A Fully Time-domain Neural Model for Subband-based Speech Synthesizer

This paper introduces a deep neural network model for subband-based speech synthesizer. The model benefits from the short bandwidth of the subband signals to reduce the complexity of the time-domain speech generator. We employed the multi-level wavelet analysis/synthesis to decompose/reconstruct the signal into subbands in time domain. Inspired from the WaveNet, a convolutional neural network (CNN) model predicts subband speech signals fully in time domain. Due to the short bandwidth of the subbands, a simple network architecture is enough to train the simple patterns of the subbands accurately. In the ground truth experiments with teacher-forcing, the subband synthesizer outperforms the fullband model significantly in terms of both subjective and objective measures. In addition, by conditioning the model on the phoneme sequence using a pronunciation dictionary, we have achieved the fully time-domain neural model for subband-based text-to-speech (TTS) synthesizer, which is nearly end-to-end. The generated speech of the subband TTS shows comparable quality as the fullband one with a slighter network architecture for each subband.Comment: 5 pages, 3 figur

Numerical analysis of high-index nanocomposite encapsulant for light-emitting diodes

We used two-dimensional Finte-Difference-Time-Domain (FDTD) software to study the transition behavior of nano-particles from scatterers to an optically uniform medium. We measured the transmission efficiency of the dipole source, which is located in the high refractive index medium(index=2.00) and encapsulated by low index resin(index=1.41). In an effort to compose index-matched resin and to reduce internal reflection, high-index nano-particles are added to low-index resin in simulations of various sizes and densities. As the size of the nano-particles and the average spacing between particles are reduced to 0.02 lambda and 0.07 lambda respectively, the transmission efficiency improves two-fold compared to that without nanoparticles. The numerical results can be used to understand the optical behavior of nano-particles and to improve the extraction efficiency of high brightness light-emitting-diodes(LEDs), through the use of nano-composite encapsulant.Comment: 9 pages, 5 jpg figure

Chronic active EBV infection: the experience of the Samsung Medical Center in South Korea

AbstractBackgroundChronic active EBV infection (CAEBV) of T-cell or NK-cell type is an EBV+ polyclonal, oligoclonal or often monoclonal lymphoproliferative disorder (LPD) recognized as representing the spectrum of EBV-associated T-cell and NK-cell LPD with different clinical presentations; one systemic and two cutaneous disorders including hydroa vacciniforme-like T-cell LPD and mosquito bite hypersensitivity. The systemic form of the disease is characterized by fever, persistent hepatitis, hepatosplenomegaly and lymphadenopathy, which shows varying degrees of clinical severity depending on the immune response of the host and the EBV viral load.Case reportsWe described the clinicopathological findings of two children with CAEBV with a brief review of the literature.ConclusionsRecognition of the disease is important for adequate management of the patient. EBV analysis should be included in the principal diagnostic tests for febrile children