University of Texas at Dallas

About: University of Texas at Dallas is a education organization based out in Richardson, Texas, United States. It is known for research contribution in the topics: Population & Computer science. The organization has 14986 authors who have published 35589 publications receiving 1293714 citations. The organization is also known as: UT-Dallas & UT Dallas.

Speech enhancement based on perceptually motivated bayesian estimators of the magnitude spectrum

Abstract: The traditional minimum mean-square error (MMSE) estimator of the short-time spectral amplitude is based on the minimization of the Bayesian squared-error cost function. The squared-error cost function, however, is not subjectively meaningful in that it does not necessarily produce estimators that emphasize spectral peak (formants) information or estimators which take into account auditory masking effects. To overcome the shortcomings of the MMSE estimator, we propose in this paper Bayesian estimators of the short-time spectral magnitude of speech based on perceptually motivated cost functions. In particular, we use variants of speech distortion measures, such as the Itakura-Saito and weighted likelihood-ratio distortion measures, which have been used successfully in speech recognition. Three classes of Bayesian estimators of the speech magnitude spectrum are derived. The first class of estimators emphasizes spectral peak information, the second class uses a weighted-Euclidean cost function that implicitly takes into account auditory masking effects, and the third class of estimators is designed to penalize spectral attenuation. Of the three classes of Bayesian estimators, the estimators that implicitly take into account auditory masking effect performed the best in terms of having less residual noise and better speech quality.

The Impact of Sustained Engagement on Cognitive Function in Older Adults: The Synapse Project

Abstract: In the research reported here, we tested the hypothesis that sustained engagement in learning new skills that activated working memory, episodic memory, and reasoning over a period of 3 months would enhance cognitive function in older adults. In three conditions with high cognitive demands, participants learned to quilt, learned digital photography, or engaged in both activities for an average of 16.51 hr a week for 3 months. Results at posttest indicated that episodic memory was enhanced in these productive-engagement conditions relative to receptive-engagement conditions, in which participants either engaged in nonintellectual activities with a social group or performed low-demand cognitive tasks with no social contact. The findings suggest that sustained engagement in cognitively demanding, novel activities enhances memory function in older adulthood, but, somewhat surprisingly, we found limited cognitive benefits of sustained engagement in social activities.

A choice prediction competition: Choices from experience and from description

Abstract: Erev, Ert, and Roth organized three choice prediction competitions focused on three related choice tasks: One shot decisions from description (decisions under risk), one shot decisions from experience, and repeated decisions from experience. Each competition was based on two experimental datasets: An estimation dataset, and a competition dataset. The studies that generated the two datasets used the same methods and subject pool, and examined decision problems randomly selected from the same distribution. After collecting the experimental data to be used for estimation, the organizers posted them on the Web, together with their fit with several baseline models, and challenged other researchers to compete to predict the results of the second (competition) set of experimental sessions. Fourteen teams responded to the challenge: The last seven authors of this paper are members of the winning teams. The results highlight the robustness of the difference between decisions from description and decisions from experience. The best predictions of decisions from descriptions were obtained with a stochastic variant of prospect theory assuming that the sensitivity to the weighted values decreases with the distance between the cumulative payoff functions. The best predictions of decisions from experience were obtained with models that assume reliance on small samples. Merits and limitations of the competition method are discussed.

Metal contacts on physical vapor deposited monolayer MoS2

Abstract: The understanding of the metal and transition metal dichalcogenide (TMD) interface is critical for future electronic device technologies based on this new class of two-dimensional semiconductors. Here, we investigate the initial growth of nanometer-thick Pd, Au, and Ag films on monolayer MoS2. Distinct growth morphologies are identified by atomic force microscopy: Pd forms a uniform contact, Au clusters into nanostructures, and Ag forms randomly distributed islands on MoS2. The formation of these different interfaces is elucidated by large-scale spin-polarized density functional theory calculations. Using Raman spectroscopy, we find that the interface homogeneity shows characteristic Raman shifts in E2g1 and A1g modes. Interestingly, we show that insertion of graphene between metal and MoS2 can effectively decouple MoS2 from the perturbations imparted by metal contacts (e.g., strain), while maintaining an effective electronic coupling between metal contact and MoS2, suggesting that graphene can act as a c...