Music Genre Classification
21 papers with code • 1 benchmarks • 1 datasets
Most implemented papers
Music Genre Classification with Paralleling Recurrent Convolutional Neural Network
Deep learning has been demonstrated its effectiveness and efficiency in music genre classification.
Convolutional Neural Network Achieves Human-level Accuracy in Music Genre Classification
Here, we propose a new method that combines knowledge of human perception study in music genre classification and the neurophysiology of the auditory system.
Texture Selection for Automatic Music Genre Classification
In this paper, we evaluate the impact of frame selection on automatic music genre classification in a bag of frames scenario.
Deep Learning Based EDM Subgenre Classification using Mel-Spectrogram and Tempogram Features
Along with the evolution of music technology, a large number of styles, or "subgenres," of Electronic Dance Music(EDM) have emerged in recent years.
Hierarchical quantum circuit representations for neural architecture search
The QCNN is a circuit model inspired by the architecture of Convolutional Neural Networks (CNNs).
Pre-training Music Classification Models via Music Source Separation
In this paper, we study whether music source separation can be used as a pre-training strategy for music representation learning, targeted at music classification tasks.
Lyrics-Based Music Genre Classification Using a Hierarchical Attention Network
In this study we apply recurrent neural network models to classify a large dataset of intact song lyrics.
Multi-label Music Genre Classification from Audio, Text, and Images Using Deep Features
Music genres allow to categorize musical items that share common characteristics.
Music Genre Classification using Masked Conditional Neural Networks
MCLNN has achieved accuracies that are competitive to state-of-the-art handcrafted attempts in addition to models based on Convolutional Neural Networks.
Bottom-up Broadcast Neural Network For Music Genre Classification
Music genre recognition based on visual representation has been successfully explored over the last years.