The first book to provide comprehensive and up-to-date coverage of all major speech
enhancement algorithms proposed in the last two decades, Speech Enhancement: Theory …

In this paper, the improvements in the recently implemented Kannada speech recognition
system is demonstrated in detail. The Kannada automatic speech recognition (ASR) system …

Recent progress in deep learning has revolutionized speech recognition research, with
Deep Neural Networks (DNNs) becoming the new state of the art for acoustic modeling …

Speech data collected under uncontrolled environment need to be processed to build a
robust automatic speech recognition system. In this paper, a method is proposed to process …

This paper proposes a new statistical model-based likelihood ratio test (LRT) VAD to obtain
reliable speech/non-speech decisions. In the proposed method, the likelihood ratio (LR) is …

Correlation of speech data is ubiquitous in real-world environments. Heterogeneous data
involving different distributions hinder federated learning (FL) significantly, which can lead to …

Voice/non-voice detection refers to the task of detecting the presence or absence of vocal
folds activity regions in the speech signal. Most of the existing state-of-the-art methods …

This paper presents a noise estimation technique based on knowledge of pitch information
for robust speech recognition. In the first stage the noise is estimated by means of …

Acoustic Models (AMs) are developed using the speech recognition toolkit Kaldi for noisy
and enhanced speech data to build an Automatic Speech Recognition (ASR) system for …

A soft decision gain modification is introduced and applied to the Ephraim-Malah gain
function based on maximum mean square error estimation (MMSE)(Ephraim, Y. and Malah …