HP INCFollow


This project focuses on diagnosis of problems in a printer from captured acoustic

signals. Previous researchers already successfully designed a feature generator to

encode the acoustic signals into 6 dimensional features. And they also trained

classifiers on artificial data to predict if a printer is in a good or bad status. The

final target is to make a diagnosis based on the acoustic data, such as pre-alert.

This will help engineers to fix the problems of the printers before customers

making service calls.

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