A huge amount of research has been done in the field of speech signal processing in recent
years. In particular, there has been increasing interest in the automatic speech recognition …

Speech enhancement model is used to map a noisy speech to a clean speech. In the
training stage, an objective function is often adopted to optimize the model parameters …

A new cross-entropy-guided measure (CEGM) is proposed to indirectly assess accuracies of
automatic speech recognition (ASR) of degraded speech with a speech enhancement front …

Speech enhancement involves the distinction of a target speech signal from an intrusive
background. Although generative approaches using Variational Autoencoders or Generative …

In the subject of pattern recognition, speech recognition is an important study topic. The
authors give a detailed assessment of voice recognition strategies for several majority …

Speech enables easy human-to-human communication as well as human-to-machine
interaction. However, the quality of speech degrades due to background noise in the …

Conventional deep neural network (DNN)-based speech enhancement (SE) approaches
aim to minimize the mean square error (MSE) between enhanced speech and clean …

Speech recognition of a language is a key area in the field of pattern recognition. This paper
presents a comprehensive survey on the speech recognition techniques for non-Indian and …

The process of recognizing a person through his/her speech signals can be termed Speech
recognition and the model used to do this task is known as the speech recognition system. It …

This paper proposes a novel fully convolutional neural network (FCN) called FLGCNN to
address the end-to-end speech enhancement in time domain. The proposed FLGCNN is …