Serial Control of Phonology in Speech Production: A Hierarchical Model

Vousden, Janet; Brown, Gordon D.; Harley, Trevor A.

doi:10.1006/cogp.2000.0739

Cited by 134 publications

(171 citation statements)

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“…Evidence that the segment size units are coded independent of syllable position comes from swaps in non-corresponding syllable positions. For example, Vousden, Brown and Harley (2000) found that more than 20% of relevant phonological errors involved changes across syllable positions (e.g., film mispronounced as flim).…”

Section: Empirical Evidence For Phonemes In Speech Productionmentioning

confidence: 99%

Spoken word identification involves accessing position invariant phoneme representations

Bowers

Kazanina

Andermane

2016

Journal of Memory and Language

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Abstract:In two adaptation experiments we investigated the role of phonemes in speech perception. Participants repeatedly categorized an ambiguous test word that started with a blended /f/-/s/ fricative (?ail can be perceived as /fail/ or /sail/) or a blended /d/-/b/ stop (?ump can be perceived as /bump/ or /dump/) after exposure to a set of adaptor words. The adaptors all included unambiguous /f/ or /s/ fricatives, or alternatively, /d/ or /b/ stops. In Experiment 1 we manipulated the position of the adaptor phonemes so that they occurred at the start of the word (e.g., farm), at the start of the second syllable (e.g., tofu), or the end of the word (e.g., leaf). We found that adaptation effects occurred across positions: Participants were less likely to categorize the ambiguous test stimulus as if it contained the adapted phoneme. For example, after exposure to the adaptors leaf, golf... etc., participants were more likely to categorize the ambiguous test word ?ail as 'sail'. In Experiment 2 we also varied the voice of the speaker: Words with unambiguous final phoneme adaptors were spoken by a female while the ambiguous initial test phonemes were spoken by a male.Again robust adaptation effects occurred. Critically, in both experiments, similar adaptation effects were obtained for the fricatives and stops despite the fact that the acoustics of stops vary more as a function of position. We take these findings to support the claim that position independent phonemes play a role in spoken word identification. 3Traditional linguistic theory postulates a small set of phonemes that can be sequenced in various ways in order to represent thousands of words in a language (Chomsky & Halle, 1968;Trubetzkoy, 1969). Phonemes are the smallest linguistic unit that can distinguish word meanings and usually are of a size of a single consonant or vowel, e.g., the consonants /b/ and /p/ are phonemes in English because they differentiate the words "bark" and "park". Phonemes are critically distinguished from speech sounds (i.e. phones) in their level of abstractness. Phones are acoustically defined units that are often context-dependent, i.e. in a given language a certain phone may be bound to a specific syllable position, or require a certain stress pattern, or occur within the context of specific surrounding sounds. Although phonemes are widely assumed in linguistic theory, the psychological evidence in support of phonemes, at least in the domain of speech perception, is scant.This has given rise to various models that abandon phonemes as a functional unit in are used to activate dog and god representations, respectively. These time-bound segments can be seen as analogous to Pierrehumbert's position-specific phones (in that the segments do not abstract across position) although the input units in these models are often labeled phonemes.The common rejection of position invariant phonemes in psychological theories and models of word perception is a fundamental claim, and we explore this issue here. First we review the current empir...

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Section: Empirical Evidence For Phonemes In Speech Productionmentioning

confidence: 99%

Spoken word identification involves accessing position invariant phoneme representations

Bowers

Kazanina

Andermane

2016

Journal of Memory and Language

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“…Brown, Preece, & Hulme, 2000;Burgess & Hitch, 1999;Henson, 1998;Page & Norris, 1998a). To this end, we feel that a recent redefinition of the "phonological loop" as a lexical-level utterance plan (Page et al, 2007) serves as a very useful place from which production researchers might incorporate theoretical and computational ideas from the working memory domain (see Vousden, Brown, & Harley, 2000 for one such example). Some possibilities include developing a model of multi-word utterances in message-driven production by setting up a fast-decaying primacy gradient (Page & Norris, 1998a), and investigating whether mechanism such as competitive queuing (e.g.…”

Section: Implications Of the Language Production Hypothesismentioning

confidence: 99%

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

Acheson

MacDonald

2009

Journal of Memory and Language

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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.

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“…This was motivated by evidence for inhibition of return in visuospatial search tasks (Posner, Rafal, Choate, & Vaughan, 1985) and response suppression in serial recall tasks (e.g., Lewandowsky & Duncan, 2002;Vousden & Brown, 1998). Response suppression has been incorporated in nearly all models of serial recall and serial response generation (e.g., Farrell & Lewandowsky, 2002;Brown et al, 2000;Vousden, Brown, & Harley, 2000;Burgess & Hitch, 1999;Henson, 1998;Page & Norris, 1998;Houghton & Hartley, 1996;Lewandowsky & Murdock, 1989). The fast bias and responsesuppression mechanisms allowed the model to develop temporally persistent mnemonic cues in the PFC layer, while permitting a range of different responses to the same mnemonic cue, without response perseveration.…”

Section: Introductionmentioning

confidence: 99%

A Computational Model of Prefrontal Control in Free Recall: Strategic Memory Use in the California Verbal Learning Task

Becker

Lim

2003

Journal of Cognitive Neuroscience

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Abstract& Several decades of research into the function of the frontal lobes in brain-damaged patients, and more recently in intact individuals using function brain imaging, has delineated the complex executive functions of the frontal cortex. And yet, the mechanisms by which the brain achieves these functions remain poorly understood. Here, we present a computational model of the role of the prefrontal cortex (PFC) in controlled memory use that may help to shed light on the mechanisms underlying one aspect of frontal control: the development and deployment of recall strategies. The model accounts for interactions between the PFC and medial temporal lobe in strategic memory use. The PFC self-organizes its own mnemonic codes using internally derived performance measures. These mnemonic codes serve as retrieval cues by biasing retrieval in the medial temporal lobe memory system. We present data from three simulation experiments that demonstrate strategic encoding and retrieval in the free recall of categorized lists of words. Experiment 1 compares the performance of the model with two control networks to evaluate the contribution of various components of the model. Experiment 2 compares the performance of normal and frontally lesioned models to data from several studies using frontally intact and frontally lesioned individuals, as well as normal, healthy individuals under conditions of divided attention. Experiment 3 compares the model's performance on the recall of blocked and unblocked categorized lists of words to data from Stuss et al. (1994) for individuals with control and frontal lobe lesions. Overall, our model captures a number of aspects of human performance on free recall tasks: an increase in total words recalled and in semantic clustering scores across trials, superiority on blocked lists of related items compared to unblocked lists of related items, and similar patterns of performance across trials in the normal and frontally lesioned models, with poorer overall performance of the lesioned models on all measures. The model also has a number of shortcomings, in light of which we suggest extensions to the model that would enable more sophisticated forms of strategic control. &

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Serial Control of Phonology in Speech Production: A Hierarchical Model

Cited by 134 publications

References 74 publications

Spoken word identification involves accessing position invariant phoneme representations

Spoken word identification involves accessing position invariant phoneme representations

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

A Computational Model of Prefrontal Control in Free Recall: Strategic Memory Use in the California Verbal Learning Task

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