Twisting tongues and memories: Explorations of the relationship between language production and verbal working memory

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Abstract

Many accounts of working memory posit specialized storage mechanisms for the maintenance of serial order. We explore an alternative, that maintenance is achieved through temporary activation in the language production architecture. Four experiments examined the extent to which the phonological similarity effect can be explained as a sublexical speech error. Phonologically similar nonword stimuli were ordered to create tongue twister or control materials used in four tasks: reading aloud, immediate spoken recall, immediate typed recall, and serial recognition. Dependent measures from working memory (recall accuracy) and language production (speech errors) fields were used. Even though lists were identical except for item order, robust effects of tongue twisters were observed. Speech error analyses showed that errors were better described as phoneme rather than item ordering errors. The distribution of speech errors was comparable across all experiments and exhibited syllable-position effects, suggesting an important role for production processes. Implications for working memory and language production are discussed.

Introduction

Verbal working memory, the temporary maintenance and processing of verbal information, has long been viewed as an important component to word learning (Gathercole and Baddeley, 1989, Gathercole and Baddeley, 1990) and language comprehension (Daneman & Carpenter, 1980). The relationship between working memory and language production has received far less attention, despite the fact that recall of verbal material requires language production (although see Bock, 1996, Ellis, 1980, Jacquemot and Scott, 2006, Jones et al., 2004, Page et al., 2007, Treiman and Danis, 1988). The production-working memory relationship was explored in a recent review by Acheson and MacDonald (2009), who argued that the mechanism for maintaining serial order in verbal working memory may emerge from the language production architecture (hereafter the language production hypothesis). In the present study, we investigate this hypothesis in studies of working memory performance, using analytic techniques and behavioral manipulations more typical of language production researchers.

Many researchers’ views of the architecture underlying working memory have been shaped by the multi-component model (Baddeley, 1986, Baddeley and Hitch, 1974), in which an attentional control mechanism termed the central executive oversees the functioning of two slave systems responsible for the temporary maintenance of verbal (the phonological loop) and visual (the visuospatial sketchpad) information. The phonological loop component of the model is in turn composed of a temporary phonological store whose contents decay with time unless refreshed via an articulatory control process. A number of key phenomena have been used to support the phonological loop concept, among them effects of phonological similarity (Conrad, 1964, Conrad and Hull, 1964, Wickelgren, 1965), word length (Baddeley, Thomson, & Buchanan, 1975), irrelevant sound (Colle and Welsh, 1976, Salame and Baddeley, 1982), and concurrent articulation (Baddeley et al., 1984, Levy, 1971, Murray, 1968). On this view, while participants must engage in language production to complete the recall task, an independent storage mechanism is responsible for memory maintenance.

One challenge to language-independent, short-term storage comes from findings that show the influence of long-term, linguistic knowledge on putatively short-term recall. For example, words are easier to recall than nonwords (Hulme, Maughan, & Brown, 1991), and high frequency words are easier to recall than low frequency ones (Roodenrys, Hulme, Lethbridge, Hinton, & Nimmo, 2002). Similarly, concrete words are easier to recall than abstract words (Walker & Hulme, 1999). In addition to these lexical or semantic influences, long-term phonological knowledge affects working memory performance: Nonwords with higher phonotactic probabilities (i.e., having higher frequency phonemes in higher frequency combinations) are easier to recall than those with lower phonotactic probabilities (Gathercole, Frankish, Pickering, & Peaker, 1999), and nonwords from more dense phonological neighborhoods (those with more phonologically related words in the language) are recalled better than those from sparse neighborhoods (Roodenrys & Hinton, 2002).

These studies suggest a system which, at the very least, uses linguistic representation that has been acquired over a lifetime to constrain performance on recall tasks. The idea that long-term, linguistic knowledge influences and should be incorporated into accounts of verbal working memory is not a new one (see Allport, 1984, Ellis, 1980, Gupta and MacWhinney, 1997, Hartley and Houghton, 1996). Researchers have used one of the classic findings in verbal working memory, the phonological similarity effect, as a means of testing the functional relationships between language and working memory (Nimmo & Roodenrys, 2004). Past research has demonstrated that memory for the order of items sharing phonological features is worse than items which do not share these features, although nonordered memory for the items themselves is generally not affected or may be enhanced (Fallon et al., 1999, Gupta et al., 2005, Nimmo and Roodenrys, 2004). Critical to the present study, the location of the feature overlap influences people’s performance. Both Nimmo and Roodenrys (2004) and Gupta et al. (2005) demonstrated that relative to nonoverlapping lists, when phonological overlap occurs within the rhyme unit of a syllable (e.g. the /æt/ sound in the list cat, bat, hat, etc.), people’s memory for the order of the stimuli is impaired while their memory for the stimuli improves. When stimuli share the same initial consonant and vowel (e.g. sane, safe, sake, etc.) or the same initial and final consonants (e.g. bought, bet, boot, etc.), people demonstrate impairments in both item and order memory (Nimmo & Roodenrys, 2004). These studies thus support claims for a role of long-term knowledge in immediate recall by demonstrating that the linguistic structure of the material (in this case, the syllabic structure), is central to how manipulations of phonological similarity affect performance.

Using manipulations of phonological similarity to examine linguistic structure can be difficult, however, as the stimuli used can create an ambiguity in interpreting the linguistic level over which errors are occurring. For example, in the case of serial recall of a sequence of phonologically similar letters (C, B, P, D, etc.), ordering errors can be interpreted as occurring at the level of whole lexical items (e.g., C, P, B, D), but they also can be interpreted at the sublexical level, as exchanging of the /b/ and /p/ phonemes in the planned utterance will also result in the C P B D error (see Page & Norris, 1998b, for a similar discussion). Analysis of naturally occurring speech errors suggests that ordering effects due to phonological similarity are not mis-orderings of whole words but are more likely have a sublexical source, reflecting errors in phonemes across the same syllable position in different items (Dell, 1984, Shattuck-Hufnagel, 1979). Page et al. (2007) investigated sub-lexical errors in recall using “spoonerized” lures. Spoonerisms occur when an exchange of speech sounds between two words results in the production of real words (e.g., “you’ve hissed my mystery lecture” instead of “you’ve missed my history lecture;” MacKay, 1970). Thus, when people do make speech errors with such stimuli, there is no ambiguity as to the unit over which the errors is occurring as the error results in the production of an unintended word. Using such lures in a serial recall task, Page et al. (2007) demonstrated that people produced many more errors when the two lures were adjacent to each other than when they were not. The authors concluded that errors due to phonological similarity (in this case, an exchange of speech onsets) likely reflect errors within the speech production system.

In this paper, we hypothesize that viewing the maintenance of serial order information in verbal working memory tasks as a slightly idiosyncratic language processing task can provide insight into working memory processes. Although this view is consistent with recent approaches suggesting that verbal working memory performance is closely linked to language production (Jacquemot and Scott, 2006, Saito and Baddeley, 2004), it differs in that these researchers have assumed “buffers” that are specifically dedicated to short-term maintenance. Alternatively, Page et al. (2007) recently suggested that what has been termed the “phonological loop” can be likened to a list wise, lexical-level production plan. In this account, serial recall amounts to a speech “reproduction” task, and differs from typical production as the source of this plan is not internally generated. This view is quite similar to ours in suggesting that verbal working memory maintenance occurs by maintaining activation over the same levels of representation responsible for normal production, although our emphasis in the present research is at a sublexical level.

Language production researchers have posited a number of subprocesses that are executed in the course of language planning and production. Two of them seem highly relevant to maintaining and recalling an ordered sequence of lexical and sublexical phonological representations. These processes are lexical retrieval and phonological encoding, in which a to-be-uttered word is translated into a sequence of phonemes prior to articulation (Dell, 1986, Garrett, 1975, Shattuck-Hufnagel, 1979). The term lexical, as it is used here and throughout, does not necessarily refer to a word with its associated semantics, but rather, to a whole phonological representation. In this sense, a lexical–phonological representation is dissociable from sublexical representations (e.g. phonemes, phonetic features, etc.). Both lexical and sublexical effects have been analyzed in corpora of naturally occurring speech errors. Such analyses have provided important empirical evidence about the nature of production processes, including phonological encoding (Fromkin, 1971, Nooteboom, 1969, Shattuck-Hufnagel, 1979), and yield several phenomena that bear a strong resemblance to classic effects in verbal working memory (see Acheson & MacDonald, 2009). If the language production hypothesis is correct, then use of speech error analyses in the context of verbal working memory tasks such as serial recall should reveal important insight into people’s performance.

To date, only two attempts have been made to incorporate speech error analyses into serial recall performance. Ellis (1980) examined the extent to which errors in serial recall obey those in normal speech production and demonstrated that errors are more likely to occur between speech elements which share more similar phonetic features (also see Wickelgren, 1965); that errors between consonants are more common than errors between vowels; and that speech sounds are more likely to exchange with each other when they occur within the same syllable position. Treiman and Danis (1988) also examined the extent to which errors in serial recall abided by syllable structure in CVC, CCV and VCC syllables. Across three studies, errors occurred primarily between speech sounds within a list, and they tended to maintain the onset-rhyme distinction within the syllable structure. Thus, errors in verbal working memory abide by what production researchers have called the syllable-position constraint (Dell, 1986). Although both the Ellis (1980) and Treiman and Danis (1988) studies were an important first step in demonstrating the utility of speech error analyses serial recall performance, they lacked the depth of detail typically presented in analyses of naturally occurring speech errors, and they did not include a nonmemory baseline condition.

Our studies expand upon previous research by systematically analyzing the types and distribution of speech errors across items and syllable positions. Such an analysis will, for the first time, provide a detailed taxonomy of the types of errors induced by phonological similarity in memory tasks. The following terminology will be used in this investigation. The level over which an error is occurring (e.g. phoneme, syllable, word) is called the segment. Within a given syllable (e.g. mip), segments are divided into the initial consonant or consonant cluster (the onset), the middle vowel, and the last consonant(s) (the coda, also called the offset), where the combination of these last two segments is termed the rhyme. We will refer to our stimulus nonwords as items to be produced or remembered, so that phonemes, onsets, etc. are components of our stimulus items.

We investigate the sublexical nature of phonological similarity by examining the types of errors people make when producing and remembering tongue twister stimuli. Tongue twisters such as she sells sea shells by the seashore are known to produce serial ordering errors both in the process of phonological encoding and in articulation itself (Wilshire, 1999). What often defines a tongue twister is the complex alternation of onset and rhyme coupled with phonetic feature similarity in the onset syllable position. In the example above, the onsets phonemes follow an ABBA pattern (/∫/ /s/ s/ /∫/) while the rhymes follow an ABAB pattern (/i/ /εl/ /i/ /εl/). The logic of using such stimuli is threefold. First, there is general agreement in the production area that tongue twisters primarily elicit phoneme and not whole item errors (Wilshire, 1999). Second, comparisons can be made across stimuli matched for overall phonological overlap, as the same stimuli appear in different orders across tongue twister conditions. Most would agree that a list of more difficult-to-produce stimuli should be harder to recall. However, beyond suggesting that tongue twister lists simply take longer to rehearse (and hence suffer more decay), it is not clear how models of working memory that do not take into account sublexical linguistic structure would account for tongue twister effects. The language production hypothesis, on the other hand, makes explicit why tongue twisters are difficult, as such ordering causes difficulty during phonological encoding. Third, although phoneme errors often result in exchanges between stimuli (e.g. she shells sea sells), they also result in repetition of the same item (e.g. she shells sea shells). Item repetitions within a list are very rare in serial recall (Henson, 1998), and this outcome is explicitly built in to many computational models in the form of post-output suppression of entire items (e.g. Burgess and Hitch, 1999, Henson, 1998). Given these mechanisms, item repetition simply should not occur in the list lengths used in this study. In the language production hypothesis, however, item repetition is easily accommodated as a phoneme repetition. Our point is not to argue that item-level maintenance does not occur, nor that post-output suppression of previously spoken material is wrong (quite simply, it can’t be). Rather, we argue that the most likely source of an item repetition in tongue twisters is in the repetition of individual phonemes rather than a failure in post-output suppression of an entire item, thus suggesting an important role for sublexical, phonological encoding.

Tongue twisters have been employed in verbal working memory tasks before (e.g. Saito & Baddeley, 2004); however, researchers have not conducted the detailed error analysis provided here. This type of analysis is capable of detecting long-term constraints on the production architecture that may be present in verbal working memory tasks. Furthermore, we manipulate the mnemonic demands in the task by having individuals produce (Experiment 1) and remember (Experiments 2–4) lists of nonwords. Nonwords were chosen as stimuli, as their structure can be tightly controlled within and across lists, and they necessarily lack semantic content, thus influences of semantic processes on serial ordering can be avoided. Unlike in previous studies, the use of a simple production task in Experiment 1 provides a baseline of performance for the following experiments in which participants perform immediate spoken (Experiment 2) or typed (Experiment 3) recall, or serial recognition (Experiment 4).

Drawing on previous research on experimentally-induced and naturally occurring speech errors, the language production hypothesis makes three specific predictions about task performance. First, tongue twister orders should be harder to recall than non-tongue twister orders due to errors in phonological encoding processes. Second, analyses should reveal similar distributions of speech errors across serial recall and production of tongue twister sequences. In the case of phonological encoding, five basic error types have been classified in the speech error literature: substitutions, exchanges, shifts, additions and omissions (Fromkin, 1971, Garrett, 1975, Nooteboom, 1969, Shattuck-Hufnagel, 1979; examples are provided in Appendix A). Given that nature of the stimuli, the primary error we predict is a contextual substitution (Wilshire, 1999), in which a target segment (the element that was intended to be uttered) is replaced by an intruding segment from elsewhere in the utterance. Third, we predict that errors due to phonological similarity reflect phoneme ordering, not errors in ordering whole items, thus phoneme substitutions will result in repetition of the same items due to perseveration (i.e., repetition of material already spoken) or anticipation (i.e. production of upcoming material) of phonemes within the list. Finally, the distribution of phoneme errors across syllables should reflect structural and distributional constraints on the production system. Thus, phoneme substitution errors should abide by syllable-position constraints, and the majority of these errors should occur at the onset consonant(s) (Shattuck-Hufnagel, Keller, & Gopnik, 1987).

Section snippets

Experiment 1: rapid, paced reading of tongue twisters

Before we embark on analysis of speech errors in the context of verbal working memory tasks, it is useful to have a nonmemory baseline measure of production errors for the same items that will be used in the memory studies. We therefore developed a list of items that would be likely to induce speech errors and instructed producers to read each list of items repeatedly in a rapid, paced manner. Such a technique has been shown to produce speech errors reliably in tongue twister lists (Wilshire,

Results

The types of speech error observed were commensurate with our predictions about tongue twisters in speech production. Tongue twister orders produce more errors than non-tongue twister orders; errors were primarily contextual and the distribution of these errors abided by syllable-position constraints. Results presented were consistent across the lists used between participants.

Participants

Thirty-four native English speakers (18 female) participated in this study for credit in an introductory psychology class at the University of Wisconsin, Madison. Their age ranged from 18 to 20 (M = 18.8, SD = 0.56). All had normal or corrected-to-normal vision. Due to malfunctions in recording equipment, data from four participants were lost.

Materials

Materials were the same as in Experiment 1.

Procedure

Participants read the lists of nonwords on a computer screen, which were presented in white font on a black

Experiment 3: immediate serial recall of tongue twisters – typed response

In this experiment, articulatory demands were changed and reduced by having participants type their responses instead of speaking them. Typing, like speaking, is a motor response, but similarities among phonemes are not maintained in the typing modality. For example, the phonemes /p/ and /b/ are highly similar acoustically and are spoken with similar speech gestures, but the letters p and b require very different motor plans to type them on a keyboard. If the effects in Experiment 2 were purely

Participants

Twenty native English speakers (13 female) participated in this study for credit in an introductory psychology class at the University of Wisconsin, Madison. Their age ranged from 18 to 28 (M = 20.6, SD = 2.5). All had normal or corrected-to-normal vision.

Materials

Materials were generated in the same way as in Experiment 1. Given the need to probe a sufficient number of yes/no responses for each serial position in this recognition task, more items were generated. In addition to the 28 lists used in the

General discussion

The four experiments presented here examined the extent to which serial ordering in verbal working memory relies on the language production architecture. Serial ordering demands were manipulated through use of nonword lists that differed only in the order of items across tongue twister and non-tongue twister conditions. Both mnemonic and output demands were manipulated across experiments to examine the extent to which these factors affected performance. Comparisons across production and working

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