  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.
