View source for 18277213. METHODS AND SYSTEMS FOR PROCESSING VOICE AUDIO TO SEGREGATE PERSONAL HEALTH INFORMATION simplified abstract (KONINKLIJKE PHILIPS N.V.)

=METHODS AND SYSTEMS FOR PROCESSING VOICE AUDIO TO SEGREGATE PERSONAL HEALTH INFORMATION=


==Organization Name==

[[:Category:KONINKLIJKE PHILIPS N.V.|KONINKLIJKE PHILIPS N.V.]]


[[Category:KONINKLIJKE PHILIPS N.V.]]

==Inventor(s)==

[[:Category:Sahar Bin Hairalah of Sammamish WA (US)|Sahar Bin Hairalah of Sammamish WA (US)]][[Category:Sahar Bin Hairalah of Sammamish WA (US)]]

[[:Category:Aravind Gundumane of Bangalore (IN)|Aravind Gundumane of Bangalore (IN)]][[Category:Aravind Gundumane of Bangalore (IN)]]

==METHODS AND SYSTEMS FOR PROCESSING VOICE AUDIO TO SEGREGATE PERSONAL HEALTH INFORMATION - A simplified explanation of the abstract==


This abstract first appeared for US patent application 18277213 titled 'METHODS AND SYSTEMS FOR PROCESSING VOICE AUDIO TO SEGREGATE PERSONAL HEALTH INFORMATION

==Simplified Explanation==

The system described in the patent application is a voice audio processing system that includes both a local device and a remote personal health data ecosystem. The local device is equipped with a speech-to-text transcriber, NLP, and ML classifier to process voice audio spoken by a user and classify it as either personal health or non-personal health related. The remote personal health data ecosystem includes a speech-to-text transcriber, NLP, text response generator, and text-to-speech translator to generate responses based on personal health spoken phrases.

* Local device with speech-to-text transcriber, NLP, and ML classifier
* Remote personal health data ecosystem with speech-to-text transcriber, NLP, text response generator, and text-to-speech translator

== Potential Applications ==
This technology could be applied in healthcare settings for remote patient monitoring and telemedicine services.

== Problems Solved ==
This technology helps in efficiently processing voice audio and extracting relevant personal health information for further analysis and response generation.

== Benefits ==
The system allows for quick and accurate processing of personal health voice audio, enabling timely responses and interventions in healthcare scenarios.

== Potential Commercial Applications ==
One potential commercial application of this technology could be in developing telehealth platforms for virtual consultations and remote patient monitoring services.

== Possible Prior Art ==
Prior art in this field may include existing voice recognition and transcription systems used in healthcare for medical dictation and documentation purposes.

=== Unanswered Questions ===

=== How does the system ensure the security and privacy of personal health data processed through voice audio? ===
The patent application does not provide details on the security measures implemented to protect personal health data during processing and transmission.

=== What is the accuracy rate of the ML classifier in classifying voice audio as personal health or non-personal health related? ===
The patent application does not mention the specific accuracy rate of the ML classifier in distinguishing between personal health and non-personal health voice audio.


==Original Abstract Submitted==

A system for processing voice audio includes a local device and a remote personal health data ecosystem. The local device includes (1) a local speech-to-text transcriber configured to generate voice text based on voice audio spoken by a user; (2) a local NLP configured to extract spoken phrases from the voice text; and (3) an ML classifier configured to classify the voice audio as either personal health or non-personal health voice audio. The remote personal health data ecosystem includes (1) a remote speech-to-text transcriber configured to generate personal health voice text based on the personal health voice audio; (2) a remote NLP configured to extract personal health spoken phrases from the personal health voice text; (3) a text response generator configured to generate a text response based on the personal health spoken phrases; (4) a text-to-speech translator configured to generate a voice response based on the text response.



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