Acoustic Fingerprints for Access Management in Ad-Hoc Sensor Networks. Zarazaga, P. P., Bäckström, T., & Sigg, S. IEEE Access, 2020. doi abstract bibtex Voice user interfaces can offer intuitive interaction with our devices, but the usability and audio quality could be further improved if multiple devices could collaborate to provide a distributed voice user interface. To ensure that users' voices are not shared with unauthorized devices, it is however necessary to design an access management system that adapts to the users' needs. Prior work has demonstrated that a combination of audio fingerprinting and fuzzy cryptography yields a robust pairing of devices without sharing the information that they record. However, the robustness of these systems is partially based on the extensive duration of the recordings that are required to obtain the fingerprint. This paper analyzes methods for robust generation of acoustic fingerprints in short periods of time to enable the responsive pairing of devices according to changes in the acoustic scenery and can be integrated into other typical speech processing tools.
@article{Pablo_2020_Acoustic,
author={Pablo Pérez Zarazaga and Tom B\"ackstr\"om and Stephan Sigg},
journal={IEEE Access},
title={Acoustic Fingerprints for Access Management in Ad-Hoc Sensor Networks},
year={2020},
abstract={Voice user interfaces can offer intuitive interaction with our devices, but the usability and audio quality could be further improved if multiple devices could collaborate to provide a distributed voice user interface. To ensure that users' voices are not shared with unauthorized devices, it is however necessary to design an access management system that adapts to the users' needs. Prior work has demonstrated that a combination of audio fingerprinting and fuzzy cryptography yields a robust pairing of devices without sharing the information that they record. However, the robustness of these systems is partially based on the extensive duration of the recordings that are required to obtain the fingerprint. This paper analyzes methods for robust generation of acoustic fingerprints in short periods of time to enable the responsive pairing of devices according to changes in the acoustic scenery and can be integrated into other typical speech processing tools.},
group = {ambience},
doi = {10.1109/ACCESS.2020.3022618}
}
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