Papers Music Modeling
“Music Modeling” 태그가 달린 논문 38편 · 필터 해제
Exploring LLMs for South Asian Music Understanding and Generation
Recent advancements in Large Language Models (LLMs) have shown promising results in music understanding and generation tasks. However, existing works remain confined to Western tonal traditions, offering little insight i…
Music GenerationMusic ModelingDepth-Structured Music Recurrence: Budgeted Recurrent Attention for Full-Piece Symbolic Music Modeling
Long-context modeling is essential for symbolic music generation, since motif repetition and developmental variation can span thousands of musical events, yet practical workflows frequently rely on resource-limited hardw…
Music GenerationMusic ModelingPianist Transformer: Towards Expressive Piano Performance Rendering via Scalable Self-Supervised Pre-Training
Existing methods for expressive music performance rendering, a conditional generation task that aims to generate a human-like performance from a symbolic score, rely on supervised learning over small labeled datasets, wh…
Self-Supervised LearningMusic ModelingHNote: Extending YNote with Hexadecimal Encoding for Fine-Tuning LLMs in Music Modeling
Recent advances in large language models (LLMs) have created new opportunities for symbolic music generation. However, existing formats such as MIDI, ABC, and MusicXML are either overly complex or structurally inconsiste…
Music GenerationMusic ModelingSLEEPING-DISCO 9M: A large-scale pre-training dataset for generative music modeling
We present Sleeping-DISCO 9M, a large-scale pre-training dataset for music and song. To the best of our knowledge, there are no open-source high-quality dataset representing popular and well-known songs for generative mu…
Music CaptioningMusic ModelingSinging Voice SynthesisFrechet Music Distance: A Metric For Generative Symbolic Music Evaluation
In this paper we introduce the Frechet Music Distance (FMD), a novel evaluation metric for generative symbolic music models, inspired by the Frechet Inception Distance (FID) in computer vision and Frechet Audio Distance …
FADMusic GenerationMusic ModelingMuPT: A Generative Symbolic Music Pretrained Transformer
In this paper, we explore the application of Large Language Models (LLMs) to the pre-training of music. While the prevalent use of MIDI in music modeling is well-established, our findings suggest that LLMs are inherently…
Music GenerationMusic ModelingImpact of time and note duration tokenizations on deep learning symbolic music modeling
Symbolic music is widely used in various deep learning tasks, including generation, transcription, synthesis, and Music Information Retrieval (MIR). It is mostly employed with discrete models like Transformers, which req…
Emotion ClassificationInformation RetrievalMusic GenerationMusic Information Retrieval+3A Domain-Knowledge-Inspired Music Embedding Space and a Novel Attention Mechanism for Symbolic Music Modeling
Following the success of the transformer architecture in the natural language domain, transformer-like architectures have been widely applied to the domain of symbolic music recently. Symbolic music and text, however, ar…
Music GenerationMusic ModelingLow-Rank Constraints for Fast Inference in Structured Models
Structured distributions, i.e. distributions over combinatorial spaces, are commonly used to learn latent probabilistic representations from observed data. However, scaling these models is bottlenecked by the high comput…
Language ModelingLanguage ModellingMusic ModelingGates Are Not What You Need in RNNs
Recurrent neural networks have flourished in many areas. Consequently, we can see new RNN cells being developed continuously, usually by creating or using gates in a new, original way. But what if we told you that gates …
Language ModelingLanguage ModellingMusic ModelingSentiment AnalysisMuSLCAT: Multi-Scale Multi-Level Convolutional Attention Transformer for Discriminative Music Modeling on Raw Waveforms
In this work, we aim to improve the expressive capacity of waveform-based discriminative music networks by modeling both sequential (temporal) and hierarchical information in an efficient end-to-end architecture. We pres…
Music ModelingMusic TaggingRethinking Neural Operations for Diverse Tasks
An important goal of AutoML is to automate-away the design of neural networks on new tasks in under-explored domains. Motivated by this goal, we study the problem of enabling users to discover the right neural operations…
AutoMLImage ClassificationInductive BiasMusic Modeling+2Recurrently Controlling a Recurrent Network with Recurrent Networks Controlled by More Recurrent Networks
This paper explores an intriguing idea of recursively parameterizing recurrent nets. Simply speaking, this refers to recurrently controlling a recurrent network with recurrent networks controlled by recurrent networks. T…
Code GenerationInductive BiasMachine TranslationMusic Modeling+2PopMAG: Pop Music Accompaniment Generation
In pop music, accompaniments are usually played by multiple instruments (tracks) such as drum, bass, string and guitar, and can make a song more expressive and contagious by arranging together with its melody. Previous w…
Music ModelingPop Music Transformer: Beat-based Modeling and Generation of Expressive Pop Piano Compositions
A great number of deep learning based models have been recently proposed for automatic music composition. Among these models, the Transformer stands out as a prominent approach for generating expressive classical piano p…
Music ModelingLearning Style-Aware Symbolic Music Representations by Adversarial Autoencoders
We address the challenging open problem of learning an effective latent space for symbolic music data in generative music modeling. We focus on leveraging adversarial regularization as a flexible and natural mean to imbu…
Music ModelingMetagross: Meta Gated Recursive Controller Units for Sequence Modeling
This paper proposes Metagross (Meta Gated Recursive Controller), a new neural sequence modeling unit. Our proposed unit is characterized by recursive parameterization of its gating functions, i.e., gating mechanisms of M…
Code GenerationInductive BiasMachine TranslationMusic Modeling+2Improving Polyphonic Music Models with Feature-Rich Encoding
This paper explores sequential modelling of polyphonic music with deep neural networks. While recent breakthroughs have focussed on network architecture, we demonstrate that the representation of the sequence can make an…
Music GenerationMusic ModelingGating Revisited: Deep Multi-layer RNNs That Can Be Trained
We propose a new STAckable Recurrent cell (STAR) for recurrent neural networks (RNNs), which has fewer parameters than widely used LSTM and GRU while being more robust against vanishing or exploding gradients. Stacking r…
Action RecognitionAction Recognition In VideosLanguage ModellingMusic Modeling+1