Style Transfer of Audio Effects with Differentiable Signal Processing

Audio style transfer

“Style transfer” among images has recently emerged as a very active research topic, fuelled by the power of convolution neural networks (CNNs), and has become fast a very popular technology in social media. This paper investigates the analogous problem in the audio domain: How to transfer the style of a reference audio signal to a target audio content? We propose a flexible framework for the ta...

Audio Signal Processing

A Digital Signal Processing Laboratory with Style

A digital signal processing (DSP) laboratory is under development at Kettering University. The laboratory materials and procedures are designed to accommodate varied student learning styles. The implications of this learning-style based approach to undergraduate DSP laboratory development are presented, including descriptions of experimental procedures.

Time Domain Neural Audio Style Transfer

A recently published method for audio style transfer has shown how to extend the process of image style transfer to audio. This method synthesizes audio "content" and "style" independently using the magnitudes of a short time Fourier transform, shallow convolutional networks with randomly initialized filters, and iterative phase reconstruction with Griffin-Lim. In this work, we explore whether ...

Neural Style Transfer for Audio Spectograms

There has been fascinating work on creating artistic transformations of images by Gatys et al. This was revolutionary in how we can in some sense alter the “style” of an image while generally preserving its “content”. In this work, we present a method for creating new sounds using a similar approach. For demonstration, we investigate two different tasks, resulting in bandwidth expansion/compres...