Music Genre Recognition
2개 벤치마크 · 논문 12편 · 이 태스크의 논문 보기 →
Benchmarks
Most implemented
Learning to Recognize Musical Genre from Audio
Learning Discrete Structures for Graph Neural Networks
Wasserstein Barycenter for Multi-Source Domain Adaptation
Client-driven Animated GIF Generation Framework Using an Acoustic Feature
Machine learning and chord based feature engineering for genre prediction in popular Brazilian music
Bottom-up Broadcast Neural Network For Music Genre Classification
Papers
Beyond Mapping : Domain-Invariant Representations via Spectral Embedding of Optimal Transport Plans
Distributional shifts between training and inference time data remain a central challenge in machine learning, often leading to poor performance. It motivated the study of principled approaches for domain alignment, such…
Unsupervised Domain AdaptationMusic Genre RecognitionCompressing Quaternion Convolutional Neural Networks for Audio Classification
Conventional Convolutional Neural Networks (CNNs) in the real domain have been widely used for audio classification. However, their convolution operations process multi-channel inputs independently, limiting the ability …
Environmental Sound ClassificationSpeech Emotion RecognitionMusic Genre RecognitionKnowledge DistillationComparison of spectrogram scaling in multi-label Music Genre Recognition
As the accessibility and ease-of-use of digital audio workstations increases, so does the quantity of music available to the average listener; additionally, differences between genres are not always well defined and can …
Music Genre RecognitionComparing the Accuracy of Deep Neural Networks (DNN) and Convolutional Neural Network (CNN) in Music Genre Recognition (MGR): Experiments on Kurdish Music
Musicologists use various labels to classify similar music styles under a shared title. But, non-specialists may categorize music differently. That could be through finding patterns in harmony, instruments, and form of t…
Music Genre RecognitionWasserstein Barycenter for Multi-Source Domain Adaptation
Multi-source domain adaptation is a key technique that allows a model to be trained on data coming from various probability distribution. To overcome the challenges posed by this learning scenario, we propose a metho…
Domain AdaptationFace RecognitionMulti-Source Unsupervised Domain AdaptationMusic Genre Recognition+2Client-driven Animated GIF Generation Framework Using an Acoustic Feature
This paper proposes a novel, lightweight method to generate animated graphical interchange format images (GIFs) using the computational resources of a client device. The method analyzes an acoustic feature from the clima…
Animated GIF GenerationMusic Genre Recognition