论文标题
基于神经网络的原型声音综合框架
A Neural Network Based Framework for Archetypical Sound Synthesis
论文作者
论文摘要
本文介绍了一种算法的初步方法，可以重现人类对声音进行分类的原型结构。特别是，我们提出了一种方法，以在声音中预测人类感知的混乱/秩序水平，并综合新的稍微呈现此功能所需数量的时间。我们采用了一种基于神经网络的方法，以利用其内部倾向来模拟感知和抽象的特征。我们最终讨论了在创造性环境中获得的准确性和可能的含义。
This paper describes a preliminary approach to algorithmically reproduce the archetypical structure adopted by humans to classify sounds. In particular, we propose an approach to predict the human perceived chaos/order level in a sound and synthesize new timbres that present the desired amount of this feature. We adopted a Neural Network based method, in order to exploit its inner predisposition to model perceptive and abstract features. We finally discuss the obtained accuracy and possible implications in creative contexts.
