# Autoencoder Based Architecture For Fast & Real Time Audio Style Transfer

arXiv: https://arxiv.org/abs/1812.07159 · HTML: https://mlsanity.com/paper/1812.07159/

## Key facts

- Cited by 1 papers in the map (data through 14 Oct 2026).
- First posted on arXiv 18 Dec 2018.

## Built on by (most cited first, 1 of 1)

- [Environment Transfer for Distributed Systems](https://mlsanity.com/paper/2101.01863/) (2021)

## Abstract (arXiv)

Recently, there has been great interest in the field of audio style transfer, where a stylized audio is generated by imposing the style of a reference audio on the content of a target audio. We improve on the current approaches which use neural networks to extract the content and the style of the audio signal and propose a new autoencoder based architecture for the task. This network generates a stylized audio for a content audio in a single forward pass. The proposed network architecture proves to be advantageous over the quality of audio produced and the time taken to train the network. The network is experimented on speech signals to confirm the validity of our proposal.