Daniel Stoller

According to our database, Daniel Stoller authored at least 17 papers between 2013 and 2023.

Collaborative distances:

• Dijkstra number of five.
• Erdős number of four.

2023

LLark: A Multimodal Foundation Model for Music.

Josh Gardner, Simon Durand, Daniel Stoller, Rachel M. Bittner

CoRR, 2023

Contrastive Learning-Based Audio to Lyrics Alignment for Multiple Languages.

Simon Durand, Daniel Stoller, Sebastian Ewert

Proceedings of the IEEE International Conference on Acoustics, 2023

2022

Few-Shot Musical Source Separation.

Yu Wang, Daniel Stoller, Rachel M. Bittner, Juan Pablo Bello

Proceedings of the IEEE International Conference on Acoustics, 2022

2020

Deep learning for music information retrieval in limited data scenarios.

Daniel Stoller

PhD thesis, 2020

Seq-U-Net: A One-Dimensional Causal U-Net for Efficient Sequence Modelling.

Daniel Stoller, Mi Tian, Sebastian Ewert, Simon Dixon

Proceedings of the Twenty-Ninth International Joint Conference on Artificial Intelligence, 2020

Training Generative Adversarial Networks from Incomplete Observations using Factorised Discriminators.

Daniel Stoller, Sebastian Ewert, Simon Dixon

Proceedings of the 8th International Conference on Learning Representations, 2020

2019

GAN-based Generation and Automatic Selection of Explanations for Neural Networks.

Saumitra Mishra, Daniel Stoller, Emmanouil Benetos, Bob L. Sturm, Simon Dixon

CoRR, 2019

A Comparative Study of Neural Models for Polyphonic Music Sequence Transduction.

Adrien Ycart, Daniel Stoller, Emmanouil Benetos

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

Ensemble Models for Spoofing Detection in Automatic Speaker Verification.

Bhusan Chettri, Daniel Stoller, Veronica Morfi, Marco A. Martínez Ramírez, Emmanouil Benetos, Bob L. Sturm

Proceedings of the Interspeech 2019, 2019

End-to-end Lyrics Alignment for Polyphonic Music Using an Audio-to-character Recognition Model.

Daniel Stoller, Simon Durand, Sebastian Ewert

Proceedings of the IEEE International Conference on Acoustics, 2019

Evolutionary Multi-objective Training Set Selection of Data Instances and Augmentations for Vocal Detection.

Igor Vatolkin, Daniel Stoller

Proceedings of the Computational Intelligence in Music, Sound, Art and Design, 2019

2018

Detection of Cut-Points for Automatic Music Rearrangement.

Daniel Stoller, Vincent Akkermans, Simon Dixon

Proceedings of the 28th IEEE International Workshop on Machine Learning for Signal Processing, 2018

Wave-U-Net: A Multi-Scale Neural Network for End-to-End Audio Source Separation.

Daniel Stoller, Sebastian Ewert, Simon Dixon

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

Adversarial Semi-Supervised Audio Source Separation Applied to Singing Voice Extraction.

Daniel Stoller, Sebastian Ewert, Simon Dixon

Proceedings of the 2018 IEEE International Conference on Acoustics, 2018

Jointly Detecting and Separating Singing Voice: A Multi-Task Approach.

Daniel Stoller, Sebastian Ewert, Simon Dixon

Proceedings of the Latent Variable Analysis and Signal Separation, 2018

2016

Analysis and Classification of Phonation Modes In Singing.

Daniel Stoller, Simon Dixon

Proceedings of the 17th International Society for Music Information Retrieval Conference, 2016

2013

Impact of Frame Size and Instrumentation on Chroma-Based Automatic Chord Recognition.

Daniel Stoller, Matthias Mauch, Igor Vatolkin, Claus Weihs

Proceedings of the Data Science, 2013