Perceptual uniqueness point effects in monitoring internal speech

Özdemir, Rebecca; Roelofs, Ardi; Levelt, Willem J. M.

doi:10.1016/j.cognition.2006.10.006

Cited by 55 publications

(61 citation statements)

References 10 publications

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“…Such a prediction may be achieved by tacitly naming the adequate sentencefinal word. Subsequently, activated phonological segments may crossover to the comprehension system via the internal monitoring loop (Özdemir, Roelofs, and Levelt, 2007). This benefit in lexical processing might reflect facilitated lexical access (Besson et al, 1992;Rugg, 1990) or be an instance of rhyme priming (Praamstra et al, 1994;Radeau, Besson, Fonteneau, and Castro, 1998).…”

Section: Discussionmentioning

confidence: 99%

Event-related brain potentials during the monitoring of speech errors

et al. 2009

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a b s t r a c t a r t i c l e i n f oWhen we perceive speech, our goal is to extract the meaning of the verbal message which includes semantic processing. However, how deeply do we process speech in different situations? In two experiments, native Dutch participants heard spoken sentences describing simultaneously presented pictures. Sentences either correctly described the pictures or contained an anomalous final word (i.e. a semantically or phonologically incongruent word). In the first experiment, spoken sentences were task-irrelevant and both anomalous conditions elicited similar centro-parietal N400s that were larger in amplitude than the N400 for the correct condition. In the second experiment, we ensured that participants processed the same stimuli semantically. In an early time window, we found similar phonological mismatch negativities for both anomalous conditions compared to the correct condition. These negativities were followed by an N400 that was larger for semantic than phonological errors. Together, these data suggest that we process speech semantically, even if the speech is task-irrelevant. Once listeners allocate more cognitive resources to the processing of speech, we suggest that they make predictions for upcoming words, presumably by means of the production system and an internal monitoring loop, to facilitate lexical processing of the perceived speech.

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Section: Discussionmentioning

confidence: 99%

Event-related brain potentials during the monitoring of speech errors

et al. 2009

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“…Although the literature is divided on the precise error detection mechanisms (e.g., Huettig & Hartsuiker, 2010;Ozdemir, Roelofs, & Levelt, 2007) there is a consensus that people monitor not only their overt speech but also a representation of pre-articulatory speech. First, some speech errors are intercepted too fast (i.e., within 150ms) to be based on overt speech (e.g., Blackmer & Mitton, 1991).…”

Section: Speech Monitoringmentioning

confidence: 99%

Lexical selection and verbal self-monitoring: Effects of lexicality, context, and time pressure in picture-word interference

Dhooge

Hartsuiker

2012

Journal of Memory and Language

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Current views of lexical selection in language production differ in whether they assume lexical selection by competition or not. To account for recent data with the picture-word interference (PWI) task, both views need to be supplemented with assumptions about the control processes that block distractor naming. In this paper, we propose that such control is achieved by the verbal self-monitor. If monitoring is involved in the PWI task, performance in this task should be affected by variables that influence monitoring such as lexicality, lexicality of context, and time pressure. Indeed, pictures were named more quickly when the distractor was a pseudoword than a word (Experiment 1), which reversed in a context of pseudoword items (Experiment 3). Additionally, under time pressure, participants frequently named the distractor instead of the picture, suggesting that the monitor failed to exclude the distractor response. Such errors occurred more often with word than pseudoword distractors (Experiment 2); however, the effect flipped around in a pseudoword context (Experiment 4). Our findings argue for the role of the monitoring system in lexical selection. Implications for competitive and non-competitive models are discussed.

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“…For example, the presence of a uniqueness point 1 or 2 phonemes before word-final phonemes may have accelerated identification of word-final sounds (i.e., C 4 ) for AWNS in previous phoneme-monitoring studies in a manner similar to Ozdemir et al [33]. If preverbal monitoring deficits were present in AWS, however, participants may have been slower to detect, or benefit from, uniqueness points and, consequently, may have identified C 4 targets more slowly than AWNS.…”

Section: Uniqueness Point Effectsmentioning

confidence: 82%

“…To more directly assess the claim of Levelt et al [29] that the comprehension system governs the preverbal speech monitor, Ozdemir et al [33] examined whether uniqueness point effects were also observed during a silent phoneme monitoring task. In their study, Dutch-speaking adults ( n = 32) were instructed to press a button as quickly as possible if the name of the pictured object contained the target phoneme.…”

Section: Uniqueness Point Effectsmentioning

confidence: 99%

“…One method of measuring monitor function is assessment of uniqueness point effects during silent monitoring. Ozdemir et al [33] found that AWNS monitor phonemes located after the uniqueness point of a word – the first phoneme that isolates the word from all lexical competitors – faster than phonemes located before this critical phoneme. The uniqueness point effect was interpreted by these authors to reflect a perceptual-based phenomenon observed when monitoring both internal and external speech and therefore linked to the function of the preverbal monitor.…”

Section: Introductionmentioning

confidence: 99%

See 1 more Smart Citation

Uniqueness Point Effects during Speech Planning in Adults Who Do and Do Not Stutter

Coalson

Byrd

Kuylen

2017

Folia Phoniatr Logop

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Background/Aims: Previous studies employing a variety of tasks have demonstrated that adults who stutter (AWS) present with phonological encoding differences compared to adults who do not stutter (AWNS). The present study examined whether atypical preverbal monitoring also influenced AWS performance during one such paradigm – the silent phoneme monitoring task. Specifically, we investigated whether monitoring latencies for AWS were accelerated after the word’s uniqueness point – the phoneme that isolates the word from all lexical competitors – as observed for AWNS when monitoring internal and external speech. Methods: Twenty adults (10 AWS, 10 AWNS) completed a silent phoneme monitoring task using stimuli which contained either (a) early uniqueness points (EUP), (b) late uniqueness points, or (c) no uniqueness point (NUP). Response latency when identifying word-final phonemes was measured. Results: AWNS exhibited the expected uniqueness point effect when monitoring internal speech; word-final phonemes were accessed more rapidly for words with EUP than NUP. In contrast, AWS did not differ in the phoneme monitoring speed. That is, AWS did not exhibit the expected uniqueness point effects. Conclusion: Findings suggest that inefficient or atypical preverbal monitoring may be present in AWS and support theories that implicate the internal speech monitor as an area of deficit.

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Perceptual uniqueness point effects in monitoring internal speech

Cited by 55 publications

References 10 publications

Event-related brain potentials during the monitoring of speech errors

Event-related brain potentials during the monitoring of speech errors

Lexical selection and verbal self-monitoring: Effects of lexicality, context, and time pressure in picture-word interference

Uniqueness Point Effects during Speech Planning in Adults Who Do and Do Not Stutter

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