Modeling of GRBAS perceptual evaluation using spectral features obtained from an auditory-based filterbank.

Perceptual voice evaluation according to the GRBAS scale is modelled using a linear combination of acoustic parameters calculated after a filter-bank analysis of the recorded voice signals. Modelling results indicate that for breathiness and asthenia more than 55% of the variance of perceptual rates can be explained by such a model, with only 4 latent variables. Moreover, the greatest part of the explained variance can be attributed to only one or two latent variables similarly weighted by all 5 listeners involved in the experiment. Correlation factors between actual rates and model predictions around 0.6 are obtained

Learning English is fun! Increasing motivation through video games

In this paper we present a study made with 16 university students with different levels of proficiency in English, who were divided into two groups: those with a basic level (B1 or lower) and those who had an advanced one (B2 or higher). These two groups had the opportunity to get to know and interact with a serious game developed in the ?Universidad Politécnica de Madrid? with the aim of helping in the teaching-learning process of English as a foreign language. Before and after the interaction, all students were interviewed on various aspects related to the English learning process. Although the results show some differences in the two groups, they mainly agree in that the use of the video game greatly increases their motivation to learn English, even though they also consider that they would be able to reach the same English level studying in a more traditional way. In addition, when the students were straightly asked about the usefulness of the video game to learn English, their answers in a graded scale of agreement, ranging from 1 to 5, had an average value of 3.76

A new approach for the glotis segmentation using Snakes

The present work describes a new methodology for the automatic detection of the glottal space from laryngeal images based on active contour models (snakes). In order to obtain an appropriate image for the use of snakes based techniques, the proposed algorithm combines a pre-processing stage including some traditional techniques (thresholding and median filter) with more sophisticated ones such as anisotropic filtering. The value selected for the thresholding was fixed to the 85% of the maximum peak of the image histogram, and the anisotropic filter permits to distinguish two intensity levels, one corresponding to the background and the other one to the foreground (glottis). The initialization carried out is based on the magnitude obtained using the Gradient Vector Flow field, ensuring an automatic process for the selection of the initial contour. The performance of the algorithm is tested using the Pratt coefficient and compared against a manual segmentation. The results obtained suggest that this method provided results comparable with other techniques such as the proposed in (Osma-Ruiz et al., 2008)