| CNN architectures for large-scale audio classification S Hershey, S Chaudhuri, DPW Ellis, JF Gemmeke, A Jansen, RC Moore, ... 2017 ieee international conference on acoustics, speech and signal …, 2017 | 1003 | 2017 |
| AudioSet: An ontology and human-labeled dataset for audio events JF Gemmeke, DPW Ellis, D Freedman, A Jansen, W Lawrence, RC Moore, ... IEEE ICASSP, 2017 | 888 | 2017 |
| 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 | 412 | 2011 |
| Compressive sensing for missing data imputation in noise robust speech recognition JF Gemmeke, H Van Hamme, B Cranen, L Boves IEEE Journal of selected topics in Signal Processing 4 (2), 272-287, 2010 | 138 | 2010 |
| An exemplar-based NMF approach to audio event detection JF Gemmeke, L Vuegen, P Karsmakers, B Vanrumste 2013 IEEE workshop on applications of signal processing to audio and …, 2013 | 105 | 2013 |
| Speech enhancement under low SNR conditions via noise estimation using sparse and low-rank NMF with Kullback–Leibler divergence M Sun, Y Li, JF Gemmeke, X Zhang IEEE/ACM Transactions on Audio, Speech, and Language Processing 23 (7), 1233 …, 2015 | 91 | 2015 |
| Compositional models for audio processing: Uncovering the structure of sound mixtures T Virtanen, JF Gemmeke, B Raj, P Smaragdis IEEE Signal Processing Magazine 32 (2), 125-144, 2015 | 84 | 2015 |
| Using sparse representations for missing data imputation in noise robust speech recognition JF Gemmeke, B Cranen 2008 16th European Signal Processing Conference, 1-5, 2008 | 79 | 2008 |
| Active-set Newton algorithm for overcomplete non-negative representations of audio T Virtanen, JF Gemmeke, B Raj IEEE Transactions on Audio, Speech, and Language Processing 21 (11), 2277-2289, 2013 | 74 | 2013 |
| Exemplar-based processing for speech recognition: An overview TN Sainath, B Ramabhadran, D Nahamoo, D Kanevsky, ... IEEE Signal Processing Magazine 29 (6), 98-113, 2012 | 72 | 2012 |
| Noise robust exemplar-based connected digit recognition JF Gemmeke, T Virtanen 2010 IEEE International Conference on Acoustics, Speech and Signal …, 2010 | 66 | 2010 |
| Non-negative matrix factorization for highly noise-robust asr: To enhance or to recognize? F Weninger, M Wöllmer, J Geiger, B Schuller, JF Gemmeke, ... 2012 IEEE International Conference on Acoustics, Speech and Signal …, 2012 | 47 | 2012 |
| Non-negative matrix deconvolution in noise robust speech recognition A Hurmalainen, J Gemmeke, T Virtanen 2011 IEEE International Conference on Acoustics, Speech and Signal …, 2011 | 40 | 2011 |
| An MFCC-GMM approach for event detection and classification L Vuegen, BVD Broeck, P Karsmakers, JF Gemmeke, B Vanrumste, ... IEEE Workshop on Applications of Signal Processing to Audio and Acoustics …, 2013 | 37 | 2013 |
| Using sparse representations for exemplar based continuous digit recognition J Gemmeke, L ten Bosch, L Boves, B Cranen 2009 17th European Signal Processing Conference, 1755-1759, 2009 | 37 | 2009 |
| Sparse imputation for large vocabulary noise robust ASR JF Gemmeke, B Cranen, U Remes Computer Speech & Language 25 (2), 462-479, 2011 | 36 | 2011 |
| Noise reduction through compressed sensing JF Gemmeke, B Cranen Brisbane, Australia: ISCA, 2008 | 35 | 2008 |
| Modelling non-stationary noise with spectral factorisation in automatic speech recognition A Hurmalainen, JF Gemmeke, T Virtanen Computer Speech & Language 27 (3), 763-779, 2013 | 32 | 2013 |
| The TUM+ TUT+ KUL approach to the CHiME Challenge 2013: Multi-stream ASR exploiting BLSTM networks and sparse NMF J Geiger, F Weninger, A Hurmalainen, J Gemmeke, M Wöllmer, B Schuller, ... Proceedings CHiME 2013, 25-30, 2013 | 32 | 2013 |
| Memory-enhanced neural networks and NMF for robust ASR JT Geiger, F Weninger, JF Gemmeke, M Wöllmer, B Schuller, G Rigoll IEEE/ACM Transactions on Audio, Speech, and Language Processing 22 (6), 1037 …, 2014 | 31 | 2014 |
Tuomas VirtanenTampere UniversityVerified email at tuni.fi
