Music Generation
132 papers with code • 0 benchmarks • 24 datasets
Music Generation is the task of generating music or music-like sounds from a model or algorithm. The goal is to produce a sequence of notes or sound events that are similar to existing music in some way, such as having the same style, genre, or mood.
Benchmarks
These leaderboards are used to track progress in Music Generation
Libraries
Use these libraries to find Music Generation models and implementationsDatasets
NSynth
MAESTRO
MusicCaps
JSB Chorales
Music21
URMP
POP909
MuseData
EMOPIA
Latest papers
Mustango: Toward Controllable Text-to-Music Generation
Through extensive experiments, we show that the quality of the music generated by Mustango is state-of-the-art, and the controllability through music-specific text prompts greatly outperforms other models such as MusicGen and AudioLDM2.
Exploring Variational Auto-Encoder Architectures, Configurations, and Datasets for Generative Music Explainable AI
bbanar2/exploring_xai_in_genmus_via_lsr
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This paper contributes a systematic examination of the impact that different combinations of Variational Auto-Encoder models (MeasureVAE and AdversarialVAE), configurations of latent space in the AI model (from 4 to 256 latent dimensions), and training datasets (Irish folk, Turkish folk, Classical, and pop) have on music generation performance when 2 or 4 meaningful musical attributes are imposed on the generative model.
Music ControlNet: A model similar to SD ControlNetD that can accurately control music generation
johndpope/MusicControlNet
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. 2023
While the image-domain Uni-ControlNet method already allows generation with any subset of controls, we devise a new strategy to allow creators to input controls that are only partially specified in time.
Video2Music: Suitable Music Generation from Videos using an Affective Multimodal Transformer model
These distinct features are then employed as guiding input to our music generation model.
JEN-1 Composer: A Unified Framework for High-Fidelity Multi-Track Music Generation
0417keito/JEN-1-COMPOSER-pytorch
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With rapid advances in generative artificial intelligence, the text-to-music synthesis task has emerged as a promising direction for music generation from scratch.
miditok: A Python package for MIDI file tokenization
Natooz/MidiTok
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Recent progress in natural language processing has been adapted to the symbolic music modality.
Content-based Controls For Music Large Language Modeling
We aim to further equip the models with direct and content-based controls on innate music languages such as pitch, chords and drum track.
Unsupervised Lead Sheet Generation via Semantic Compression
Lead sheets have become commonplace in generative music research, being used as an initial compressed representation for downstream tasks like multitrack music generation and automatic arrangement.
CoCoFormer: A controllable feature-rich polyphonic music generation method
This paper explores the modeling method of polyphonic music sequence.
Impact of time and note duration tokenizations on deep learning symbolic music modeling
Natooz/music-modeling-time-duration
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Symbolic music is widely used in various deep learning tasks, including generation, transcription, synthesis, and Music Information Retrieval (MIR).
