Instrument Classi cation for Cochlear Implant Filtering using Convolutional Neural Networks
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2021-01-26
Language
en
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Abstract
In this thesis, Convolutional Neural Networks are used to classify instru-
ments in audio les containing musical instruments. In particular, music
enjoyment for Cochlear Implant users is central in this thesis. Therefore,
there are di erent frequency lters applied in the preprocessing, to further
explore the optimal preprocessing when frequency space is limited. The
results show that, in line with previous research, there is a certain range
that is particularly important in instrument recognition. However, in this
research this range di ers, possibly because this research is focused on music
whereas the original research is based on speech. The classi cation when
ltered on this range outperforms the classi cation when presented with the
full spectrum.
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Faculteit der Sociale Wetenschappen