| 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 | 1133 | 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 | 446 | 2016 |
| 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 | 413 | 2011 |
| 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 | 344 | 2017 |
| Metrics for Polyphonic Sound Event Detection A Mesaros, T Heittola, T Virtanen Applied Sciences 6 (6), 162, 2016 | 326 | 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 | 310 | 2017 |
| Acoustic event detection in real life recordings A Mesaros, T Heittola, A Eronen, T Virtanen 18th European Signal Processing Conference, 1267-1271, 2010 | 267 | 2010 |
| 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 | 260 | 2016 |
| 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 | 238 | 2015 |
| Separation of drums from polyphonic music using non-negative matrix factorization and support vector machine M Helén, T Virtanen Proc. EUSIPCO 2005, 2005 | 201 | 2005 |
| 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 | 195 | 2010 |
| 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 | 194 | 2013 |
| 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 | 178 | 2018 |
| 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 | 178 | 2008 |
| A multi-device dataset for urban acoustic scene classification A Mesaros, T Heittola, T Virtanen arXiv preprint arXiv:1807.09840, 2018 | 173 | 2018 |
| Techniques for noise robustness in automatic speech recognition T VIRTANEN, B SINGH, Rita, RAJ Wiley, 2012 | 168 | 2012 |
| Sound source separation using sparse coding with temporal continuity objective T Virtanen Proc. ICMC 3, 231-234, 2003 | 161 | 2003 |
| Musical Instrument Recognition in Polyphonic Audio Using Source-Filter Model for Sound Separation. T Heittola, A Klapuri, T Virtanen ISMIR, 327-332, 2009 | 158 | 2009 |
| Exemplar-based sparse representation with residual compensation for voice conversion Z Wu, T Virtanen, ES Chng, H Li IEEE/ACM Transactions on Audio, Speech, and Language Processing 22 (10 …, 2014 | 151 | 2014 |
| Non-negative matrix factorization based compensation of music for automatic speech recognition. B Raj, T Virtanen, S Chaudhuri, R Singh INTERSPEECH, 717-720, 2010 | 149 | 2010 |
Toni HeittolaResearcher, Tampere UniversityVerified email at tuni.fi
