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Open source audio transcription model that obscures sensitive info in realtime
For applications that do not require masking, the model can be configured to simply tag sensitive entities, providing options.
Unlike traditional multi-step systems, which leave data exposed during intermediary processing stages, Whisper-NER eliminates the need for separate ASR and NER tools, reducing vulnerability to breaches. “We designed this as an open-source tool to advance privacy in AI,” said Gill Hetz, Vice President of Research at aiOla, in a recent video call interview with VentureBeat. With Whisper-NER now available to the public, aiOla reinforces its commitment to creating responsible AI tools that prioritize user privacy and security while fostering collaboration and innovation through open access.
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