requires additional testing.
A further question is whether all levels of production contribute to reduction equally.
Fowler (1988) finds that simple word repetition while reading from a list does not produce
reduction. Perhaps facilitation at lower levels of the production system does not create reduction
by itself, and in fact requires referential or conceptual anchoring. However, Lam and Watson
2
We thank an anonymous reviewer for this suggestion.
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(2012) find that referential repetition is not necessary for reduction. Alternatively, the
conceptual/referential level of processing may interact superadditively with lexical- or sublexical representations and processes to create even more reduction in our tasks like ours.
Nevertheless, our work should not be taken to indicate that information status does not
exist, or that speakers do not represent it. Information status distinctions are correlated with
variation in linguistic form in multiple domains, and speakers are likely to represent this
information in a way that influences production processes. In addition, an explicit representation
of information status may prove necessary to explain some prosodic variation, such as pitch,
intensity, vowel-space modification, segment deletion, and so on. The FRH does not make
specific predictions about prosodic variables other than duration. Recent research suggests that
pitch, intensity, and duration may vary independently, and not in service of a single pragmatic
choice like “acoustic prominence” (Lam & Watson, 2010; Watson, 2010; Watson, Arnold, &
Tanenhaus, 2008; for discussion see Arnold & Watson, under review). This speaks against
duration as a categorical phenomenon, but also suggests speakers may perform the processes that
lead to other forms of acoustic variation separately.
At the broadest level, our findings contribute to the characterization of the conditions
under which durational reduction occurs. We have considered two approaches to describing the
psychological mechanisms underlying reduction. While more work is needed, we have
demonstrated that a trigger mechanism, including an explicit representation of discourse status,
may not be necessary to account for some reduction effects. Moreover, a facilitation mechanism
may provide a more robust account. We thus propose that a processing-based facilitation
account may be necessary to supplement, if not supplant, information-status accounts of
durational variation.
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48
Table 1.
Means and SD’s of the durations of each segment from Experiment 1, in milliseconds.
Onset to Speak
Determiner
(the)
Target Word
Action
Word
Linguistic
921 (295)
94 (28)
377 (96)
758 (179)
Nonlinguistic
895 (280)
100 (38)
397 (107)
799 (185)
Control
1278 (469)
102 (35)
414 (108)
783 (172)
PROCESSING-CENTERED REDUCTION
49
Table 2
T-values of the parameter estimates associated with particular variables in the analyses reported
for Experiment 1 for the target (third) instruction. The columns refer to models of individual
segments, and the rows to variables in the analyses. “--“ indicates that the variable was not
included in the final model for that segment. The set of contrasts here compares the linguistic
condition to the other two conditions, and the non-linguistic condition to the control condition.
Trial
Onset to Speak
t = -2.04
Determiner (the)
t = -4.73
Target word
--
Action word
t = -2.0
Imageability
Familiarity
t = 1.83
--
---
-t = 2.04
---
Visual Complexity
Log Frequency
t = -2.39
--
---
-t = -1.75
---
# Object Word
Syllables
--
--
t = 4.5
--
# Action Word
Syllables
Log Onset Duration
t = -7.19
--
t = 3.24
t = 20.59
--
--
--
--
Log the Duration
t = 1.42
--
t = 2.92
--
Log Object Duration
Log Action Duration
-t = -4.68
t = 2.59
t = 1.34
-t = 8.24
t = 7.45
--
Linguistic vs. (Nonlinguistic + Control)
Non-linguistic vs.
Control
t = -7.48
t = 1.23
t = -4.7
t = -1.9
t = 14.49
t = -1.12
t = 3.82
t = -0.59
PROCESSING-CENTERED REDUCTION
50
Table 3
T-values of the parameter estimates associated with particular variables in the analyses reported
for Experiment 1 for the target (third) instruction. The columns refer to models of individual
segments, and the rows to variables in the analyses. “--“ indicates that the variable was not
included in the final model for that segment. The set of contrasts here compares the control
condition to the experimental conditions, and the linguistic condition to the non-linguistic
condition.
Trial
Onset to Speak
t = -2.04
Determiner (the)
t = -4.73
Target word
--
Action word
t = -2.0
Imageability
Familiarity
t = 1.83
--
---
-t = 2.04
---
Visual Complexity
Log Frequency
t = -2.39
--
---
-t = -1.75
---
# Object Word
Syllables
--
--
t = 4.5
--
# Action Word
Syllables
Log Onset Duration
Log the Duration
t = -7.19
--
t = 3.24
t = 20.59
-t = 1.42
---
-t = 2.92
---
Log Object Duration
Log Action Duration
-t = -4.68
t = 2.59
t = 1.34
-t = 8.24
t = 7.45
--
Control vs.
(Linguistic + Nonlinguistic)
Non-linguistic vs.
Control
t = 16.13
t = -2.09
t = 5.63
t = -1.34
t = 0.78
t = 0.51
t = -2.41
t = -1.48
PROCESSING-CENTERED REDUCTION
51
Table 4
Means and standard deviations of the durations of each segment in Experiment 2
Onset to Speak
Determiner (the)
Target word
Action word
Congruent
Incongruent
Congruent
Incongruent
Congruent
Incongruent
Congruent
Incongruent
Linguistic
1548 (750)
1735 (776)
77 (31)
83 (35)
421 (90)
440 (88)
674 (118)
682 (128)
Nonlinguistic
1669 (718)
1764 (767)
84 (55)
88 (43)
442 (89)
445 (92)
691 (138)
686 (151)
52
GIVENNESS AND DURATIONAL REDUCTION
Table 5
T-values of the parameter estimates associated with particular variables in the analyses reported
for Experiment 2. The columns refer to models of individual segments, and the rows to variables
in the analyses. “--“ indicates that the variable was not included in the final model for that
segment.
Onset to speak
Trial
--
Determiner
(the)
t = -2.39
Imageability
--
--
--
--
Familiarity
--
--
t = 3.1
--
Visual
Complexity
--
--
t = 2.72
--
Log Frequency
--
--
t = -2.89
t = 2.21
Log Onset
Duration
Log the Duration
--
t = 1.87
--
t = -9.76
t = 2.9
--
t = -1.47
t = 1.39
--
t = 1.49
--
t = 1.32
t = -9.21
t = 1.61
--
--
t = -1.75
t = -0.95
t = -1.62
t = -0.82
Congruent vs.
Incongruent
t = -4.37
t = -2.8
t = -2.48
t = -2.29
Condition *
Congruence
t = -1.83
t = -0.52
t = -2.37
t = -1.72
Log Object
Duration
Log Action
Duration
Linguistic vs.
Non-linguistic
52
Target word
Action word
--
--
53
GIVENNESS AND DURATIONAL REDUCTION
Figure 1. The stages of speech planning (adapted from Levelt 1989).
53
54
GIVENNESS AND DURATIONAL REDUCTION
Figure 2. An example object array.
54
55
GIVENNESS AND DURATIONAL REDUCTION
Ling
Set 1
Ctrl
Set 2
Nonling
Set 3
Set 1
train
ring
toothbrush
nail
lamp
basket
snake
finger
Set 2
bee
knife
horse
harp
bell
broom
fly
clock
Set 3
shoe
couch
sheep
bow
needle
bus
whistle
deer
Ctrl
Set 1
Nonling
Set 2
Ling
Set 3
Nonling
Set 1
Ling
Set 2
Ctrl
Set 3
Figure 3. An example of the list design in Experiment 1. The three sets of words were
randomized within each condition-set pairing. No condition could appear twice in a row,
and a condition could repeat only after all three conditions had been seen the same
number of times. (Ctrl = control condition, Ling = linguistic condition, Non-ling = nonlinguistic condition)
55
Givenness and Durational Reduction 56
Appendix
accordion, airplane, alligator, anchor, ant, arm, arrow, artichoke, ashtray, asparagus, axe, ball,
balloon, banana, barn, barrel, basket, bat, bear, bed, bee, beetle, bell, belt, bike, bird, blouse,
book, boot, bottle, bowl, box, bow, bread, broom, brush, bus, butterfly, button, cake, camel,
candle, cannon, cap, car, carrot, cat, caterpillar, celery, chain, chair, cherry, chicken, chisel,
church, cigar, cigarette, clock, clothespin, cloud, clown, coat, comb, corn, couch, cow, crown,
cup, deer, desk, dog, doll, donkey, door, doorknob, dress, dresser, drum, duck, eagle, ear,
elephant, envelope, eye, fence, finger, fish, flag, flower, flute, fly, foot, football, fork, fox, frog,
giraffe, glass, glasses, glove, goat, gorilla, grapes, grasshopper, guitar, gun, hair, hammer, hand,
hangar, harp, hat, heart, helicopter, horse, house, iron, jacket, kangaroo, kettle, key, kite, knife,
ladder, lamp, leaf, leg, lemon, leopard, lettuce, lightbulb, lightswitch, lion, lips, lobster, lock,
mitten, monkey, moon, motorcycle, mountain, mouse, mushroom, nail, nailfile, necklace, needle,
nose, nut, onion, orange, ostrich, owl, paintbrush, pan, pants, peach, peacock, peanut, pear, pen,
pencil, penguin, pepper, piano, pig, pineapple, pipe, pitcher, pliers, plug, potato, pumpkin, purse,
rabbit, raccoon, rhinoceros, ring, rollerskate, rooster, ruler, sailboat, salt, sandwich, saw, scissors,
screw, screwdriver, seal, sheep, shirt, shoe, skirt, skunk, sled, snail, snake, snowman, sock,
spider, spool, spoon, squirrel, star, stool, stove, strawberry, suitcase, sun, swan, sweater, swing,
table, telephone, television, thimble, thumb, thumbnail, tie, tiger, toaster, tomato, toothbrush, top,
train, trashcan, tree, truck, trumpet, turtle, umbrella, urn, vest, violin, wagon, watch, watermelon,
well, wheel, whistle, windmill, window, wrench, zebra
56