In order to examine the stability and patterning of speech movement sequences, movements of the lip were recorded as subjects produced a phrase at normal, fast, and slow rates. Three methods of analysis were employed. First, a new index of spatiotemporal stability was derived by summing the standard deviations computed across amplitude- and time-normalized displacement records. This index indicated that normal and fast rates of speech production result in more stable movement execution compared to slow rates. In the second analysis, the relative time of occurrence of the peak velocity of the three middle opening movements of the utterance was measured. For each of the three peaks, the preservation of relative timing was assessed by applying Genter's (1987) slope test. The results clearly indicate that the relative timing of these events does not remain constant across changes in speech rate. The relative timing of the middle opening gestures shifted, becoming later as utterance duration increased. In a third analysis, pattern recognition techniques were applied to the normalized displacement waveforms. A classification algorithm was highly successful in sorting waveforms into normal, fast, and slow rate conditions. These findings were interpreted to suggest that, within a subject, three distinct patterns or movement templates exist, one for each rate of production. Speech rate appears to be a global parameter, one that affects the entire command sequence for the utterance.

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There has been recent interest in characterizing UHF propagation within buildings and houses. Factory radio channels, however, have not been discussed previously in the literature. This paper details the results of narrow-hand propagation measurements performed at five factories. The extensive empirical data indicate that path loss is dependent upon local surroundings and is log-normally distributed, temporal fading is Rician, and small-scale signal fluctuations due to receiver motion are primarily Rayleigh, although Rician and lognormal distributions fit some of the data. Shadowing effects of common factory equipment likely to obstruct indoor radio paths are also given here.

There are two approaches to the two-sensor track fusion problem. recently presented the state vector fusion method which combines the filtered state vectors from the two sensors to form a new estimate while taking into account the correlated process noise. The measurement fusion method or data compression [5] combines the measurements from the two sensors first and then uses this fused measurement to estimate the state vector. The two methods are compared and an example shows the amount of improvement in the uncertainty of the resulting estimate of the state vector with the measurement fusion method.

Speech requires the control of complex movements of orofacial structures to produce dynamic variations in the vocal tract transfer function. The nature of the underlying motor control processes has traditionally been investigated by employing measures of articulatory movements, including movement amplitude, velocity, and duration, at selected points in time. An alternative approach, first used in the study of limb motion, is to examine the entire movement trajectory over time. A new approach to speech movement trajectory analysis was introduced in earlier work from this laboratory. In this method, trajectories from multiple movement sequences are time-and amplitude-normalized, and the STI (spatiotemporal index) is computed to capture the degree of convergence of a set of trajectories onto a single, underlying movement template. This research note describes the rationale for this analysis and provides a detailed description of the signal processing involved. Alternative interpolation procedures for timenormalization of kinematic data are also considered. A widely used strategy for gaining insights into the control of movement is to search for invariance in movement trajectories. This approach has been used in the study of many different movement production systems, from octopus tentacle movements to human arm and speech movements (Atkeson & Hollerbach, 1985; Flash & Hogan, 1985; Gutfreund et al., 1996; Ostry, Cooke, & Munhall, 1987; Smith, Goffman, Zelaznik, Ying, & McGillem, 1995). When kinematic invariance is sought, two related aspects of movement trajectories are often assessed: (1) the degree to which a set of trajectories shows stereotypic features (e.g., a bell-shaped velocity profile), and (2) how variable a set of trajectories is in relation to this standard pattern.The majority of studies of speech kinematic output have employed measures at single time points (e.g., Ackermann, Hertrich, & Scharf, 1995; Kent & Moll, 1975; Kuehn & Moll, 1976; Zimmermann 1980a Zimmermann , 1980b to search for invariant aspects of motor output. In these studies, rather than considering the movement trajectory as a whole, specific points are selected to characterize temporal and spatial aspects of motion. In a smaller number of studies, movement trajectories for single speech movements were analyzed to determine if there is a common pattern in the velocity profile (Adams, Weismer, & Kent, 1993; Ostry et al., 1987; Shaiman, Adams, & Kimelman, 1997 parameters of movement (e.g., displacement, peak velocity, and duration), and a few investigations attempted to determine if the bell-shaped velocity profile, prevalent in many limb movements, also characterized single speech movements. In 1995, we introduced an analysis that employed the entire lower lip movement trajectory for a six-syllable phrase (Smith et al., 1995). After linearly amplitude-and time-normalizing each multicomponent movement trajectory, an average trajectory for the set of trials within one condition was computed. Standard deviations of the set were comput...