The seminal work of Gatys et al. demonstrated the power of Convolutional Neural Networks
(CNNs) in creating artistic imagery by separating and recombining image content and style …

The utilization of deep learning techniques in generating various contents (such as image,
text, etc.) has become a trend. Especially music, the topic of this paper, has attracted …

Recently, with the advent of Convolutional Neural Network (CNN) era, Neural style transfer
on images has become a very active research topic and the style of an image can be …

Audio signals are classified into speech, music, and environmental sounds. From the
evolution of audio features, an adequate amount of work has been seen in speech and …

In this transformation we present a rhythmically constrained audio style transfer technique
for automatic mixing and mashing of two audio inputs. In this transformation the rhythmic and …

Synthesizing and converting environmental sounds have the potential for many applications
such as supporting movie and game production, data augmentation for sound event …

The concept of textures is not new to humans. In general, a texture is the physical feel of
something when touched, viewed, or heard. For images, the texture could be categorized …

Within the creative industries, music information retrieval techniques are now being applied
in a variety of music creation and production applications. Audio artists incorporate …

Recently the continuance of the pandemic has propelled the propagation of offensive
content associated with Covid-19 on social media. Some researchers begin to develop …

Neural networks have gained extensive usage in various tasks such as classification, object
detection, and style transfer, particularly with images and text. Audio style transfer has made …