| Monaural sound source separation by nonnegative matrix factorization with temporal continuity and sparseness criteria T Virtanen IEEE Transactions on Audio, Speech, and Language Processing 15 (3), 1066-1074, 2007 | 1271 | 2007 |
| TUT database for acoustic scene classification and sound event detection A Mesaros, T Heittola, T Virtanen 2016 24th European Signal Processing Conference (EUSIPCO), 1128-1132, 2016 | 622 | 2016 |
| Convolutional recurrent neural networks for polyphonic sound event detection E Cakır, G Parascandolo, T Heittola, H Huttunen, T Virtanen IEEE/ACM Transactions on Audio, Speech, and Language Processing 25 (6), 1291 …, 2017 | 570 | 2017 |
| Metrics for Polyphonic Sound Event Detection A Mesaros, T Heittola, T Virtanen Applied Sciences 6 (6), 162, 2016 | 557 | 2016 |
| DCASE 2017 challenge setup: Tasks, datasets and baseline system A Mesaros, T Heittola, A Diment, B Elizalde, A Shah, E Vincent, B Raj, ... DCASE 2017-Workshop on Detection and Classification of Acoustic Scenes and …, 2017 | 518 | 2017 |
| Deep Learning for Audio Signal Processing H Purwins, B Li, T Virtanen, J Schlüter, SY Chang, T Sainath IEEE Journal of Selected Topics in Signal Processing 13 (2), 206-219, 2019 | 507 | 2019 |
| Exemplar-based sparse representations for noise robust automatic speech recognition JF Gemmeke, T Virtanen, A Hurmalainen IEEE Transactions on Audio, Speech, and Language Processing 19 (7), 2067-2080, 2011 | 433 | 2011 |
| Recurrent neural networks for polyphonic sound event detection in real life recordings G Parascandolo, H Huttunen, T Virtanen Acoustics, Speech and Signal Processing (ICASSP), 2016 IEEE International …, 2016 | 379 | 2016 |
| A multi-device dataset for urban acoustic scene classification A Mesaros, T Heittola, T Virtanen arXiv preprint arXiv:1807.09840, 2018 | 358 | 2018 |
| Acoustic event detection in real life recordings A Mesaros, T Heittola, A Eronen, T Virtanen 18th European Signal Processing Conference, 1267-1271, 2010 | 356 | 2010 |
| Sound event localization and detection of overlapping sources using convolutional recurrent neural networks S Adavanne, A Politis, J Nikunen, T Virtanen IEEE Journal of Selected Topics in Signal Processing 13 (1), 34-48, 2018 | 344 | 2018 |
| Polyphonic sound event detection using multi label deep neural networks E Cakir, T Heittola, H Huttunen, T Virtanen 2015 international joint conference on neural networks (IJCNN), 1-7, 2015 | 325 | 2015 |
| Detection and Classification of Acoustic Scenes and Events: Outcome of the DCASE 2016 Challenge A Mesaros, T Heittola, E Benetos, P Foster, M Lagrange, T Virtanen, ... IEEE/ACM Transactions on Audio, Speech, and Language Processing 26 (2), 379-393, 2018 | 313 | 2018 |
| Context-dependent sound event detection T Heittola, A Mesaros, A Eronen, T Virtanen EURASIP Journal on Audio, Speech, and Music Processing 2013 (1), 1, 2013 | 255 | 2013 |
| Computational analysis of sound scenes and events T Virtanen, MD Plumbley, D Ellis Springer International Publishing, 2018 | 248 | 2018 |
| Voice conversion using partial least squares regression E Helander, T Virtanen, J Nurminen, M Gabbouj Audio, Speech, and Language Processing, IEEE Transactions on 18 (5), 912-921, 2010 | 235 | 2010 |
| Direction of arrival estimation for multiple sound sources using convolutional recurrent neural network S Adavanne, A Politis, T Virtanen 2018 26th European Signal Processing Conference (EUSIPCO), 1462-1466, 2018 | 222 | 2018 |
| Audio Source Separation and Speech Enhancement E Vincent, T Virtanen, S Gannot John Wiley & Sons, 2018 | 222 | 2018 |
| Separation of drums from polyphonic music using non-negative matrix factorization and support vector machine M Helén, T Virtanen Proc. EUSIPCO 2005, 2005 | 211 | 2005 |
| Bayesian extensions to non-negative matrix factorisation for audio signal modelling T Virtanen, AT Cemgil, S Godsill Acoustics, Speech and Signal Processing, 2008. ICASSP 2008. IEEE …, 2008 | 200 | 2008 |
Toni HeittolaPost-doctoral researcher, Tampere UniversityVerified email at tuni.fi
