MIDI-VAE: Modeling Dynamics and Instrumentation of Music with Applications to Style Transfer
We introduce MIDI-VAE, a neural network model based on Variational Autoencoders that is capable of handling polyphonic music with multiple instrument tracks, as well as modeling the dynamics of music by incorporating note durations and velocities. We show that MIDI-VAE can perform style transfer on symbolic music by automatically changing pitches, dynamics and instruments of a music piece from, e.g., a Classical to a Jazz style. We evaluate the efficacy of the style transfer by training separate style validation classifiers. Our model can also interpolate between short pieces of music, produce medleys and create mixtures of entire songs. The interpolations smoothly change pitches, dynamics and instrumentation to create a harmonic bridge between two music pieces. To the best of our knowledge, this work represents the first successful attempt at applying neural style transfer to complete musical compositions.
Code (0)
등록된 구현이 없습니다.
Tasks
Style TransferSimilar Papers 제목 키워드 기반
Barwise Section Boundary Detection in Symbolic Music Using Convolutional Neural Networks
Current methods for Music Structure Analysis (MSA) focus primarily on audio data. While symbolic music can be synthesized into audio and analyzed using existing MSA techniques, such an approach does not exploit symbolic …
Boundary DetectionPopMAG: 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 ModelingMulti-view MidiVAE: Fusing Track- and Bar-view Representations for Long Multi-track Symbolic Music Generation
Variational Autoencoders (VAEs) constitute a crucial component of neural symbolic music generation, among which some works have yielded outstanding results and attracted considerable attention. Nevertheless, previous VAE…
Music GenerationBERT-like Pre-training for Symbolic Piano Music Classification Tasks
This article presents a benchmark study of symbolic piano music classification using the masked language modelling approach of the Bidirectional Encoder Representations from Transformers (BERT). Specifically, we consider…
ClassificationEmotion ClassificationLanguage ModellingMelody Extraction+1GTR-CTRL: Instrument and Genre Conditioning for Guitar-Focused Music Generation with Transformers
Recently, symbolic music generation with deep learning techniques has witnessed steady improvements. Most works on this topic focus on MIDI representations, but less attention has been paid to symbolic music generation u…
Genre classificationMusic GenerationRhythm