LSTM Deep Neural Networks Postfiltering for Improving the Quality of Synthetic Voices

Recent developments in speech synthesis have produced systems capable of outcome intelligible speech, but now researchers strive to create models that more accurately mimic human voices. One such development is the incorporation of multiple linguistic styles in various languages and accents. HMM-based Speech Synthesis is of great interest to many researchers, due to its ability to produce sophisticated features with small footprint. Despite such progress, its quality has not yet reached the level of the predominant unit-selection approaches that choose and concatenate recordings of real speech. Recent efforts have been made in the direction of improving these systems. In this paper we present the application of Long-Short Term Memory Deep Neural Networks as a Postfiltering step of HMM-based speech synthesis, in order to obtain closer spectral characteristics to those of natural speech. The results show how HMM-voices could be improved using this approach.Comment: 5 pages, 5 figure

Probing a Bose-Einstein condensate with an atom laser

A pulsed atom laser derived from a Bose-Einstein condensate is used to probe a second target condensate. The target condensate scatters the incident atom laser pulse. From the spatial distribution of scattered atoms, one can infer important properties of the target condensate and its interaction with the probe pulse. As an example, we measure the s-wave scattering length that, in low energy collisions, describes the interaction between the |F = 1,mF = −1> and |F = 2,mF = 0> hyperfine ground states in 87Rb

Microwave-mediated synthesis of N-methyliminodiacetic acid (MIDA) boronates

A library of over 20, mainly aryl or heteroaryl, N-methyliminodiacetic acid (MIDA) boronates have been synthesised. A rapid microwave-mediated (MW) method (5–10 min) has been developed using polyethylene glycol 300 (PEG 300) as solvent. However, acetonitrile (MeCN) and dimethylformamide (DMF) were found to be alternative solvents, the latter especially for 2-substituted aryl boronic acids

The scientific heritage of Richard Henry Dalitz, FRS (1925-2006)

Professor Richard H. Dalitz passed away on January 13, 2006. He was almost 81 years old and his outstanding contributions are intimately connected to some of the major breakthroughs of the 20th century in particle and nuclear physics. These outstanding contributions go beyond the Dalitz Plot, Dalitz Pair and CDD poles that bear his name. He pioneered the theoretical study of strange baryon resonances, of baryon spectroscopy in the quark model, and of hypernuclei, to all of which he made lasting contributions. His formulation of the "$\theta-\tau$ puzzle" led to the discovery that parity is not a symmetry of the weak interactions. A brief scientific evaluation of Dalitz's major contributions to particle and nuclear physics is hereby presented, followed by the first comprehensive list of his scientific publications, as assembled from several sources. The list is divided into two categories: the first, main part comprises Dalitz's research papers and reviews, including topics in the history of particle physics, biographies and reminiscences; the second part lists book reviews, public lectures and obituaries authored by Dalitz, and books edited by him. This provides the first necessary step towards a more systematic research of the Dalitz heritage in modern physics. The present 2016 edition updates the original 2006 edition, published in Nucl. Phys. A 771 (2006) 2-7, doi:10.1016/j.nuclphysa.2006.03.007, and 8-25, doi:10.1016/j.nuclphysa.2006.03.008, by including for the first time a dozen or so of publications, found recently in a list submitted to the Royal Society by Dalitz in 2004, that escaped our attention in the original version.Comment: updates the original edition by including several publications, mostly in category III, that were unknown to us in 200

Post-training discriminative pruning for RBMs

One of the major challenges in the area of artificial neural networks is the identification of a suitable architecture for a specific problem. Choosing an unsuitable topology can exponentially increase the training cost, and even hinder network convergence. On the other hand, recent research indicates that larger or deeper nets can map the problem features into a more appropriate space, and thereby improve the classification process, thus leading to an apparent dichotomy. In this regard, it is interesting to inquire whether independent measures, such as mutual information, could provide a clue to finding the most discriminative neurons in a network. In the present work we explore this question in the context of Restricted Boltzmann Machines, by employing different measures to realize post-training pruning. The neurons which are determined by each measure to be the most discriminative, are combined and a classifier is applied to the ensuing network to determine its usefulness. We find that two measures in particular seem to be good indicators of the most discriminative neurons, producing savings of generally more than 50% of the neurons, while maintaining an acceptable error rate. Further, it is borne out that starting with a larger network architecture and then pruning is more advantageous than using a smaller network to begin with. Finally, a quantitative index is introduced which can provide information on choosing a suitable pruned network.Fil: Sánchez Gutiérrez, Máximo. Universidad Autónoma Metropolitana; MéxicoFil: Albornoz, Enrique Marcelo. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Científico Tecnológico Conicet - Santa Fe. Instituto de Investigación en Señales, Sistemas e Inteligencia Computacional. Universidad Nacional del Litoral. Facultad de Ingeniería y Ciencias Hídricas. Instituto de Investigación en Señales, Sistemas e Inteligencia Computacional; ArgentinaFil: Rufiner, Hugo Leonardo. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Científico Tecnológico Conicet - Santa Fe. Instituto de Investigación en Señales, Sistemas e Inteligencia Computacional. Universidad Nacional del Litoral. Facultad de Ingeniería y Ciencias Hídricas. Instituto de Investigación en Señales, Sistemas e Inteligencia Computacional; Argentina. Universidad Nacional de Entre Ríos; ArgentinaFil: Close, John Goddard. Universidad Autónoma Metropolitana; Méxic

Retail Redlining: Are gasoline prices higher in poor and minority neighborhoods?

Higher retail prices are frequently cited as a cost of living in poor, minority neighborhoods. However, the empirical evidence, which primarilycomes from the grocery gap literature on food prices, has been mixed. This study uses new data on retail gasoline prices in three major U.S.cities to provide evidence on the relationship between neighborhood characteristics and consumer prices. We find that gasoline prices do not varygreatly with neighborhood racial composition, but that prices are higher in poor neighborhoods. For a 10 percentage point increase in the percentof families with incomes below the poverty line relative to families with incomes between 1 and 2 times the poverty line, retail gasoline prices are estimated to increase by an average of 0.70 percent. This differential is reduced to 0.22 percent once we add controls for costs, competition, and demand. Finally, we provide evidence that the remaining, small, price differential for poor neighborhoods is likely the result of traditional price discrimination in response to less competition and/or more inelastic demand in these locations.

Approaching the Heisenberg limit in an atom laser

We present experimental and theoretical results showing the improved beam quality and reduced divergence of an atom laser produced by an optical Raman transition, compared to one produced by an rf transition. We show that Raman outcoupling can eliminate the diverging lens effect that the condensate has on the outcoupled atoms. This substantially improves the beam quality of the atom laser, and the improvement may be greater than a factor of 10 for experiments with tight trapping potentials. We show that Raman outcoupling can produce atom lasers whose quality is only limited by the wave function shape of the condensate that produces them, typically a factor of 1.3 above the Heisenberg limit