Private Meeting Summarization Without Performance Loss. (arXiv:2305.15894v1 [cs.CL])

Meeting summarization has an enormous business potential, but in addition to
being a hard problem, roll-out is challenged by privacy concerns. We explore
the problem of meeting summarization under differential privacy constraints and
find, to our surprise, that while differential privacy leads to slightly lower
performance on in-sample data, differential privacy improves performance when
evaluated on unseen meeting types. Since meeting summarization systems will
encounter a great variety of meeting types in practical employment scenarios,
this observation makes safe meeting …

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