Windings of the stable Kolmogorov process

We investigate the windings around the origin of the two-dimensional Markov process (X,L) having the stable L\'evy process L and its primitive X as coordinates, in the non-trivial case when |L| is not a subordinator. First, we show that these windings have an almost sure limit velocity, extending McKean's result [McK63] in the Brownian case. Second, we evaluate precisely the upper tails of the distribution of the half-winding times, connecting the results of our recent papers [CP14, PS14]

Persistence of integrated stable processes

We compute the persistence exponent of the integral of a stable L\'evy process in terms of its self-similarity and positivity parameters. This solves a problem raised by Z. Shi (2003). Along the way, we investigate the law of the stable process L evaluated at the first time its integral X hits zero, when the bivariate process (X,L) starts from a coordinate axis. This extends classical formulae by McKean (1963) and Gor'kov (1975) for integrated Brownian motion

Towards Personalized Synthesized Voices for Individuals with Vocal Disabilities: Voice Banking and Reconstruction

When individuals lose the ability to produce their own speech, due to degenerative diseases such as motor neurone disease (MND) or Parkinson’s, they lose not only a functional means of communication but also a display of their individual and group identity. In order to build personalized synthetic voices, attempts have been made to capture the voice before it is lost, using a process known as voice banking. But, for some patients, the speech deterioration frequently coincides or quickly follows diagnosis. Using HMM-based speech synthesis, it is now possible to build personalized synthetic voices with minimal data recordings and even disordered speech. The power of this approach is that it is possible to use the patient’s recordings to adapt existing voice models pre-trained on many speakers. When the speech has begun to deteriorate, the adapted voice model can be further modified in order to compensate for the disordered characteristics found in the patient’s speech. The University of Edinburgh has initiated a project for voice banking and reconstruction based on this speech synthesis technology. At the current stage of the project, more than fifteen patients with MND have already been recorded and five of them have been delivered a reconstructed voice. In this paper, we present an overview of the project as well as subjective assessments of the reconstructed voices and feedback from patients and their families

Large enhancement of the thermoelectric power factor in disordered materials through resonant scattering

In the search for more efficient thermoelectric materials, scientists have placed high hopes in the possibility of enhancing the power factor using resonant states. In this study, we investigate theoretically the effects of randomly distributed resonant impurities on the power factor. Using the Chebyshev Polynomial Green's Function method, we compute the electron transport properties for very large systems (10 million atoms) with an exact treatment of disorder. The introduction of resonant defects can lead to a large enhancement of the power factor together with a sign inversion in the Seebeck coefficient. This boost depends crucially on the position of the resonant peak, and on the interplay between elastic impurity scattering and inelastic processes. Strong electron-phonon or electron-electron scattering are found detrimental. Finally, the robustness of our results is examined in the case of anisotropic orbitals and two-dimensional confinement. Our findings are promising for the prospect of thermoelectric power generation.Comment: To appear in Phys. Rev.

NGC 6302: high-ionization permitted lines. Applying X-SSN synthesis to VLT-UVES spectra

A preliminary VLT-UVES spectrum of NGC 6302 (Casassus et al. 2002, MN), which hosts one of the hottest PN nuclei known (Teff ~ 220000 K; Wright et al. 2011, MN), has been recently analysed by means of X-SSN, a spectrum synthesis code for nebulae (Morisset and P\'equignot). Permitted recombination lines from highly-ionized species are detected/identified for the first time in a PN, and some of them probably for the first time in (Astro)Physics. The need for a homogeneous, high signal-to-noise UVES spectrum for NGC 6302 is advocated.Comment: Poster contribution (2 pages, 1 figure) to IAU Symposium 283: "Planetary Nebulae: An Eye to the Future" held in Puerto de la Cruz, Tenerife, Spain in July 25th-29th 201

Spatial memory shapes density dependence in population dynamics

Most population dynamics studies assume that individuals use space uniformly, and thus mix well spatially. In numerous species, however, individuals do not move randomly, but use spatial memory to visit renewable resource patches repeatedly. To understand the extent to which memorybased foraging movement may affect density-dependent population dynamics through its impact on competition, we developed a spatially explicit, individual-based movement model where reproduction and death are functions of foraging efficiency. We compared the dynamics of populations of with- and without-memory individuals. We showed that memory-based movement leads to a higher population size at equilibrium, to a higher depletion of the environment, to a marked discrepancy between the global (i.e. measured at the population level) and local (i.e. measured at the individual level) intensities of competition, and to a nonlinear density dependence. These results call for a deeper investigation of the impact of individual movement strategies and cognitive abilities on population dynamics

Analysis of Speaker Clustering Strategies for HMM-Based Speech Synthesis

This paper describes a method for speaker clustering, with the application of building average voice models for speakeradaptive HMM-based speech synthesis that are a good basis for adapting to specific target speakers. Our main hypothesis is that using perceptually similar speakers to build the average voice model will be better than use unselected speakers, even if the amount of data available from perceptually similar speakers is smaller. We measure the perceived similarities among a group of 30 female speakers in a listening test and then apply multiple linear regression to automatically predict these listener judgements of speaker similarity and thus to identify similar speakers automatically. We then compare a variety of average voice models trained on either speakers who were perceptually judged to be similar to the target speaker, or speakers selected by the multiple linear regression, or a large global set of unselected speakers. We find that the average voice model trained on perceptually similar speakers provides better performance than the global model, even though the latter is trained on more data, confirming our main hypothesis. However, the average voice model using speakers selected automatically by the multiple linear regression does not reach the same level of performance. Index Terms: Statistical parametric speech synthesis, hidden Markov models, speaker adaptatio