Federated learning for secure development of AI models for Parkinson’s disease detection using speech from different languages

Tayebi Arasteh S, Rios-Urrego CD, Nöth E, Maier A, Yang SH, Rusz J, Rafael Orozco-Arroyave J (2023)

Publication Language: English

Publication Type: Conference contribution, Conference Contribution

Publication year: 2023

City/Town: Dublin, Ireland

Pages Range: 5

Conference Proceedings Title: Proceedings of INTERSPEECH 2023

Event location: Dublin IE

DOI: 10.21437/Interspeech.2023-2108

Open Access Link: https://doi.org/10.21437/Interspeech.2023-2108

Abstract

Parkinson's disease (PD) is a neurological disorder impacting a person's speech. Among automatic PD assessment methods, deep learning models have gained particular interest. Recently, the community has explored cross-pathology and cross-language models which can improve diagnostic accuracy even further. However, strict patient data privacy regulations largely prevent institutions from sharing patient speech data with each other. In this paper, we employ federated learning (FL) for PD detection using speech signals from 3 real-world language corpora of German, Spanish, and Czech, each from a separate institution. Our results indicate that the FL model outperforms all the local models in terms of diagnostic accuracy, while not performing very differently from the model based on centrally combined training sets, with the advantage of not requiring any data sharing among collaborators. This will simplify inter-institutional collaborations, resulting in enhancement of patient outcomes.

Authors with CRIS profile

Soroosh Tayebi Arasteh Lehrstuhl für Informatik 5 (Mustererkennung) Elmar Nöth Technische Fakultät Andreas Maier Lehrstuhl für Informatik 5 (Mustererkennung) Seung Hee Yang Professur für Artificial Intelligence in Biomedical Speech Processing (Stiftungsprofessur)

Involved external institutions

Czech Technical University in Prague / České vysoké učení technické v Praze CZ Czech Republic (CZ) Universidad de Antioquía (UDEA) CO Colombia (CO)

How to cite

APA:

Tayebi Arasteh, S., Rios-Urrego, C.D., Nöth, E., Maier, A., Yang, S.H., Rusz, J., & Rafael Orozco-Arroyave, J. (2023). Federated learning for secure development of AI models for Parkinson’s disease detection using speech from different languages. In Proceedings of INTERSPEECH 2023 (pp. 5). Dublin, IE: Dublin, Ireland.

MLA:

Tayebi Arasteh, Soroosh, et al. "Federated learning for secure development of AI models for Parkinson’s disease detection using speech from different languages." Proceedings of the Interspeech 2023, Dublin Dublin, Ireland, 2023. 5.

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