Genre classification
46 papers with code • 2 benchmarks • 6 datasets
Genre classification is the process of grouping objects together based on defined similarities such as shape, pixel, location, or intensity.
FMA
MuMu
Moviescope
Trailers12k
PTVD
Most implemented papers
Explaining Deep Convolutional Neural Networks on Music Classification
Deep convolutional neural networks (CNNs) have been actively adopted in the field of music information retrieval, e. g. genre classification, mood detection, and chord recognition.
Column Networks for Collective Classification
CLN has many desirable theoretical properties: (i) it encodes multi-relations between any two instances; (ii) it is deep and compact, allowing complex functions to be approximated at the network level with a small set of free parameters; (iii) local and relational features are learned simultaneously; (iv) long-range, higher-order dependencies between instances are supported naturally; and (v) crucially, learning and inference are efficient, linear in the size of the network and the number of relations.
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
fadymedhat/MCLNN
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MCLNN has achieved accuracies that are competitive to state-of-the-art handcrafted attempts in addition to models based on Convolutional Neural Networks.
Transfer Learning of Artist Group Factors to Musical Genre Classification
mmwebster/variable-transfer-genre
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The automated recognition of music genres from audio information is a challenging problem, as genre labels are subjective and noisy.
Utilizing a Transparency-driven Environment toward Trusted Automatic Genre Classification: A Case Study in Journalism History
With the growing abundance of unlabeled data in real-world tasks, researchers have to rely on the predictions given by black-boxed computational models.
Bottom-up Broadcast Neural Network For Music Genre Classification
Music genre recognition based on visual representation has been successfully explored over the last years.
Recognizing Musical Entities in User-generated Content
Recognizing Musical Entities is important for Music Information Retrieval (MIR) since it can improve the performance of several tasks such as music recommendation, genre classification or artist similarity.
Machine learning for music genre: multifaceted review and experimentation with audioset
Music genre classification is one of the sub-disciplines of music information retrieval (MIR) with growing popularity among researchers, mainly due to the already open challenges.
