10 likes | 227 Views
**. ns. **. **. *. ns. **. *. *. ns. *. METHODS. Results: Ex. 2. ABSTRACT. Results: Ex. 1. THE SELF-SELECT SPEECH PARADIGM AND KLAPP’S MODEL. THEORETICAL BASIS. PREDICTIONS. INT Complexity. INT Complexity. CV ta. CC(C)V stra. 150 ms. 450 ms. Simple. Simple.
E N D
** ns ** ** * ns ** * * ns * METHODS Results: Ex. 2 ABSTRACT Results: Ex. 1 THE SELF-SELECT SPEECH PARADIGM AND KLAPP’S MODEL THEORETICAL BASIS PREDICTIONS INT Complexity INT Complexity CV ta CC(C)V stra 150 ms 450 ms Simple Simple SEQ Complexity SEQ Complexity 150-450-450-150 450-150-150-450 Complex Complex CV repeat ta-ta-ta-ta CC(C)V repeat stra-stra-stra-stra CC(C)V different ta-stra-ru-ta Simple Complex Simple Complex Complex Motor programming for speech sequencesRhee, J., Vaculin, A., & Wright, D.L. Human Performance Laboratory, Department of Health and Kinesiology, Texas A&M University. Klapp (1995) argues that motor programming (MP) involves two processes: INT and SEQ. The INT process has been reported to be sensitive to the duration of the programmed unit, while SEQ is related to the number of units that must be programmed in a sequence. Experiment 1 considered whether the duration of spoken syllables (e.g., /ba/) impacts INT. Twelve individuals articulated monosyllabic and multi-syllabic sequences. Study time (ST), reaction time (RT), and total duration for each syllable were recorded. A sequence length effect (SEQ) was present for RT but the demands of INT, reflected in ST, were quite small and non-significant in the case of monosyllabic responses. These data suggest that the duration of the syllable have little effect on MP during speech. A second experiment evaluated the impact on INT and SEQ for syllable complexity manipulations based on voicing and manner of production. The latter features of speech production were central to recent studies examining MP during speech (e.g., Bohland & Guenther, 2006). Both the expected SEQ, in the form of a sequence length effect for RT, and INT, larger impact on ST for more complex sequences, were present. a a d b e b c f c Figure 1. The self-select paradigm separately assesses the impact of the INT and SEQ processes in Klapp’s (1995) model. A trial begins with the “ready” signal being presented. Shortly after, the individual is provided a precue revealing the speech sequence that should be readied. Study time (ST) is defined as the interval between the presentation of a precue informing the participant of the nature of the upcoming responses and the participant indicating they are ready (e.g., left-clicking” a mouse). This interval is assumed to be sensitive to changes in features influencing the INT motor programming process. Following the execution of the mouse click a variable fore-period occurs prior to the presentation of the “GO” signal. RT is defined as the interval between the presentation of the “GO” signal and initial articulation of the first syllable. Initial articulation was defined as in Zeigler & Deger (2001) as the 30% min-to-max threshold of the rising SPL-contour. The RT interval is assumed to be sensitive to changes in the demands of SEQ. Figure 4a-f. Figure 4a indicates that the mono-syllabic utterances were articulated with a similar overall duration. Despite this, the simple mono-syllabic utterance was associated with greater ST indicative of a larger INT demand (Figure 4b). As anticipated, utterances involving only one syllable have similar RT suggesting SEQ demands were similar (Figure 4c). When comparing the mono- and multi-syllabic utterances (left panel) there was the expected sequence length effect for RT because of the necessary increase in involvement of SEQ to maintain serial order (Figure 4f). Interestingly, there is a further increase in RT when planning different syllables rather than repeats. This suggests a larger demand on SEQ which may be related to organizing the necessary transitions. Finally, there is a greater demand on INT process, reflected in an increase in ST, when organizing more than one syllable (Figure 4e). The data from Experiment 2 are in keeping with Klapp’s two process account of motor programming for speech responses when delineating speech complexity on the basis of recent models of speech production (Klapp, 2003; Spencer & Rogers, 2005; Bohland & Guenther, 2006). • Klapp’s (1995) two-process model of motor programming consists of two independent processes that govern the production of sequential actions such as speech: • INT process – involves retrieving information necessary to plan the individual units that are programmed in the sequence • SEQ process – involves placing the programmed units into the correct order prior to execution • . Figure 3a-c. Figure 3a (top) reveals that individuals could distinguish the duration requirements of the mono- and multi-syllabic utterances. Figure 3b (middle) indicates no additional INT demand results when planning single utterances that are longer in duration. Figure 2c. (bottom) reveals the anticipated larger SEQ cost for planning multiple syllables within an utterance. • An important assumption made in for these experiments is the syllable is the basic unit being programmed, given this, we expected • Duration of syllable will impact INT manifest as greater study time (ST) for longer duration monosyllabic responses – Exp.1 • Number of syllables will impact SEQ which will be manifest as greater reaction time (RT) for sequences involving more syllables – Exp. 1 • The structure of the planned syllable will impact INT which will be manifest as larger study time (ST) for monosyllabic responses that are more complex (e.g., CC(C)V vs. CV) – Exp 2 • Despite the structure of the planned syllables, the number of syllables will impact SEQ which will be manifest as greater reaction time (RT) for sequences involving more syllables – Exp. 2 Figure 2 provides an overview of the speech utterances required in Experiment 1 (left) and Experiment 2 (right). Utterances were differentiated on the basis of complexity at the level of INT and SEQ. The specific utterances used in each experiment were randomly presented during a period of practice.. Funding from the Sydney and J.L. Huffines Institute, Texas A&M University supported this research