Privacy-preserving Contact Context Estimation

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Contact tracing apps provide data about whether a critical COVID-19 contact occurred. This contact tracing is solely based on Bluetoot signals. We plan to extend this mechanism with acustic indicators that incorporate the surrounding, i.e., the context of a critical contact. The recorded data would not leave the device yet privacy-preserving continuous learning of the acustic scene classifiers shall be done via differentially private federated learning. Complementarily, we plan to collect additional acustic data in a clinical study about coughing symtoms and change in speech by wearing a mask. As a result, we would validate publicly available audio data and extend the publicly available datasets for future research.