This work explores the utility of the Hilbert Spectrum (HS) of the speech signal, constructed
from its AM-FM components, or Intrinsic Mode Functions (IMFs), in characterizing speakers …

The primary objective of the presented work is to exploit the power of modified empirical
mode decomposition (M-EMD) for the denoising of ECG signals. It is well known that the …

This work explores the utility of the time-domain signal components, or the Intrinsic Mode
Functions (IMFs), of speech signals', as generated from the data-adaptive filterbank nature of …

Empirical mode decomposition (EMD) is a well-established technique to decompose
nonstationary signals into intrinsic oscillatory modes, which is essential to catch crucial …

Automatic speaker verification (ASV) systems have maximum threat from replay spoofing
attacks. High frequency regions of the underlying audio signal exhibit the phenomenon …

This paper proposes an improved ensemble empirical mode decomposition method based
on genetic algorithm to solve the mode mixing problem in empirical mode decomposition …

In this work, we explore various noise robust techniques at different stages of a Text-
Dependent Speaker Verification (TDSV) system. A speech-specific knowledge-based robust …

Single channel blind source separation (SCBSS) refers to separating multiple sources from
a mixture collected by a single sensor. Existing methods for SCBSS have limited …

The objective of this thesis work is to develop a robust text-dependent speaker verification
(TDSV) system by using robust techniques for achieving better system performance under …

This work explores the effectiveness of the Intrinsic Mode Functions (IMFs) of the speech
signal, in estimating its Glottal Closure Instants (GCIs). The IMFs of the speech signal, which …