| Convolutional recurrent neural networks for polyphonic sound event detection E Cakir, G Parascandolo, T Heittola, H Huttunen, T Virtanen IEEE/ACM Transactions on Audio, Speech, and Language Processing 25 (6), 1291 …, 2017 | 582 | 2017 |
| Convolutional recurrent neural networks for polyphonic sound event detection E Cakir, G Parascandolo, T Heittola, H Huttunen, T Virtanen IEEE/ACM Transactions on Audio, Speech, and Language Processing 25 (6), 1291 …, 2017 | 582 | 2017 |
| 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 | 328 | 2015 |
| Convolutional recurrent neural networks for bird audio detection E Cakir, S Adavanne, G Parascandolo, K Drossos, T Virtanen 2017 25th European signal processing conference (EUSIPCO), 1744-1748, 2017 | 108 | 2017 |
| Convolutional recurrent neural networks for rare sound event detection E Cakır, T Virtanen Deep Neural Networks for Sound Event Detection 12, 2019 | 64 | 2019 |
| Robust direction estimation with convolutional neural networks based steered response power P Pertilä, E Cakir 2017 IEEE International Conference on Acoustics, Speech and Signal …, 2017 | 58 | 2017 |
| Stacked convolutional and recurrent neural networks for bird audio detection S Adavanne, K Drossos, E Çakir, T Virtanen 2017 25th European signal processing conference (EUSIPCO), 1729-1733, 2017 | 57 | 2017 |
| Unsupervised adversarial domain adaptation for acoustic scene classification S Gharib, K Drossos, E Cakir, D Serdyuk, T Virtanen arXiv preprint arXiv:1808.05777, 2018 | 53 | 2018 |
| Multi-label vs. combined single-label sound event detection with deep neural networks E Cakir, T Heittola, H Huttunen, T Virtanen 2015 23rd European signal processing conference (EUSIPCO), 2551-2555, 2015 | 47 | 2015 |
| End-to-end polyphonic sound event detection using convolutional recurrent neural networks with learned time-frequency representation input E Çakir, T Virtanen 2018 International Joint Conference on Neural Networks (IJCNN), 1-7, 2018 | 42 | 2018 |
| Filterbank learning for deep neural network based polyphonic sound event detection E Cakir, EC Ozan, T Virtanen 2016 International Joint Conference on Neural Networks (IJCNN), 3399-3406, 2016 | 40 | 2016 |
| The machine learning approach for analysis of sound scenes and events T Heittola, E Çakır, T Virtanen Computational Analysis of Sound Scenes and Events, 13-40, 2018 | 29 | 2018 |
| Domestic audio tagging with convolutional neural networks E Cakır, T Heittola, T Virtanen IEEE AASP challenge on detection and classification of acoustic scenes and …, 2016 | 28 | 2016 |
| Multi-task regularization based on infrequent classes for audio captioning E Çakır, K Drossos, T Virtanen arXiv preprint arXiv:2007.04660, 2020 | 19 | 2020 |
| Acoustic scene classification using convolutional recurrent neural networks H Jallet, E Cakır, T Virtanen the Detection and Classification of Acoustic Scenes and Events (DCASE), 1-5, 2017 | 13 | 2017 |
| Automatic recognition of environmental sound events using all-pole group delay features A Diment, E Cakir, T Heittola, T Virtanen 2015 23rd European signal processing conference (EUSIPCO), 729-733, 2015 | 13 | 2015 |
| Multilabel sound event classification with neural networks E Cakir | 13 | 2014 |
| Deep neural networks for sound event detection E Cakir Tampere University, 2019 | 10 | 2019 |
| Mobile microphone array speech detection and localization in diverse everyday environments P Pertilä, E Cakir, A Hakala, E Fagerlund, T Virtanen, A Politis, A Eronen 2021 29th European Signal Processing Conference (EUSIPCO), 406-410, 2021 | 4 | 2021 |
| Musical instrument synthesis and morphing in multidimensional latent space using variational, convolutional recurrent autoencoders E Çakir, T Virtanen Audio Engineering Society Convention 145, 2018 | 4 | 2018 |
Tuomas VirtanenTampere UniversityVerified email at tuni.fi
