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dc.contributor.authorFaulkner, Sam 14:08:08 (GMT) 14:08:08 (GMT)
dc.description.abstractThis paper was created with the goal of researching the different impacts that background noise can have on listeners' ability to interpret speech. The brain is responsible for separating speech and noise, but this can be difficult if this organ is damaged or the noise is too overwhelming to separate out. I partnered with Augmented to see whether their noise reduction software can do some of this processing on behalf of the brain. This would reduce cognitive effort and help make conversations more accessible in noisy environments. To research this topic, I created a study that evaluated participants' ability to understand words that have often confused sounds in them. These words were presented with different types of voices, with different kinds of background noise, and both with and without processing from AugmentedHearing's algorithms. Preliminary results indicate that intelligibility scores were not higher for the denoised speech compared to the noisy speech. This was not the expected result, however, there is still much to consider within the data. These preliminary findings are grounds for further studies and will hopefully lead to an improvement in future iterations of the speech processing software.en
dc.publisherUniversity of Waterlooen
dc.relation.ispartofseriesINTEG 420: Senior Research Project / PSYCH 484: Independent Studyen
dc.rightsAttribution-NonCommercial-NoDerivatives 4.0 International*
dc.subjectartificial intelligenceen
dc.subjectsound processingen
dc.subjectnoise removalen
dc.titleEvaluating Speech Intelligibility with Processed Sounden
dc.typeBachelor Thesisen of Environment, Resources and Sustainabilityen Integrationen
uws-etd.degreeBachelor of Knowledge Integrationen
uws.contributor.advisorWhite, Katherine
uws.contributor.affiliation1Faculty of Environmenten

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Attribution-NonCommercial-NoDerivatives 4.0 International
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