This paper proposes a 1D residual convolutional neural network (CNN) architecture for
music genre classification and compares it with other recent 1D CNN architectures. The 1D …

In this paper we focus on the automatic identification of bird species from their audio
recorded song. Bird monitoring is important to perform several tasks, such as to evaluate the …

The trend for listening to music online has greatly increased over the past decade due to the
number of online musical tracks. The large music databases of music libraries that are …

Automatic music genre classification is a prevailing pattern recognition task, and many
algorithms have been proposed for accurate classification. Considering that the genre of …

With increasing amounts of music being available in digital form, research in music
information retrieval has turned into a dominant field to support organization of and easy …

This paper shows the susceptibility of spectrogram-based audio classifiers to adversarial
attacks and the transferability of such attacks to audio waveforms. Some commonly used …

This paper presents research on music genre recognition. It is a crucial task because there
are millions of songs in the online databases. Classifying them by a human being is …

This paper presents two novel hierarchical classification methods which are extensions of a
previously proposed selective classifier top-down approach, which consists of selecting …

The aim of this work is to predict the genres of songs by using machine learning techniques.
For this purpose, feature extraction is done by using signal processing techniques, then …

Video game genre classification has long been a focusing perspective in game studies
domain. Despite the commonly acknowledged usefulness of genre classification, scholars in …