Frank Rudzicz
Frank Rudzicz
Dalhousie University, Computer Science ; Vector Institute for Artificial Intelligence
Verified email at - Homepage
Cited by
Cited by
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
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
Artificial intelligence and the implementation challenge
J Shaw, F Rudzicz, T Jamieson, A Goldfarb
Journal of medical Internet research 21 (7), e13659, 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
Detecting anxiety through reddit
JH Shen, F Rudzicz
Proceedings of the Fourth Workshop on Computational Linguistics and Clinical …, 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
Classifying phonological categories in imagined and articulated speech
S Zhao, F Rudzicz
2015 IEEE international conference on acoustics, speech and signal …, 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
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
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
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
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
Fast incremental LDA feature extraction
YA Ghassabeh, F Rudzicz, HA Moghaddam
Pattern Recognition 48 (6), 1999-2012, 2015
Articulatory knowledge in the recognition of dysarthric speech
F Rudzicz
IEEE Transactions on Audio, Speech, and Language Processing 19 (4), 947-960, 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
Adapting acoustic and lexical models to dysarthric speech
KT Mengistu, F Rudzicz
2011 IEEE International Conference on Acoustics, Speech and Signal …, 2011
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
Explainable artificial intelligence for safe intraoperative decision support
L Gordon, T Grantcharov, F Rudzicz
JAMA surgery 154 (11), 1064-1065, 2019
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
Adjusting dysarthric speech signals to be more intelligible
F Rudzicz
Computer Speech & Language 27 (6), 1163-1177, 2013
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