An audio indexing system aims at describing audio content by identifying, labeling, or
categorizing different acoustic events. Since the resulting audio classification and indexing …

Spiking Neural Networks (SNNs), known for their potential to enable low energy
consumption and computational cost, can bring significant advantages to the realm of …

For several decades, auditory neuroscientists have used spectro-temporal encoding models
to understand how neurons in the auditory system represent sound. Derived from early …

Auditory filter models have a history of over a hundred years, with explicit bio-mimetic
inspiration at many stages along the way. From passive analogue electric delay line models …

This paper presents a pathological voice identification system employing signal processing
techniques through cochlear implant models. The fundamentals of the biological process for …

This paper introduces a new dictionary design method for sparse coding of a class of
signals. It has been shown that one can sparsely approximate some natural signals using an …

Current approaches to speech emotion recognition focus on speech features that can
capture the emotional content of a speech signal. Mel Frequency Cepstral Coefficients …

Audio signal processing and its classification dates back to the past century. From speech
recognition to speaker recognition and from speech to text conversion to music generation, a …

This paper presents a digital implementation of the Cascade of Asymmetric Resonators with
Fast-Acting Compression (CAR-FAC) cochlear model. The CAR part simulates the basilar …

Crying is one of the means of communication for a newborn. Newborn cry signals convey
precious information about the newborn's health condition and their emotions. In this study …