| Non-negative tensor factorisation of modulation spectrograms for monaural sound source separation. T Barker, T Virtanen INTERSPEECH 2813, 827-831, 2013 | 48 | 2013 |
| Low latency sound source separation using convolutional recurrent neural networks G Naithani, T Barker, G Parascandolo, L Bramsl, NH Pontoppidan, ... 2017 IEEE Workshop on Applications of Signal Processing to Audio and …, 2017 | 38 | 2017 |
| Improving competing voices segregation for hearing impaired listeners using a low-latency deep neural network algorithm L Bramsløw, G Naithani, A Hafez, T Barker, NH Pontoppidan, T Virtanen The Journal of the Acoustical Society of America 144 (1), 172-185, 2018 | 29 | 2018 |
| Coupled dictionary training for exemplar-based speech enhancement D Baby, T Virtanen, T Barker 2014 IEEE International Conference on Acoustics, Speech and Signal …, 2014 | 23 | 2014 |
| Low-latency sound source separation using deep neural networks G Naithani, G Parascandolo, T Barker, NH Pontoppidan, T Virtanen 2016 IEEE Global Conference on Signal and Information Processing (GlobalSIP …, 2016 | 20 | 2016 |
| Blind Separation of Audio Mixtures through Nonnegative Tensor Factorisation of Modulation Spectograms T Barker, T Virtanen IEEE/ACM Transactions on Audio, Speech, and Language Processing, 2016 | 19 | 2016 |
| Low-latency sound-source-separation using non-negative matrix factorisation with coupled analysis and synthesis dictionaries T Barker, T Virtanen, NH Pontoppidan 2015 IEEE International Conference on Acoustics, Speech and Signal …, 2015 | 14 | 2015 |
| Ultrasound-coupled Semi-supervised Nonnegative Matrix Factorisation for Speech Enhancement T Barker, T Virtanen, O Delhomme ICASSP 2014, 2014 | 8 | 2014 |
| Semi-supervised non-negative tensor factorisation of modulation spectrograms for monaural speech separation T Barker, T Virtanen 2014 International Joint Conference on Neural Networks (IJCNN), 3556-3561, 2014 | 7 | 2014 |
| Exemplar-based noise robust automatic speech recognition using modulation spectrogram features D Baby, T Virtanen, JF Gemmeke, T Barker 2014 IEEE Spoken Language Technology Workshop (SLT), 519-524, 2014 | 6 | 2014 |
| Real-time auralisation system for virtual microphone positioning T Barker, G Campos, P Dias, J Vieira, C Mendonça, J Santos 15th Internation Conference on Digital Audio Effects, 2012 | 5 | 2012 |
| Reflection orders and auditory distance C Mendonça, J Lamas, T Barker, G Campos, P Dias, V Pulkki, C Silva, ... Proceedings of Meetings on Acoustics 19 (1), 2013 | 3 | 2013 |
| Non-negative factorisation techniques for sound source separation T Barker Tampere University of Technology, 2017 | 1 | 2017 |
| Separation of Known Sources Using Non-negative Spectrogram Factorisation T Virtanen, T Barker Audio Source Separation, 25-48, 2018 | | 2018 |
| 2016 Index IEEE/ACM Transactions on Audio, Speech, and Language Processing Vol. 24 S Abdul-Rauf, WH Abdulla, SI Adalbjornsson, M Adeli, K Adiloglu, ... IEEE/ACM Transactions on Audio, Speech, and Language Processing 24 (12), 2555, 2016 | | 2016 |
| Modelling Primitive Streaming of Simple Tone Sequences Through Factorisation of Modulation Pattern Tensors T Barker, H Van Hamme, T Virtanen Interspeech, 1371-1375, 2014 | | 2014 |
| Evaluation of the benefit of neural network based speech separation algorithms with hearing impaired listeners G Naithani, T Barker, G Parascandalo, L Bramsløw, NH Pontoppidan, ... | | |
| Long-Term SNR Estimation of Speech Signals in Known and Unknown Channel Conditions........................................................................................ P … N Moritz, B Kollmeier, J Anemüller, M Krawczyk-Becker, T Gerkmann, ... | | |
| Separating known competing voices for people with hearing loss NH Pontoppidan, M Vatti, R Rossing, T Barker, T Virtanen | | |
Tuomas VirtanenTampere UniversityVerified email at tuni.fi
