Denoising a single-channel speech (recorded using one microphone) remains an open
problem in many speech-related applications. Recently, supervised deep learning methods …

In this research work, we propose the model based on the Genetic Algorithm (GA) and Deep
Neural Network (DNN) to enhance the quality and intelligibility of the noisy speech. In this …

We compare the run-time complexity of recent deep neural network (DNN) and non-DNN
based monaural speech enhancement algorithms. Specifically, we consider fully connected …

This research work proposes a new Genetic Algorithm (GA) based fusion scheme to
effectively fuse the Time–Frequency (T–F) binary mask of voiced and unvoiced speech. The …

Improving the speech intelligibility remains a challenging problem in digital hearing aids.
This research work proposes a new speech segregation algorithm to improve the speech …

Speech signal enhancement achieves high-level performance in recent years using deep
learning techniques. However, the deep learning technique in the speech enhancement …

Fusion plays an important role to retrieve the single output data from the input data set and
in turn improves the quality of the results. Single channel based separation of speech …

Voice activity detection (VAD) is a vital module in various applications like speech
recognition, speech enhancement, and dominant speaker identification. The performance of …

Speech Intelligibility is of prime importance in places of mass gathering such as railway
stations and airports as it is imperative for the speech to be understandable for the benefit …

Speech enhancement is one of the speech processing techniques which is perturbed mostly
with increasing some perceptual part of speech like quality and intelligibility that has been …