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Showing 1 to 4 of 4 for “"speech denoising"”.
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Speech denoising using nonnegative matrix factorization and neural networks
… we are concerned specifically with separating speech of a speaker from background noise as another source. So we deal with single-channel mixtures of speech with stationary, semi-stationary and non-stationary noise types. This is what we define as speech denoising. Our goal is to build a system …
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Multi-modal and deep learning for robust speech recognition
Automatic speech recognition (ASR) decodes speech signals into text. While ASR can produce accurate word recognition in clean environments, system performance can degrade dramatically when noise and reverberation are present. In this thesis, speech denoising and model adaptation for robust speech …
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Modeling and Evaluating Human Sound Localization in the Natural Environment
… In the fourth study, we used a model of human speech perception as a perceptual metric to improve speech denoising. We found that while this perceptual metric improved denoising over standard approaches, a simple model of the cochlea performed similarly, suggesting much of the benefit of this …
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Audio computing in the wild: frameworks for big data and small computers
… in real time; a lightweight custom chipset for speech enhancement on hand-held devices; instant music analysis engine running on smartphone apps. In all those applications, efficient machine learning algorithms are supposed to achieve not only a good performance, but also a great …