Papers Music Genre Recognition
“Music Genre Recognition” 태그가 달린 논문 12편 · 필터 해제
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 RecognitionSAD: Saliency-based Defenses Against Adversarial Examples
With the rise in popularity of machine and deep learning models, there is an increased focus on their vulnerability to malicious inputs. These adversarial examples drift model predictions away from the original intent of…
Adversarial AttackMusic Genre RecognitionLearning Discrete Structures for Graph Neural Networks
Graph neural networks (GNNs) are a popular class of machine learning models whose major advantage is their ability to incorporate a sparse and discrete dependency structure between data points. Unfortunately, GNNs can on…
Music Genre RecognitionNode ClassificationMachine learning and chord based feature engineering for genre prediction in popular Brazilian music
Music genre can be hard to describe: many factors are involved, such as style, music technique, and historical context. Some genres even have overlapping characteristics. Looking for a better understanding of how music g…
BIG-bench Machine LearningFeature EngineeringMusic Genre RecognitionBottom-up Broadcast Neural Network For Music Genre Classification
Music genre recognition based on visual representation has been successfully explored over the last years. Recently, there has been increasing interest in attempting convolutional neural networks (CNNs) to achieve the ta…
ClassificationDecision MakingGeneral ClassificationGenre classification+2Extended pipeline for content-based feature engineering in music genre recognition
We present a feature engineering pipeline for the construction of musical signal characteristics, to be used for the design of a supervised model for musical genre identification. The key idea is to extend the traditiona…
Feature EngineeringGeneral ClassificationMusic Genre RecognitionLearning to Recognize Musical Genre from Audio
We here summarize our experience running a challenge with open data for musical genre recognition. Those notes motivate the task and the challenge design, show some statistics about the submissions, and present the resul…
Music Genre Recognition