Computational drug repositioning, designed to identify new indications for existing drugs,
significantly reduced the cost and time involved in drug development. Prediction of drug …

The generated speech of hidden Markov model (HMM)-based statistical parametric speech
synthesis still sounds “muffled.” One cause of this degradation in speech quality may be the …

In the state-of-the-art statistical parametric speech synthesis system, a speech analysis
module, eg STRAIGHT spectral analysis, is generally used for obtaining accurate and stable …

Methods, systems, and computer-readable media for text to-speech synthesis using an
autoencoder. In some imple mentations, data indicating a text for text-to-speech synthe sis is …

Abstract Collaborative Filtering to Supervised Learning (COFILS) transforms a Collaborative
Filtering (CF) problem into classical Supervised Learning (SL) problem. Applying COFILS …

In this work we look at using non-parametric, exemplar-based regression for the prediction
of prosodic contour targets from textual features in a speech synthesis system. We …

The paper proposes a novel deep neural network (DNN) architecture aimed at improving the
expressiveness of text-to-speech synthesis (TTS) by learning the properties of a particular …

The paper presents a novel architecture and method for training neural networks to produce
synthesized speech in a particular voice and speaking style, based on a small quantity of …

In this paper, we investigate the effectiveness of speaker adaptation for various essential
components in deep neural network based speech synthesis, including acoustic models …

In this paper, we investigate a combination of several feedforward deep neural networks
(DNNs) for a high-quality statistical parametric speech synthesis system. Recently, DNNs …