Deep neural networks (DNN) techniques have become pervasive in domains such as
natural language processing and computer vision. They have achieved great success in …

This study proposes a fully convolutional network (FCN) model for raw waveform-based
speech enhancement. The proposed system performs speech enhancement in an end-to …

The recently proposed deep clustering framework represents a significant step towards
solving the cocktail party problem. This study proposes and compares a variety of alternative …

This paper aims to address two issues existing in the current speech enhancement methods:
1) the difficulty of phase estimations; 2) a single objective function cannot consider multiple …

This paper proposes an end-to-end approach for single-channel speaker-independent multi-
speaker speech separation, where time-frequency (TF) masking, the short-time Fourier …

Recent approaches in text-to-speech (TTS) synthesis employ neural network strategies to
vocode perceptually-informed spectrogram representations directly into listenable …

Neural networks have proven their ability to be usefully applied as component of a speech
enhancement system. This is based on the known feature of neural nets to map regions …

Speech enhancement aims to suppress background noise in noisy speech signals in order
to improve speech perceptual quality and intelligibility. For tasks utilizing deep learning …

(DNN) based speech enhancement method that aims to enhance magnitude and phase
components of speech signals simultaneously. The novelty of the proposed method is two …

COLLEGE OF ENGINEERING Page 1 -1- CHIN-HUI LEE PROFESSOR SCHOOL OF
ELECTRICAL AND COMPUTER ENGINEERING JANUARY 2018 I. EARNED DEGREES • Ph.D …