This work reviews the advancements in the non-conventional analysis of speech signals,
particularly from an AM-FM analysis point of view. The benefits of such an analysis, as …

This paper provides a review of the Teager–Kaiser (TK) energy operator and its extensions
for signals and images processing. This class of operators possesses simplicity and good …

Most of the real-life signals are non-stationary in nature. The examples of such signals
include biomedical signals, communication signals, speech, earthquake signals, vibration …

Multimodal streams of sensory information are naturally parsed and integrated by humans
using signal-level feature extraction and higher level cognitive processes. Detection of …

This paper presents an experimental evaluation of different features for use in speaker
identification. The features are tested using speech data provided by the chains corpus, in a …

Fake audio detection is expected to become an important research area in the field of smart
speakers such as Google Home, Amazon Echo and chatbots developed for these platforms …

The objective of this paper is to establish the importance of phase of analytic signal of
speech, referred to as the analytic phase, in human perception of speaker identity, as well as …

Most of the features used by modern automatic speech recognition systems, such as mel-
frequency cepstral coefficients (MFCC) and perceptual linear predictive (PLP) coefficients …

Prevention of malicious spoofing attacks is currently acknowledged as a priority area of
investigation for the deployment of automatic speaker verification systems. Various features …

Time-frequency distributions that evaluate the signal's energy content both in the time and
frequency domains are indispensable signal processing tools, especially, for nonstationary …