Previous Research on Phonological Encoding in Fluency Disorders Phonological encoding entails the assignment of speech segments to their

sequential timing slots (Levelt, Roelefs, & Meyer, 1999). According to Levelt’s

incremental speech planning model, the phonological code produced during phonological encoding is subject to the speaker’s internal speech monitor. Although phonological encoding has not yet been investigated in PWC directly, previous research suggests that

Howell, 2002; See also Chapter 1 for a detailed review of such research in stuttering). Of particular interest to the present study, Sasisekaran et al. (2006) and Sasisekaran and De Nil (2006) investigated phonological encoding during covert (silent) speech production with a phoneme monitoring task. Results indicated that PWS were significantly slower than controls when monitoring for phonemes, but not during auditory tone monitoring or during simple motor tasks, suggesting specific problems with the selection of

phonological segments during encoding, or alternatively, with the monitoring of the pre- articulatory speech plan, which is also used to detect errors. An alternative interpretation is that PWS have difficulties assembling the phonemes into the phonological code, rather than the selection of the phonemes themselves, that is, something goes awry during serial ordering and creation of the phonological code, even though the correct phonemes have been selected. Given these various interpretations, the need to provide further empirical data to support or refute such speculation, and the fact that phonological difficulties may be shared by both PWS and PWC motivated the further exploration of this area of investigation.

Specifically, Experiment 1 aimed to extend the methodology of Sasisekaran et al. (2006) to study phonological encoding in cluttering, to investigate whether the

phonological manipulation abilities of PWC differ from PWS and (TFA) using a phoneme monitoring task. This covert speech task requires completion of the

phonological encoding step and invokes the internal speech monitor, as participants must silently scan the phonological code to decide if a sound is present. The task employed in the Experiment 1 assessed phonological encoding through a monitoring task, and

syllabified phonological code. Wheeldon and Levelt (1995) found that covert-speech monitoring was affected by syllabic structure, and argue that it is the phonological output

(prior to articulation) that is being monitored, rather than segmental spell-out, which is not syllabified, according to the Levelt model. They also argue that it is not the phonetic plan that is monitored, as participants were still able to monitor during articulatory suppression (i.e., placement of a device preventing movement of the articulators).

Phonological encoding abilities will be examined in Experiment 1 with regard to both accuracy and reaction time. First, errors may be due to incorrect phonological encoding (assuming correct lexical retrieval), or due to inaccurate monitoring. If the speech output patterns of PWC reflect deficient phonological encoding and/or pre- articulatory monitoring abilities, these speakers are expected to be more error-prone than TFA on a phoneme monitoring task. There is a possibility that requiring PWC to monitor would reduce the probability of their errors, but it was assumed that if PWC are forced to use their internal speech monitor that is deficient in some way, this will likely still lead to errors. While the presence of errors alone in this covert speech monitoring task would not provide direct information regarding the specific level of deficit, their presence would indicate subtle underlying issues in utterance preparation that are unrelated to the overt articulation act itself. Such a finding would contribute to the sparse existing literature on linguistic aspects of speech planning in cluttering, and provide a basis for further

hypothesis development and testing.

The potential effects of a hypothesized hypomonitoring deficit on reaction time (RT) are less straightforward; however, at least three potential outcomes may be possible.

be expected to show faster RTs during phoneme monitoring, as the output of the

phonological-encoding step will be available for monitoring sooner. A second possibility, however, is that if the internal monitoring step is normally absent or compromised in PWC, there would be little reason to expect faster times when they are forced to

deliberately monitor the internal speech plan in an experimental task. In fact, this might even result in increased RTs on a task designed specifically to invoke the monitor, as the speech planning system is not accustomed to such deliberate monitoring, possibly resulting in slower responding. Third, if the level of deficit in cluttering is further along in the speech production process, for example, at the level of the phonological buffer or even motor execution, performance on a covert phoneme monitoring task should not differ from that of TFA either in terms of accuracy or RT.

In summary, if one important contributor to cluttering is a hypomonitoring deficit, then PWC should be less able than other speakers to ‘catch’ and repair phonological- encoding errors pre-articulatorily. If this is the case, it was predicted that PWC would show higher error rates on a silent-speech monitoring task than TFA, and RT data will shed light on the level of deficit as well.

Finally, although the primary focus of Experiment 1 is on cluttering, it is also a partial replication of a study on stuttering by Sasisekaran et al. (2006), who found that PWS showed normal accuracy but slower RTs than TFA, suggesting hypermonitoring in PWS (i.e., more time spent monitoring, slower response/reaction time). A group of PWS was included to validate the present results against those of this previous study, and to serve as pilot data for Experiments 2 and 3 in Chapter 3. Therefore, comparisons will be made between all three groups of participants.

2.2. Methods and Materials