Stefan Lattner

CoRR, 2024

2023

Self-Supervised Music Source Separation Using Vector-Quantized Source Category Estimates.

[BibT_eX]

[DOI]

Marco Pasini

George Fazekas

CoRR, 2023

Singer Identity Representation Learning Using Self-Supervised Techniques.

[BibT_eX]

[DOI]

Bernardo Torres

Proceedings of the 24th International Society for Music Information Retrieval Conference, 2023

PESTO: Pitch Estimation With Self-Supervised Transposition-Equivariant Objective.

[BibT_eX]

[DOI]

Proceedings of the 24th International Society for Music Information Retrieval Conference, 2023

Exploring Sampling Techniques for Generating Melodies With a Transformer Language Model.

[BibT_eX]

[DOI]

Mathias Rose Bjare

Proceedings of the 24th International Society for Music Information Retrieval Conference, 2023

2022

On the Development and Practice of AI Technology for Contemporary Popular Music Production.

[BibT_eX]

[DOI]

Trans. Int. Soc. Music. Inf. Retr., 2022

Differentiable Short-Term Models for Efficient Online Learning and Prediction in Monophonic Music.

[BibT_eX]

[DOI]

Mathias Rose Bjare

Trans. Int. Soc. Music. Inf. Retr., 2022

On the Typicality of Musical Sequences.

[BibT_eX]

[DOI]

Mathias Rose Bjare

CoRR, 2022

Stochastic Restoration of Heavily Compressed Musical Audio using Generative Adversarial Networks.

[BibT_eX]

[DOI]

CoRR, 2022

DrumGAN VST: A Plugin for Drum Sound Analysis/Synthesis With Autoencoding Generative Adversarial Networks.

[BibT_eX]

[DOI]

CoRR, 2022

SampleMatch: Drum Sample Retrieval by Musical Context.

[BibT_eX]

[DOI]

Proceedings of the 23rd International Society for Music Information Retrieval Conference, 2022

2021

VQCPC-GAN: Variable-Length Adversarial Audio Synthesis Using Vector-Quantized Contrastive Predictive Coding.

[BibT_eX]

[DOI]

Proceedings of the IEEE Workshop on Applications of Signal Processing to Audio and Acoustics, 2021

DarkGAN: Exploiting Knowledge Distillation for Comprehensible Audio Synthesis With GANs.

[BibT_eX]

[DOI]

Proceedings of the 22nd International Society for Music Information Retrieval Conference, 2021

2020

Modeling Musical Structure with Artificial Neural Networks.

[BibT_eX]

[DOI]

CoRR, 2020

DRUMGAN: Synthesis of Drum Sounds with Timbral Feature Conditioning Using Generative Adversarial Networks.

[BibT_eX]

[DOI]

Proceedings of the 21th International Society for Music Information Retrieval Conference, 2020

Comparing Representations for Audio Synthesis Using Generative Adversarial Networks.

[BibT_eX]

[DOI]

Proceedings of the 28th European Signal Processing Conference, 2020

2019

High-Level Control of Drum Track Generation Using Learned Patterns of Rhythmic Interaction.

[BibT_eX]

[DOI]

Proceedings of the 2019 IEEE Workshop on Applications of Signal Processing to Audio and Acoustics, 2019

Learning Complex Basis Functions for Invariant Representations of Audio.

[BibT_eX]

[DOI]

Monika Dörfler

Andreas Arzt

Proceedings of the 20th International Society for Music Information Retrieval Conference, 2019

2018

Learning Transposition-Invariant Interval Features from Symbolic Music and Audio.

[BibT_eX]

[DOI]

CoRR, 2018

Learning Interval Representations from Polyphonic Music Sequences.

[BibT_eX]

[DOI]

Proceedings of the 19th International Society for Music Information Retrieval Conference, 2018

A Predictive Model for Music based on Learned Interval Representations.

[BibT_eX]

[DOI]

Proceedings of the 19th International Society for Music Information Retrieval Conference, 2018

Audio-to-Score Alignment using Transposition-invariant Features.

[BibT_eX]

[DOI]

Andreas Arzt

Proceedings of the 19th International Society for Music Information Retrieval Conference, 2018

2017

Learning Musical Relations using Gated Autoencoders.

[BibT_eX]

[DOI]

CoRR, 2017

Improving Content-Invariance in Gated Autoencoders for 2D and 3D Object Rotation.

[BibT_eX]

[DOI]

CoRR, 2017

2016

Imposing higher-level Structure in Polyphonic Music Generation using Convolutional Restricted Boltzmann Machines and Constraints.

[BibT_eX]

[DOI]

CoRR, 2016

2015

Probabilistic Segmentation of Musical Sequences Using Restricted Boltzmann Machines.

[BibT_eX]

[DOI]

Carlos Eduardo Cancino Chacón

Kat Agres

Proceedings of the Mathematics and Computation in Music - 5th International Conference, 2015

Pseudo-Supervised Training Improves Unsupervised Melody Segmentation.

[BibT_eX]

[DOI]

Carlos Eduardo Cancino Chacón

Carlos Eduardo Cancino Chacón

Proceedings of the Twenty-Fourth International Joint Conference on Artificial Intelligence, 2015

A Computational Approach to Modelling the Perception of Pitch and Tonality in Music.

[BibT_eX]

[DOI]

Proceedings of the 37th Annual Meeting of the Cognitive Science Society, 2015

2014

Developing Tonal Perception through Unsupervised Learning.

[BibT_eX]

[DOI]