Privacy preserving encrypted phonetic search of speech data
@article{Glackin2017PrivacyPE, title={Privacy preserving encrypted phonetic search of speech data}, author={C. Glackin and G{\'e}rard Chollet and Nazim Dugan and Nigel Cannings and J. Wall and S. Tahir and I. G. Ray and M. Rajarajan}, journal={2017 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP)}, year={2017}, pages={6414-6418} }
This paper presents a strategy for enabling speech recognition to be performed in the cloud whilst preserving the privacy of users. The approach advocates a demarcation of responsibilities between the client and server-side components for performing the speech recognition task. On the client-side resides the acoustic model, which symbolically encodes the audio and encrypts the data before uploading to the server. The server-side then employs searchable encryption to enable the phonetic search… CONTINUE READING
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