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Samuel J. Yang

2 accepted papers

2023

Speech Intelligibility Classifiers from 550k Disordered Speech Samples

ICASSP 2023accepted

We developed dysarthric speech intelligibility classifiers on 551,176 disordered speech samples contributed by a diverse set of 468 speakers, with a range of self-reported speaking disorders and rated for their overall intelligibility on a five-point scale. We trained three models following differen…

Cited by 0SourceScholar
2021

Physics-Enhanced Machine Learning for Virtual Fluorescence Microscopy

ICCV 2021poster

This paper introduces a new method of data-driven microscope design for virtual fluorescence microscopy. We use a deep neural network (DNN) to effectively design optical patterns for specimen illumination that substantially improve upon the ability to infer fluorescence image information from unstai…

Cited by 18PDFcodeScholar