Linguistic features identify Alzheimer’s disease in narrative speech KC Fraser, JA Meltzer, F Rudzicz Journal of Alzheimer's Disease 49 (2), 407-422, 2016 | 790 | 2016 |
The TORGO database of acoustic and articulatory speech from speakers with dysarthria F Rudzicz, AK Namasivayam, T Wolff Language resources and evaluation 46, 523-541, 2012 | 348 | 2012 |
Artificial intelligence and the implementation challenge J Shaw, F Rudzicz, T Jamieson, A Goldfarb Journal of medical Internet research 21 (7), e13659, 2019 | 318 | 2019 |
A survey of word embeddings for clinical text FK Khattak, S Jeblee, C Pou-Prom, M Abdalla, C Meaney, F Rudzicz Journal of Biomedical Informatics 100, 100057, 2019 | 258 | 2019 |
Detecting anxiety through reddit JH Shen, F Rudzicz Proceedings of the Fourth Workshop on Computational Linguistics and Clinical …, 2017 | 230 | 2017 |
BENDR: Using transformers and a contrastive self-supervised learning task to learn from massive amounts of EEG data D Kostas, S Aroca-Ouellette, F Rudzicz Frontiers in Human Neuroscience 15, 653659, 2021 | 190 | 2021 |
Classifying phonological categories in imagined and articulated speech S Zhao, F Rudzicz 2015 IEEE international conference on acoustics, speech and signal …, 2015 | 172 | 2015 |
To BERT or not to BERT: comparing speech and language-based approaches for Alzheimer's disease detection A Balagopalan, B Eyre, F Rudzicz, J Novikova arXiv preprint arXiv:2008.01551, 2020 | 144 | 2020 |
NeuroSpeech: An open-source software for Parkinson's speech analysis JR Orozco-Arroyave, JC Vásquez-Correa, JF Vargas-Bonilla, R Arora, ... Digital Signal Processing 77, 207-221, 2018 | 135 | 2018 |
Centroid-based deep metric learning for speaker recognition J Wang, KC Wang, MT Law, F Rudzicz, M Brudno ICASSP 2019-2019 IEEE International Conference on Acoustics, Speech and …, 2019 | 120 | 2019 |
Treatment intensity and childhood apraxia of speech AK Namasivayam, M Pukonen, D Goshulak, J Hard, F Rudzicz, T Rietveld, ... International journal of language & communication disorders 50 (4), 529-546, 2015 | 117 | 2015 |
Evaluation of deep learning models for identifying surgical actions and measuring performance S Khalid, M Goldenberg, T Grantcharov, B Taati, F Rudzicz JAMA network open 3 (3), e201664-e201664, 2020 | 116 | 2020 |
Fast incremental LDA feature extraction YA Ghassabeh, F Rudzicz, HA Moghaddam Pattern Recognition 48 (6), 1999-2012, 2015 | 109 | 2015 |
Articulatory knowledge in the recognition of dysarthric speech F Rudzicz IEEE Transactions on Audio, Speech, and Language Processing 19 (4), 947-960, 2010 | 107 | 2010 |
Evaluation of speech-based digital biomarkers: review and recommendations J Robin, JE Harrison, LD Kaufman, F Rudzicz, W Simpson, M Yancheva Digital Biomarkers 4 (3), 99-108, 2020 | 105 | 2020 |
Adapting acoustic and lexical models to dysarthric speech KT Mengistu, F Rudzicz 2011 IEEE International Conference on Acoustics, Speech and Signal …, 2011 | 102 | 2011 |
Explainable artificial intelligence for safe intraoperative decision support L Gordon, T Grantcharov, F Rudzicz JAMA surgery 154 (11), 1064-1065, 2019 | 99 | 2019 |
Using linguistic features longitudinally to predict clinical scores for Alzheimer’s disease and related dementias M Yancheva, KC Fraser, F Rudzicz Proceedings of SLPAT 2015: 6th workshop on speech and language processing …, 2015 | 99 | 2015 |
Speech interaction with personal assistive robots supporting aging at home for individuals with Alzheimer’s disease F Rudzicz, R Wang, M Begum, A Mihailidis ACM Transactions on Accessible Computing (TACCESS) 7 (2), 1-22, 2015 | 94 | 2015 |
Adjusting dysarthric speech signals to be more intelligible F Rudzicz Computer Speech & Language 27 (6), 1163-1177, 2013 | 85 | 2013 |