Deep learning researches on the transformation problems for image and text have raised great attention. However, present methods for music feature transfer using neural networks are far from practical application. In this paper, we initiate a novel system for transferring the texture of music, and release it as an open source project. Its core algorithm is composed of a converter which represents sounds as texture spectra, a corresponding reconstructor and a feed-forward transfer network. We evaluate this system from multiple perspectives, and experimental results reveal that it achieves convincing results in both sound effects and computational performance.

翻译：对图像和文字的转化问题的深层学习研究引起了人们的极大关注。然而,目前使用神经网络的音乐特征传输方法远非实际应用。在本文中,我们启动了一个新颖的音乐质地传输系统,并将其作为开放源项目发布。其核心算法由转换器组成,该转换器代表着质谱光谱的声音、一个相应的重建器和一个进化前传输网络。我们从多个角度评估了这个系统,实验结果显示,它在音效和计算性能两方面都取得了令人信服的结果。