The work aims to propose a novel approach for automatically identifying all instruments
present in an audio excerpt using sets of individual convolutional neural networks (CNNs) …

With the continuous promotion of “smart cities” worldwide, the approach to be used in
combining smart cities with modern advanced technologies (Internet of Things, cloud …

As digital music production has become mainstream, the selection of appropriate virtual
instruments plays a crucial role in determining the quality of music. To search the musical …

Introduction Musical instrument recognition is a critical component of music information
retrieval (MIR), aimed at identifying and classifying instruments from audio recordings. This …

Audio classification and source separation are two important components in the music
industry and for audio engineering as well. The Indian classical music industry is filled with a …

Detecting instruments in a music signal is often used in database indexing, song annotation,
and creating applications for musicians and music producers. Therefore, effective methods …

The purpose of this paper is to introduce neural network-based methods that surpass state-
of-the-art (SOTA) models, either by training faster or having simpler architecture, while …

Identifying instrument activities within audio excerpts is vital in music information retrieval,
with significant implications for music cataloging and discovery. Prior deep learning …

Phoneme classification is an important part of automatic speech recognition systems.
However, attempting to classify phonemes during singing has been significantly less …

In the field of machine learning, the classification of musical instrument sounds is becoming
popular. The aim of this work is to automate the identification and categorization of diverse …