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Generative Fourier-Based Auto-encoders: Preliminary Results

Conference paper
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Part of the Lecture Notes in Computer Science book series (LNCS, volume 12566)

Abstract

This paper presents a new general framework for turning any auto-encoder into a generative model. Here, we focus on a specific instantiation of the auto-encoder that consists of the Short Time Fourier Transform as an encoder, and a composition of the Griffin-Lim Algorithm and the pseudo inverse of the Short Time Fourier Transform as a decoder. In order to allow sampling from this model, we propose to use the probabilistic Principal Component Analysis. We show preliminary results on the UrbanSound8K Dataset.

Keywords

Auto-encoders Generative modelling Fourier Transform 

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Copyright information

© Springer Nature Switzerland AG 2020

Authors and Affiliations

  1. 1.Vrije Universiteit AmsterdamAmsterdamThe Netherlands

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