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

Monaural speech separation is the process of separating the target speech from the noisy
speech mixture recorded using single microphone. It is a challenging problem in speech …

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 …

Monaural speech separation is the process of separating the target speech from a noisy
speech mixture recorded using single microphone. It can be used in wide range of …

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 …

This research work proposes an image analysis‐based algorithm to enhance the time–
frequency (T–F) mask obtained in the initial segmentation of CASA‐based monaural speech …

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 …