| Wave-U-Net: A Multi-Scale Neural Network for End-to-End Audio Source Separation D Stoller, S Ewert, S Dixon IEEE International Conference on Acoustics, Speech, and Signal Processing …, 2018 | 786 | 2018 |
| End-to-end Lyrics Alignment for Polyphonic Music Using An Audio-to-Character Recognition Model S Stoller, Daniel and Durand, Simon and Ewert Proceedings of the IEEE International Conference on Acoustics, Speech, and …, 2019 | 114* | 2019 |
| Ensemble Models for Spoofing Detection in Automatic Speaker Verification B Chettri, D Stoller, V Morfi, MAM Ramírez, E Benetos, BL Sturm Proceedings of Interspeech, 1018-1022, 2019 | 100 | 2019 |
| Adversarial Semi-Supervised Audio Source Separation applied to Singing Voice Extraction D Stoller, S Ewert, S Dixon IEEE International Conference on Acoustics, Speech, and Signal Processing …, 2018 | 88 | 2018 |
| Seq-U-Net: A One-Dimensional Causal U-Net for Efficient Sequence Modelling D Stoller, M Tian, S Ewert, S Dixon arXiv preprint arXiv:1911.06393, 2019 | 33 | 2019 |
| Jointly detecting and separating singing voice: A multi-task approach D Stoller, S Ewert, S Dixon Latent Variable Analysis and Signal Separation: 14th International …, 2018 | 28 | 2018 |
| A deep learning approach to intelligent drum mixing with the wave-u-net M Martinez Ramirez, D Stoller, D Moffat Audio Engineering Society, 2021 | 24 | 2021 |
| Analysis and classification of phonation modes in singing D Stoller, S Dixon International Conference for Music Information Retrieval (ISMIR) 17, 80-86, 2016 | 20 | 2016 |
| Few-shot musical source separation Y Wang, D Stoller, RM Bittner, JP Bello ICASSP 2022-2022 IEEE International Conference on Acoustics, Speech and …, 2022 | 16 | 2022 |
| GAN-based Generation and Automatic Selection of Explanations for Neural Networks S Mishra, D Stoller, E Benetos, BL Sturm, S Dixon ICLR 2019 SafeML Workshop, 2019 | 11 | 2019 |
| Contrastive Learning-Based Audio to Lyrics Alignment for Multiple Languages S Durand, D Stoller, S Ewert ICASSP 2023-2023 IEEE International Conference on Acoustics, Speech and …, 2023 | 10 | 2023 |
| A comparative study of neural models for polyphonic music sequence transduction A Ycart, D Stoller, E Benetos | 10 | 2019 |
| Evolutionary multi-objective training set selection of data instances and augmentations for vocal detection I Vatolkin, D Stoller Computational Intelligence in Music, Sound, Art and Design: 8th …, 2019 | 4 | 2019 |
| Deep Learning for Music Information Retrieval in Limited Data Scenarios. D Stoller Queen Mary University of London, 2020 | 3 | 2020 |
| Intuitive and efficient computer-aided music rearrangement with optimised processing of audio transitions D Stoller, I Vatolkin, H Müller Journal of New Music Research, 2018 | 3 | 2018 |
| Training Generative Adversarial Networks from Incomplete Observations using Factorised Discriminators D Stoller, S Ewert, S Dixon International Conference on Learning Representations (ICLR), 2020 | 2 | 2020 |
| Detection of Cut-Points for Automatic Music Rearrangement D Stoller, V Akkermans, S Dixon 2018 IEEE 28th International Workshop on Machine Learning for Signal …, 2018 | 2 | 2018 |
| Systems and methods for aligning lyrics using a neural network D Stoller, SRG Durand, S Ewert US Patent 11,475,887, 2022 | | 2022 |
| Systems and methods for aligning lyrics using a neural network D Stoller, SRG Durand, S Ewert US Patent 11,308,943, 2022 | | 2022 |
| Impact of Frame Size and Instrumentation on Chroma-based Automatic Chord Recognition D Stoller, M Mauch, I Vatolkin, C Weihs European Conference on Data Analysis 2015 (ECDA), 411 - 421, 2015 | | 2015 |
