Mejora de la interfaz del simulador de voz Vox

A partir de un simulador de vocales denominado Vox, programado en MATLAB, desarrollado originalmente en la Universidad Técnica de Aquisgrán por Malte Kob [1] y mejorado en el Departamento de ICS de la EUITT [2], se pueden generar voces sintéticas. La principal limitación del simulador es que sólo puede generar vocales sintéticas, además la simulación se realiza a partir de parámetros anatómicos y fisiológicos fijos. La estructura actual del programa dificulta la modificación rápida de cualquiera de los parámetros básicos de la misma, circunstancia que podría mejorar mediante una interfaz gráfica. El proyecto consistirá, por un lado, en completar el simulador haciendo posible también la síntesis a partir de los parámetros anatómicos de hombres, mujeres y niños; y por otro, en el diseño e implementación de una interfaz gráfica de usuario que nos permita seleccionar los diferentes parámetros físicos para la simulación y recoger los resultados de la misma de manera más sencilla. Starting from a vowels simulator called Vox, programmed in MATLAB, originally developed in the Technical college of Aquisgrán by Malte Kob [1] and improved in the ICS Department of the EUITT [2], with this programme you can generate synthetic voices. The main limitation of the simulator is that it only can generate synthetic vowels; moreover the simulation is made from anatomical and physiological fixed parameters. The current structure of the programme complicates the quick modification of any of the basic parameters of it, circumstance that could be improved through a graphic interface. On the one hand, the project consists in completing the simulator doing the synthesis possible, from the anatomical woman, men and children parameters; on the other hand, the design and implementation of a graphic user interface, that allow us to select different physical parameters to the simulation and gather the results of it in a simple way.

Effects of the correction of particle microbial contamination and particle transit model in the rumen on in situ protein evaluation of grass hays.

Effects of considering the particle comminution rate -kc- in addition to particle rumen outflow -kp- and the ruminal microbial contamination on estimates of by-pass and intestinal digestibility of DM, organic matter and crude protein were examined in perennial ryegrass and oat hays. By-pass kc-kp-based values of amino acids were also determined. This study was performed using particle transit, in situ and 15N techniques on three rumen and duodenum-cannulated wethers. The above estimates were determined using composite samples from rumen-incubated residues representative of feed by-pass. Considering the comminution rate, kc, modified the contribution of the incubated residues to these samples in both hays and revealed a higher microbial contamination, consistently in oat hay and only as a tendency for crude protein in ryegrass hay. Not considering kc or rumen microbial contamination overvalued by-pass and intestinal digestibility in both hays. Therefore, non-microbial-corrected kp-based values of intestinal digested crude protein were overestimated as compared with corrected and kc-kp-based values in ryegrass hay -17.4 vs 4.40%- and in oat hay -5.73 vs 0.19%-. Both factors should be considered to obtain accurate in situ estimates in grasses, as the protein value of grasses is very conditioned by the microbial synthesis derived from their ruminal fermentation. Consistent overvaluations of amino acid by-pass due to not correcting microbial contamination were detected in both hays, with large variable errors among amino acids. A similar degradation pattern of amino acids was recorded in both hays. Cysteine, methionine, leucine and valine were the most degradation-resistant amino acids.

Methods for noise reduction in far-field patterns obtained from cylindrical near-field antenna measurements

Two different methods to reduce the noise power in the far-field pattern of an antenna as measured in cylindrical near-field (CNF) are proposed. Both methods are based on the same principle: the data recorded in the CNF measurement, assumed to be corrupted by white Gaussian and space-stationary noise, are transformed into a new domain where it is possible to filter out a portion of noise. Those filtered data are then used to calculate a far-field pattern with less noise power than that one obtained from the measured data without applying any filtering. Statistical analyses are carried out to deduce the expressions of the signal-to-noise ratio improvement achieved with each method. Although the idea of the two alternatives is the same, there are important differences between them. The first one applies a modal filtering, requires an oversampling and improves the far-field pattern in all directions. The second method employs a spatial filtering on the antenna plane, does not require oversampling and the far-field pattern is only improved in the forward hemisphere. Several examples are presented using both simulated and measured near-field data to verify the effectiveness of the methods.

A comparison of open-source segmentation architectures for dealing with imperfect data from the media in speech synthesis

Traditional Text-To-Speech (TTS) systems have been developed using especially-designed non-expressive scripted recordings. In order to develop a new generation of expressive TTS systems in the Simple4All project, real recordings from the media should be used for training new voices with a whole new range of speaking styles. However, for processing this more spontaneous material, the new systems must be able to deal with imperfect data (multi-speaker recordings, background and foreground music and noise), filtering out low-quality audio segments and creating mono-speaker clusters. In this paper we compare several architectures for combining speaker diarization and music and noise detection which improve the precision and overall quality of the segmentation.