INESC-ID

About: INESC-ID is a nonprofit organization based out in Lisbon, Portugal. It is known for research contribution in the topics: Field-programmable gate array & Control theory. The organization has 932 authors who have published 2618 publications receiving 37658 citations.

Pitch-synchronous time-scaling for prosodic and voice quality transformations.

Abstract: Current time-domain pitch modification techniques have well known limitations for large variations of the original fundamental frequency This paper proposes a technique for changing the pitch and duration of a speech signal based on time-scaling the linear prediction (LP) residual The resulting speech signal achieves better quality than the traditional LP-PSOLA method for large fundamental frequency modifications By using nonuniform time-scaling, this technique can also change the shape of the LP residual for each pitch period This way we can simulate changes of the most relevant glottal source parameters like the open quotient, the spectral tilt and the asymmetry coefficient Careful adjustments of these source parameters allows the transformation of the original speech signal so that it is perceived as if it was uttered with a different voice quality or emotion

A comparative study of citations and links in document classification

Abstract: It is well known that links are an important source of information when dealing with Web collections However, the question remains on whether the same techniques that are used on the Web can be applied to collections of documents containing citations between scientific papers In this work we present a comparative study of digital library citations and Web links, in the context of automatic text classification We show that there are in fact differences between citations and links in this context For the comparison, we run a series of experiments using a digital library of computer science papers and a Web directory In our reference collections, measures based on co-citation tend to perform better for pages in the Web directory, with gains up to 37% over text based classifiers, while measures based on bibliographic coupling perform better in a digital library We also propose a simple and effective way of combining a traditional text based classifier with a citation-link based classifier This combination is based on the notion of classifier reliability and presented gains of up to 14% in micro-averaged F1 in the Web collection However, no significant gain was obtained in the digital library Finally, a user study was performed to further investigate the causes for these results We discovered that misclassifications by the citation-link based classifiers are in fact difficult cases, hard to classify even for humans

Reduced-Order Models for Electromagnetic Scattering Problems

Abstract: We consider model-order reduction of systems occurring in electromagnetic scattering problems, where the inputs are current distributions operating in the presence of a scatterer, and the outputs are their corresponding scattered fields. Using the singular-value decomposition (SVD), we formally derive minimal-order models for such systems. We then use a discrete empirical interpolation method (DEIM) to render the minimal-order models more suitable to numerical computation. These models consist of a set of elementary sources and a set of observation points, both interior to the scatterer, and located automatically by the DEIM. A single matrix then maps the values of any incident field at the observation points to the amplitudes of the sources needed to approximate the corresponding scattered field. Similar to a Green's function, these models can be used to quickly analyze the interaction of the scatterer with other nearby scatterers or antennas.