| An end-to-end neural network for polyphonic piano music transcription S Sigtia, E Benetos, S Dixon IEEE/ACM Transactions on Audio, Speech, and Language Processing 24 (5), 927-939, 2016 | 247 | 2016 |
| Improved music feature learning with deep neural networks S Sigtia, S Dixon 2014 IEEE international conference on acoustics, speech and signal …, 2014 | 119 | 2014 |
| Unsupervised feature learning based on deep models for environmental audio tagging Y Xu, Q Huang, W Wang, P Foster, S Sigtia, PJB Jackson, MD Plumbley IEEE/ACM Transactions on Audio, Speech, and Language Processing 25 (6), 1230 …, 2017 | 70 | 2017 |
| Audio Chord Recognition with a Hybrid Recurrent Neural Network. S Sigtia, N Boulanger-Lewandowski, S Dixon ISMIR, 127-133, 2015 | 60 | 2015 |
| Chime-home: A dataset for sound source recognition in a domestic environment P Foster, S Sigtia, S Krstulovic, J Barker, MD Plumbley 2015 IEEE Workshop on Applications of Signal Processing to Audio and …, 2015 | 58 | 2015 |
| Automatic environmental sound recognition: Performance versus computational cost S Sigtia, AM Stark, S Krstulović, MD Plumbley IEEE/ACM Transactions on Audio, Speech, and Language Processing 24 (11 …, 2016 | 57 | 2016 |
| A hybrid recurrent neural network for music transcription S Sigtia, E Benetos, N Boulanger-Lewandowski, T Weyde, ASA Garcez, ... 2015 IEEE international conference on acoustics, speech and signal …, 2015 | 41 | 2015 |
| RNN-based music language models for improving automatic music transcription S Sigtia, E Benetos, S Cherla, T Weyde, A Garcez, S Dixon | 38 | 2014 |
| Generalised discriminative transform via curriculum learning for speaker recognition E Marchi, S Shum, K Hwang, S Kajarekar, S Sigtia, H Richards, R Haynes, ... 2018 IEEE International Conference on Acoustics, Speech and Signal …, 2018 | 18 | 2018 |
| Efficient Voice Trigger Detection for Low Resource Hardware S Sigtia, R Haynes, H Richards, E Marchi, J Bridle Interspeech, 2092-2096, 2018 | 16 | 2018 |
| Multi-Task Learning for Speaker Verification and Voice Trigger Detection S Sigtia, E Marchi, S Kajarekar, D Naik, J Bridle ICASSP 2020-2020 IEEE International Conference on Acoustics, Speech and …, 2020 | 10 | 2020 |
| Multi-task Learning for Voice Trigger Detection S Sigtia, P Clark, R Haynes, H Richards, J Bridle 2020 IEEE International Conference on Acoustics, Speech and Signal …, 2020 | 10* | 2020 |
| Learning to generate genotypes with neural networks AW Churchill, S Sigtia, C Fernando arXiv preprint arXiv:1604.04153, 2016 | 7 | 2016 |
| A denoising autoencoder that guides stochastic search AW Churchill, S Sigtia, C Fernando arXiv preprint arXiv:1404.1614, 2014 | 7 | 2014 |
| Fully deep neural networks incorporating unsupervised feature learning for audio tagging Y Xu, Q Huang, W Wang, P Foster, S Sigtia, PJB Jackson, MD Plumbley arXiv preprint arXiv:1607.03681, 2016 | 3 | 2016 |
| Hybrid Transformer/CTC Networks for Hardware Efficient Voice Triggering S Adya, V Garg, S Sigtia, P Simha, C Dhir INTERSPEECH, 2020 | 2 | 2020 |
| Neural Networks for Analysing Music and Environmental Audio S Sigtia Queen Mary University of London, 2017 | 1 | 2017 |
| Progressive Voice Trigger Detection: Accuracy vs Latency S Sigtia, J Bridle, H Richards, P Clark, E Marchi, V Garg arXiv preprint arXiv:2010.15446, 2020 | | 2020 |
Simon DixonCentre for Digital Music, Queen Mary University of LondonVerified email at qmul.ac.uk
