| Open-unmix-a reference implementation for music source separation FR Stöter, S Uhlich, A Liutkus, Y Mitsufuji The Journal of Open Source Software, 2019 | 319 | 2019 |
| Improving music source separation based on deep neural networks through data augmentation and network blending S Uhlich, M Porcu, F Giron, M Enenkl, T Kemp, N Takahashi, Y Mitsufuji ICASSP, 261-265, 2017 | 276 | 2017 |
| MMDenseLSTM: An efficient combination of convolutional and recurrent neural networks for audio source separation N Takahashi, N Goswami, Y Mitsufuji 2018 16th International Workshop on Acoustic Signal Enhancement (IWAENC), 2018 | 209 | 2018 |
| Multi-scale multi-band densenets for audio source separation N Takahashi, Y Mitsufuji 2017 IEEE Workshop on Applications of Signal Processing to Audio and …, 2017 | 188 | 2017 |
| Deep neural network based instrument extraction from music. S Uhlich, F Giron, Y Mitsufuji ICASSP, 2135-2139, 2015 | 157 | 2015 |
| ACCDOA: Activity-Coupled Cartesian Direction of Arrival Representation for Sound Event Localization And Detection K Shimada, Y Koyama, N Takahashi, S Takahashi, Y Mitsufuji ICASSP, 915-919, 2021 | 99 | 2021 |
| Recursive speech separation for unknown number of speakers N Takahashi, S Parthasaarathy, N Goswami, Y Mitsufuji INTERSPEECH, 1348-1352, 2019 | 99 | 2019 |
| Music demixing challenge 2021 Y Mitsufuji, G Fabbro, S Uhlich, FR Stöter, A Défossez, M Kim, W Choi, ... Frontiers in Signal Processing, 18, 2022 | 97* | 2022 |
| D3Net: Densely connected multidilated densenet for music source separation N Takahashi, Y Mitsufuji arXiv preprint arXiv:2010.01733, 2020 | 88 | 2020 |
| PhaseNet: Discretized Phase Modeling with Deep Neural Networks for Audio Source Separation. N Takahashi, P Agrawal, N Goswami, Y Mitsufuji INTERSPEECH, 2713-2717, 2018 | 85 | 2018 |
| Densely connected multi-dilated convolutional networks for dense prediction tasks N Takahashi, Y Mitsufuji Proceedings of the IEEE/CVF conference on computer vision and pattern …, 2021 | 80 | 2021 |
| STARSS22: A dataset of spatial recordings of real scenes with spatiotemporal annotations of sound events A Politis, K Shimada, P Sudarsanam, S Adavanne, D Krause, Y Koyama, ... arXiv preprint arXiv:2206.01948, 2022 | 77 | 2022 |
| Multi-ACCDOA: Localizing and Detecting Overlapping Sounds from the Same Class with Auxiliary Duplicating Permutation Invariant Training K Shimada, Y Koyama, S Takahashi, N Takahashi, E Tsunoo, Y Mitsufuji ICASSP, 316-320, 2022 | 75 | 2022 |
| Signal processing apparatus and signal processing method, encoder and encoding method, decoder and decoding method, and program Y Yamamoto, T Chinen, H Honma, Y Mitsufuji US Patent 9,406,312, 2016 | 70 | 2016 |
| Consistency trajectory models: Learning probability flow ode trajectory of diffusion D Kim, CH Lai, WH Liao, N Murata, Y Takida, T Uesaka, Y He, Y Mitsufuji, ... ICLR, 2024 | 64 | 2024 |
| All for One and One for All: Improving Music Separation by Bridging Networks R Sawata, S Uhlich, S Takahashi, Y Mitsufuji ICASSP, 51-55, 2021 | 60 | 2021 |
| SQ-VAE: Variational Bayes on Discrete Representation with Self-annealed Stochastic Quantization Y Takida, T Shibuya, WH Liao, CH Lai, J Ohmura, T Uesaka, N Murata, ... ICML, 20987-21012, 2022 | 50 | 2022 |
| Frequency band extending device and method, encoding device and method, decoding device and method, and program Y Yamamoto, T Chinen, H Honma, Y Mitsufuji US Patent 9,208,795, 2015 | 46 | 2015 |
| Frequency band extending apparatus, frequency band extending method, player apparatus, playing method, program and recording medium Y Mitsufuji, T Chinen, H Honma, K Makino US Patent App. 13/616,944, 2013 | 39 | 2013 |
| Frequency Band Extension Apparatus and Method, Encoding Apparatus and Method, Decoding Apparatus and Method, and Program H Honma, T Chinen, Y Yamamoto, Y Mitsufuji, K Makino US Patent App. 12/739,106, 2011 | 38 | 2011 |
Naoya TakahashiSONYVerified email at sony.com
