Papers Music Classification
“Music Classification” 태그가 달린 논문 52편 · 필터 해제
Moonbeam: A MIDI Foundation Model Using Both Absolute and Relative Music Attributes
Moonbeam is a transformer-based foundation model for symbolic music, pretrained on a large and diverse collection of MIDI data totaling 81.6K hours of music and 18 billion tokens. Moonbeam incorporates music-domain induc…
Music ClassificationMusic GenerationProgressive Rock Music Classification
This study investigates the classification of progressive rock music, a genre characterized by complex compositions and diverse instrumentation, distinct from other musical styles. Addressing this Music Information Retri…
Audio ClassificationClassificationDimensionality ReductionGenre classification+3M2D2: 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+13EVolutionary Independent DEtermiNistiC Explanation
The widespread use of artificial intelligence deep neural networks in fields such as medicine and engineering necessitates understanding their decision-making processes. Current explainability methods often produce incon…
DiagnosticExplainable artificial intelligenceExplainable Artificial Intelligence (XAI)Genre classification+1Arabic Music Classification and Generation using Deep Learning
This paper proposes a machine learning approach for classifying classical and new Egyptian music by composer and generating new similar music. The proposed system utilizes a convolutional neural network (CNN) for classif…
ClassificationDeep LearningMusic ClassificationMusic Recommendation+1CLaMP 2: Multimodal Music Information Retrieval Across 101 Languages Using Large Language Models
Challenges in managing linguistic diversity and integrating various musical modalities are faced by current music information retrieval systems. These limitations reduce their effectiveness in a global, multimodal music …
Contrastive LearningDiversityInformation RetrievalMusic Classification+2Benchmarking Sub-Genre Classification For Mainstage Dance Music
Music classification, with a wide range of applications, is one of the most prominent tasks in music information retrieval. To address the absence of comprehensive datasets and high-performing methods in the classificati…
BenchmarkingClassificationGenre classificationInformation Retrieval+3Music Era Recognition Using Supervised Contrastive Learning and Artist Information
Does popular music from the 60s sound different than that of the 90s? Prior study has shown that there would exist some variations of patterns and regularities related to instrumentation changes and growing loudness acro…
Contrastive LearningMusic ClassificationHearing-Loss Compensation Using Deep Neural Networks: A Framework and Results From a Listening Test
This article investigates the use of deep neural networks (DNNs) for hearing-loss compensation. Hearing loss is a prevalent issue affecting millions of people worldwide, and conventional hearing aids have limitations in …
Music ClassificationSpeaker Identificationspeech-recognitionSpeech RecognitionSignificance of Chirp MFCC as a Feature in Speech and Audio Applications
A novel feature, based on the chirp z-transform, that offers an improved representation of the underlying true spectrum is proposed. This feature, the chirp MFCC, is derived by computing the Mel frequency cepstral coeffi…
Music ClassificationSpeaker IdentificationPre-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+3MusicAgent: An AI Agent for Music Understanding and Generation with Large Language Models
AI-empowered music processing is a diverse field that encompasses dozens of tasks, ranging from generation tasks (e.g., timbre synthesis) to comprehension tasks (e.g., music classification). For developers and amateurs, …
AI AgentMusic ClassificationAudio Embeddings as Teachers for Music Classification
Music classification has been one of the most popular tasks in the field of music information retrieval. With the development of deep learning models, the last decade has seen impressive improvements in a wide range of c…
ClassificationInformation RetrievalInstrument RecognitionKnowledge Distillation+5Toward Leveraging Pre-Trained Self-Supervised Frontends for Automatic Singing Voice Understanding Tasks: Three Case Studies
Automatic singing voice understanding tasks, such as singer identification, singing voice transcription, and singing technique classification, benefit from data-driven approaches that utilize deep learning techniques. Th…
DiversityMusic ClassificationSelf-Supervised LearningSinger IdentificationCLaMP: Contrastive Language-Music Pre-training for Cross-Modal Symbolic Music Information Retrieval
We introduce CLaMP: Contrastive Language-Music Pre-training, which learns cross-modal representations between natural language and symbolic music using a music encoder and a text encoder trained jointly with a contrastiv…
Data AugmentationInformation RetrievalMusic ClassificationMusic Information Retrieval+3Symbolic Music Structure Analysis with Graph Representations and Changepoint Detection Methods
Music Structure Analysis is an open research task in Music Information Retrieval (MIR). In the past, there have been several works that attempt to segment music into the audio and symbolic domains, however, the identific…
Information RetrievalMusic ClassificationMusic GenerationMusic Information RetrievalToward Universal Text-to-Music Retrieval
This paper introduces effective design choices for text-to-music retrieval systems. An ideal text-based retrieval system would support various input queries such as pre-defined tags, unseen tags, and sentence-level descr…
Music ClassificationRetrievalSentenceTAGSpectNet : End-to-End Audio Signal Classification Using Learnable Spectrograms
Pattern recognition from audio signals is an active research topic encompassing audio tagging, acoustic scene classification, music classification, and other areas. Spectrogram and mel-frequency cepstral coefficients (MF…
Acoustic Scene ClassificationAnomaly DetectionAudio ClassificationAudio Tagging+4Low-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+1Learning Music Representations with wav2vec 2.0
Learning music representations that are general-purpose offers the flexibility to finetune several downstream tasks using smaller datasets. The wav2vec 2.0 speech representation model showed promising results in many dow…
Music Classification