Papers Music Genre Classification
“Music Genre Classification” 태그가 달린 논문 56편 · 필터 해제
M2D2: Exploring General-purpose Audio-Language Representations Beyond CLAP
Contrastive language-audio pre-training (CLAP) has addressed audio-language tasks such as audio-text retrieval by aligning audio and text in a common feature space. While CLAP addresses general audio-language tasks, its …
Audio captioningAudio ClassificationAudio TaggingAudio to Text Retrieval+13BAN: Neuroanatomical Aligning in Auditory Recognition between Artificial Neural Network and Human Cortex
Drawing inspiration from neurosciences, artificial neural networks (ANNs) have evolved from shallow architectures to highly complex, deep structures, yielding exceptional performance in auditory recognition tasks. Howeve…
Genre classificationMusic Genre ClassificationMasked Latent Prediction and Classification for Self-Supervised Audio Representation Learning
Recently, self-supervised learning methods based on masked latent prediction have proven to encode input data into powerful representations. However, during training, the learned latent space can be further transformed t…
Audio ClassificationAudio TaggingClassificationEnvironmental Sound Classification+9Multi-label Cross-lingual automatic music genre classification from lyrics with Sentence BERT
Music genres are shaped by both the stylistic features of songs and the cultural preferences of artists' audiences. Automatic classification of music genres using lyrics can be useful in several applications such as reco…
ClassificationGenre classificationInformation RetrievalMusic Genre Classification+4Music Genre Classification: Ensemble Learning with Subcomponents-level Attention
Music Genre Classification is one of the most popular topics in the fields of Music Information Retrieval (MIR) and digital signal processing. Deep Learning has emerged as the top performer for classifying music genres a…
Ensemble LearningGenre classificationInformation RetrievalMusic Genre Classification+1Attention-guided Spectrogram Sequence Modeling with CNNs for Music Genre Classification
Music genre classification is a critical component of music recommendation systems, generation algorithms, and cultural analytics. In this work, we present an innovative model for classifying music genres using attention…
ClassificationGenre classificationMusic Genre ClassificationMusic Recommendation+1Audio Processing using Pattern Recognition for Music Genre Classification
This project explores the application of machine learning techniques for music genre classification using the GTZAN dataset, which contains 100 audio files per genre. Motivated by the growing demand for personalized musi…
Genre classificationMusic Genre ClassificationMusic RecommendationRecommendation SystemsMusic Genre Classification using Large Language Models
This paper exploits the zero-shot capabilities of pre-trained large language models (LLMs) for music genre classification. The proposed approach splits audio signals into 20 ms chunks and processes them through convoluti…
ClassificationGenre classificationInformation RetrievalMusic Genre Classification+2Enhancing Music Genre Classification through Multi-Algorithm Analysis and User-Friendly Visualization
The aim of this study is to teach an algorithm how to recognize different types of music. Users will submit songs for analysis. Since the algorithm hasn't heard these songs before, it needs to figure out what makes each …
Genre classificationMusic Genre ClassificationRhythmMusic Genre Classification: Training an AI model
Music genre classification is an area that utilizes machine learning models and techniques for the processing of audio signals, in which applications range from content recommendation systems to music recommendation syst…
ClassificationGenre classificationmodelMusic Genre Classification+2Music Genre Classification: A Comparative Analysis of CNN and XGBoost Approaches with Mel-frequency cepstral coefficients and Mel Spectrograms
In recent years, various well-designed algorithms have empowered music platforms to provide content based on one's preferences. Music genres are defined through various aspects, including acoustic features and cultural c…
Genre classificationModel SelectionMusic Genre ClassificationPre-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. To this end, we first pre-train U-Net networks und…
ClassificationGenre classificationMusic Auto-TaggingMusic Classification+3Exploring Music Genre Classification: Algorithm Analysis and Deployment Architecture
Music genre classification has become increasingly critical with the advent of various streaming applications. Nowadays, we find it impossible to imagine using the artist's name and song title to search for music in a so…
ClassificationGenre classificationMusic Genre ClassificationMusic Genre Classification with ResNet and Bi-GRU Using Visual Spectrograms
Music recommendation systems have emerged as a vital component to enhance user experience and satisfaction for the music streaming services, which dominates music consumption. The key challenge in improving these recomme…
Classificationfeature selectionGenre classificationMusic Genre Classification+2Multi-Source Contrastive Learning from Musical Audio
Contrastive learning constitutes an emerging branch of self-supervised learning that leverages large amounts of unlabeled data, by learning a latent space, where pairs of different views of the same sample are associated…
CoLAContrastive LearningGenre classificationMusic Auto-Tagging+4Effective Audio Classification Network Based on Paired Inverse Pyramid Structure and Dense MLP Block
Recently, massive architectures based on Convolutional Neural Network (CNN) and self-attention mechanisms have become necessary for audio classification. While these techniques are state-of-the-art, these works' effectiv…
Audio ClassificationClassificationData AugmentationEnvironmental Sound Classification+3Integrated Parameter-Efficient Tuning for General-Purpose Audio Models
The advent of hyper-scale and general-purpose pre-trained models is shifting the paradigm of building task-specific models for target tasks. In the field of audio research, task-agnostic pre-trained models with high tran…
Genre classificationKeyword SpottingMusic Genre ClassificationSpeaker Verification+1Convolution channel separation and frequency sub-bands aggregation for music genre classification
In music, short-term features such as pitch and tempo constitute long-term semantic features such as melody and narrative. A music genre classification (MGC) system should be able to analyze these features. In this resea…
Genre classificationMusic Genre ClassificationLow-Resource Music Genre Classification with Cross-Modal Neural Model Reprogramming
Transfer learning (TL) approaches have shown promising results when handling tasks with limited training data. However, considerable memory and computational resources are often required for fine-tuning pre-trained neura…
ClassificationGenre classificationMusic ClassificationMusic Genre Classification+1Masked Modeling Duo: Learning Representations by Encouraging Both Networks to Model the Input
Masked Autoencoders is a simple yet powerful self-supervised learning method. However, it learns representations indirectly by reconstructing masked input patches. Several methods learn representations directly by predic…
Audio ClassificationAudio TaggingKeyword SpottingKeyword Spotting on Google Speech Commands+3