IEEE

Improving Imbalance Learning in Audio Domain through Spectrogram-Based Augmentation

Abstract: Class imbalance is a critical concern in the machine learning domain which relies on data heavily. The model may work poorly if the underlying data are not well-formed and balanced. Several ...
GitHub

audio-spectrogram-transformer

This is the official repository of the papers "Parameter-Efficient Transfer Learning of Audio Spectrogram Transformers" [IEEE MLSP 2024] and "Efficient Fine-tuning of Audio Spectrogram Transformers ...
Nature

Deep Learning Approaches in Music Genre Classification

Deep learning methods have revolutionised the automatic categorisation of music into genres by replacing handcrafted features with data-driven representations. Central to this progress are ...
IEEE

Audio Sentiment Analysis with Spectrogram Representations and Transformer Models

Abstract: Recent advancements in the domain of computer vision have enabled the analysis of audio spectrograms. In this paper, we present a novel approach that leverages spectrogram representations ...