Reconstructing Images and Audio: Multi-modal autoencoders

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Issue Date
2020-07-01
Language
en
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Abstract
In this thesis, a multi-modal auto-encoder is built that reconstructs both images and audio. The goal is to build a multi-modal auto-encoder that is capable of learning a shared representation between images of digits and audio of the pronunciation of the digits. This model, while fairly accurate on digits, does not perform very well on the audio data.
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Faculteit der Sociale Wetenschappen