| A survey on deep learning-based non-invasive brain signals: recent advances and new frontiers X Zhang, L Yao, X Wang, J Monaghan, D Mcalpine, Y Zhang Journal of neural engineering 18 (3), 031002, 2021 | 462* | 2021 |
| Development of social vocalizations in mice JMS Grimsley, JJM Monaghan, JJ Wenstrup PloS one 6 (3), e17460, 2011 | 299 | 2011 |
| A convolutional recurrent attention model for subject-independent EEG signal analysis D Zhang, L Yao, K Chen, J Monaghan IEEE signal processing letters 26 (5), 715-719, 2019 | 195 | 2019 |
| Speech enhancement based on neural networks improves speech intelligibility in noise for cochlear implant users T Goehring, F Bolner, JJM Monaghan, B Van Dijk, A Zarowski, S Bleeck Hearing research 344, 183-194, 2017 | 145 | 2017 |
| A statistical, formant-pattern model for segregating vowel type and vocal-tract length in developmental formant data RE Turner, TC Walters, JJM Monaghan, RD Patterson The Journal of the Acoustical Society of America 125 (4), 2374-2386, 2009 | 84* | 2009 |
| Hidden hearing loss impacts the neural representation of speech in background noise JJM Monaghan, JA Garcia-Lazaro, D McAlpine, R Schaette Current Biology 30 (23), 4710-4721. e4, 2020 | 59 | 2020 |
| Deep reinforcement learning guided graph neural networks for brain network analysis X Zhao, J Wu, H Peng, A Beheshti, JJM Monaghan, D McAlpine, ... Neural Networks 154, 56-67, 2022 | 45 | 2022 |
| Speech enhancement based on neural networks applied to cochlear implant coding strategies F Bolner, T Goehring, J Monaghan, B Van Dijk, J Wouters, S Bleeck 2016 IEEE International Conference on Acoustics, Speech and Signal …, 2016 | 44 | 2016 |
| Auditory inspired machine learning techniques can improve speech intelligibility and quality for hearing-impaired listeners JJM Monaghan, T Goehring, X Yang, F Bolner, S Wang, M Wright, ... The Journal of the Acoustical Society of America 141 (3), 1985-1998, 2017 | 35 | 2017 |
| Tolerable delay for speech production and perception: Effects of hearing ability and experience with hearing aids T Goehring, JL Chapman, S Bleeck, JJM Monaghan* International Journal of Audiology 57 (1), 61-68, 2018 | 34 | 2018 |
| Factors affecting the use of envelope interaural time differences in reverberation JJM Monaghan, K Krumbholz, BU Seeber The Journal of the Acoustical Society of America 133 (4), 2288-2300, 2013 | 31 | 2013 |
| A method to enhance the use of interaural time differences for cochlear implants in reverberant environments JJM Monaghan, BU Seeber The Journal of the Acoustical Society of America 140 (2), 1116-1129, 2016 | 30 | 2016 |
| Sensitivity to Envelope Interaural Time Differences at High Modulation Rates JJM Monaghan, S Bleeck, D McAlpine Trends in Hearing 19, 2331216515619331, 2015 | 26 | 2015 |
| Cross-modal functional connectivity supports speech understanding in cochlear implant users AM Fullerton, DA Vickers, R Luke, AN Billing, D McAlpine, ... Cerebral Cortex 33 (7), 3350-3371, 2023 | 25 | 2023 |
| Low-dimensional, auditory feature vectors that improve vocal-tract-length normalization in automatic speech recognition JJ Monaghan, C Feldbauer, TC Walters, RD Patterson Journal of the Acoustical Society of America 123 (5), 3066, 2008 | 22 | 2008 |
| Speech enhancement for hearing-impaired listeners using deep neural networks with auditory-model based features T Goehring, X Yang, JJM Monaghan, S Bleeck 2016 24th European signal processing conference (EUSIPCO), 2300-2304, 2016 | 17 | 2016 |
| Semi-supervised EEG clustering with multiple constraints C Dai, J Wu, JJM Monaghan, G Li, H Peng, SI Becker, D McAlpine IEEE Transactions on Knowledge and Data Engineering 35 (8), 8529-8544, 2022 | 16 | 2022 |
| Generalizable sample-efficient Siamese autoencoder for tinnitus diagnosis in listeners with subjective tinnitus Z Liu, L Yao, X Wang, JJM Monaghan, R Schaette, Z He, D McAlpine IEEE Transactions on Neural Systems and Rehabilitation Engineering 29, 1452-1461, 2021 | 14 | 2021 |
| Influence of envelope waveform on ITD sensitivity of neurons in the auditory midbrain D Greenberg, JJM Monaghan, M Dietz, T Marquardt, D McAlpine Journal of neurophysiology 118 (4), 2358-2370, 2017 | 14 | 2017 |
| Deep factor learning for accurate brain neuroimaging data analysis on discrimination for structural MRI and functional MRI H Ke, D Chen, Q Yao, Y Tang, J Wu, J Monaghan, P Sowman, ... IEEE/ACM Transactions on Computational Biology and Bioinformatics, 2023 | 13 | 2023 |
David McAlpineMacquarie UniversityVerified email at mq.edu.au
