No abstract

Recent advances in physiological data collection methods have made it possible to test the accuracy of predictions against speaker-specific vocal tracts and acoustic patterns. Vocal tract dimensions for /r/ derived via magnetic-resonance imaging (MRI) for two speakers of American English [Alwan, Narayanan, and Haker, J. Acoust. Soc. Am. 101, 1078-1089 (1997)] were used to construct models of the acoustics of /r/. Because previous models have not sufficiently accounted for the very low F3 characteristic of /r/, the aim was to match formant frequencies predicted by the models to the full range of formant frequency values produced by the speakers in recordings of real words containing /r/. In one set of experiments, area functions derived from MRI data were used to argue that the Perturbation Theory of tube acoustics cannot adequately account for /r/, primarily because predicted locations did not match speakers' actual constriction locations. Different models of the acoustics of /r/ were tested using the Maeda computer simulation program [Maeda, Speech Commun. 1, 199-299 (1982)]; the supralingual vocal-tract dimensions reported in Alwan et al. were found to be adequate at predicting only the highest of attested F3 values. By using (1) a recently developed adaptation of the Maeda model that incorporates the sublingual space as a side branch from the front cavity, and by including (2) the sublingual space as an increment to the dimensions of the front cavity, the mid-to-low values of the speakers' F3 range were matched. Finally, a simple tube model with dimensions derived from MRI data was developed to account for cavity affiliations. This confirmed F3 as a front cavity resonance, and variations in F1, F2, and F4 as arising from mid- and back-cavity geometries. Possible trading relations for F3 lowering based on different acoustic mechanisms for extending the front cavity are also proposed.

Magnetic resonance images of the vocal tract during sustained production of [symbol: see text] by four native American English talkers are employed for measuring vocal-tract dimensions and for morphological analysis of the 3D vocal tract and tongue shapes. Electropalatography contact profiles are used for studying inter- and intra-talker variabilities. The vocal tract during the production of [symbol: see text] appears to be characterized by three cavities due to the presence of two supraglottal constrictions: the primary one in the oral cavity, and a secondary one in the pharyngeal cavity. All subjects show a large volume anterior to the oral constriction, which results from an inward-drawn tongue body, an anterior tongue body that is characterized by convex cross sections, and a concave posterior tongue body shape. Inter-subject variabilities are observed in the oral-constriction location and the way the constriction is formed. No systematic differences are found between the 3-D vocal tract and tongue shapes of word-initial and syllabic [symbol: see text]s. Tongue-shaping mechanisms for these sounds and their acoustic implications are discussed.

Tamil is unusual among the world's languages in that some of its dialects have five contrasting liquids. This paper focuses on the characterization of these sounds in terms of articulatory geometry and kinematics, as well as their articulatory-acoustic relations. This study illustrates the use of multiple techniques--static palatography, magnetic resonance imaging (MRI), and magnetometry (EMMA)--for investigating both static and dynamic articulatory characteristics using a single native speaker of Tamil. Dialectal merger and neutralization phenomena exhibited by the liquids of Tamil are discussed. Comparisons of English /[symbol: see text]/ and /l/ with Tamil provide evidence for generality in underlying mechanisms of rhotic and lateral production. The articulatory data justify the postulation of a class of rhotics and a class of laterals in Tamil, but do not provide evidence in favor of a larger class of liquids. Such a superclass appears to have largely an acoustic basis.

New and emerging mobile technologies are providing unprecedented possibilities for understanding and intervening on obesity-related behaviors in real time. However, the mobile health (mHealth) field has yet to catch up with the fast-paced development of technology. Current mHealth efforts in weight management still tend to focus mainly on short message systems (SMS) interventions, rather than taking advantage of real-time sensing to develop Just-In-Time, Adaptive Interventions (JITAIs). This paper will give an overview of the current technology landscape for sensing and intervening on three behaviors that are central to weight management; diet, physical activity, and sleep. Then five studies that really dig into the possibilities that these new technologies afford will be showcased. We conclude with a discussion of hurdles that mHealth obesity research has yet to overcome, and a future-facing discussion.