フォロー
Stefan Uhlich
Stefan Uhlich
Sony Europe B.V., ZNL Deutschland
確認したメール アドレス: lss.uni-stuttgart.de
タイトル
引用先
引用先
Open-unmix-a reference implementation for music source separation
FR Stöter, S Uhlich, A Liutkus, Y Mitsufuji
Journal of Open Source Software 4 (41), 1667, 2019
2992019
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
International Conference on Acoustics, Speech and Signal Processing (ICASSP), 2017
2692017
Mixed precision DNNs: All you need is a good parametrization
S Uhlich, L Mauch, F Cardinaux, K Yoshiyama, JA García, S Tiedemann, ...
ICLR 2020, 2020
194*2020
Deep neural network based instrument extraction from music
S Uhlich, F Giron, Y Mitsufuji
2015 IEEE International Conference on Acoustics, Speech and Signal …, 2015
1512015
Music demixing challenge 2021
Y Mitsufuji, G Fabbro, S Uhlich, FR Stöter, A Défossez, M Kim, W Choi, ...
Frontiers in Signal Processing 1, 808395, 2022
85*2022
All for one and one for all: Improving music separation by bridging networks
R Sawata, S Uhlich, S Takahashi, Y Mitsufuji
ICASSP 2021-2021 IEEE International Conference on Acoustics, Speech and …, 2021
552021
Exploring the best loss function for DNN-based low-latency speech enhancement with temporal convolutional networks
Y Koyama, T Vuong, S Uhlich, B Raj
arXiv preprint arXiv:2005.11611, 2020
542020
Multidimensional localization of multiple sound sources using frequency domain ICA and an extended state coherence transform
B Loesch, S Uhlich, B Yang
2009 IEEE/SP 15th Workshop on Statistical Signal Processing, 677-680, 2009
352009
Method, system and artificial neural network
F Cardinaux, M Enenkl, F Giron, T Kemp, S Uhlich
US Patent 10,564,923, 2020
192020
Improving DNN-based Music Source Separation using Phase Features
J Muth, S Uhlich, N Perraudin, T Kemp, F Cardinaux, Y Mitsufuji
Joint Workshop on Machine Learning for Music at ICML, IJCAI/ECAI and AAMAS, 2018
182018
Bayes risk reduction of estimators using artificial observation noise
S Uhlich
IEEE Transactions on Signal Processing 63 (20), 5535-5545, 2015
182015
Automatic music mixing with deep learning and out-of-domain data
MA Martínez-Ramírez, WH Liao, G Fabbro, S Uhlich, C Nagashima, ...
arXiv preprint arXiv:2208.11428, 2022
172022
Multichannel non-negative matrix factorization using banded spatial covariance matrices in wavenumber domain
Y Mitsufuji, S Uhlich, N Takamune, D Kitamura, S Koyama, H Saruwatari
IEEE/ACM Transactions on Audio, Speech, and Language Processing 28, 49-60, 2019
172019
Iteratively training look-up tables for network quantization
F Cardinaux, S Uhlich, K Yoshiyama, JA García, L Mauch, S Tiedemann, ...
IEEE Journal of Selected Topics in Signal Processing 14 (4), 860-870, 2020
142020
Signal processing unit employing a blind channel estimation algorithm and method of operating a receiver apparatus
B Eitel, J Zinsser, RA Salem, S Uhlich
US Patent 9,401,826, 2016
142016
Electronic device, method and computer program for active noise control inside a vehicle
F Cardinaux, M Enenkl, MF Font, T Kemp, P Putzolu, S Uhlich
US Patent 10,650,798, 2020
132020
Open-unmix for speech enhancement (UMX SE)
S Uhlich, Y Mitsufuji
Zenodo, May, 2020
122020
NMF-based blind source separation using a linear predictive coding error clustering criterion
X Guo, S Uhlich, Y Mitsufuji
2015 IEEE International Conference on Acoustics, Speech and Signal …, 2015
122015
Robustification and optimization of a Kalman filter with measurement loss using linear precoding
R Blind, S Uhlich, B Yang, F Allgower
2009 American Control Conference, 2222-2227, 2009
122009
Training speech enhancement systems with noisy speech datasets
K Saito, S Uhlich, G Fabbro, Y Mitsufuji
arXiv preprint arXiv:2105.12315, 2021
112021
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