A reverberation-time-aware deep-neural-network (DNN)-based speech dereverberation
framework is proposed to handle a wide range of reverberation times. There are three key …

We propose an integrated end-to-end automatic speech recognition (ASR) paradigm by joint
learning of the front-end speech signal processing and back-end acoustic modeling. We …

A number of numerical practices exist that actuaries use to predict annual medical claim
expense in an insurance company. This amount needs to be included in the yearly financial …

In this paper, we propose a model to perform speech dereverberation by estimating its
spectral magnitude from the reverberant counterpart. Our models are capable of extracting …

Along with the increasing penetration of photovoltaic (PV) power generation, regional power
forecasting becomes more and more critical for stable and economical operation of power …

In order to suppress the late reverberation in the spectral domain, many single-channel
dereverberation techniques rely on an estimate of the late reverberation power spectral …

In daily-life scenarios, reverberation inevitably caus-es a decrease in speech recognizability
and speech quality. Exploring methods to eliminate reverberation will benefit both human …

We present an improved method for training Deep Neural Networks for dereverberation and
show that it can improve performance for the speech processing tasks of speaker verification …

To cope with reverberation and noise in single channel acoustic scenarios, typical
supervised deep neural network (DNN)-based techniques learn a mapping from reverberant …

A number of numerical practices exist that actuaries use to predict annual medical claims
expense in an insurance company. This amount needs to be included in the yearly financial …