Ido Cohn
Ido Cohn is a SWE in Israel's Google Research group, working on health-related research, currently focusing on Scanned Medical Documents Understanding.
Prior to that, Ido worked the de-identification of audio and text medical records, creating the state-of-the-art medical conversation de-identification system.
Before joining Google, Ido was an engineering manager at General Motors, working on perception technologies for Autonomous Vehicles, and a senior researcher at Microsoft's Cortana research group.
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Audio De-identification: A New Entity Recognition Task
Tzvika Hartman
NAACL (2019)
Preview abstract
Named Entity Recognition (NER) has been mostly studied in the context of written text. Specifically, NER is an important step in de-identification (de-ID) of medical records, many of which are recorded conversations between a patient and a doctor. In such recordings, audio spans with personal information should be redacted, similar to the redaction of sensitive character spans in de-ID for written text. The application of NER in the context of audio de-identification has yet to be fully investigated. To this end, we define the task of audio de-ID, in which audio spans with entity mentions should be detected. We then present our pipeline for this task, which involves Automatic Speech Recognition (ASR), NER on the transcript text, and text-to-audio alignment. Finally, we introduce a novel metric for audio de-ID and a new evaluation benchmark consisting of a large labeled segment of the Switchboard and Fisher audio datasets and detail our pipeline's results on it.
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