The coronavirus pandemic became a major risk in global public health. The outbreak is caused by SARS-CoV-2, a member of the coronavirus family. Though the images of the virus are familiar to us, in the present study, an attempt is made to hear the coronavirus by translating its protein spike into audio sequences. The musical features such as pitch, timbre, volume and duration are mapped based on the coronavirus protein sequence. Three different viruses Influenza, Ebola and Coronavirus were studied and compared through their auditory virus sequences by implementing Haar wavelet transform. The sonification of the coronavirus benefits in understanding the protein structures by enhancing the hidden features. Further, it makes a clear difference in the representation of coronavirus compared with other viruses, which will help in various research works related to virus sequence. This evolves as a simplified and novel way of representing the conventional computational methods.

冠状病毒大流行已成为全球公共卫生的主要风险。此次爆发是由冠状病毒家族的一员 SARS-CoV-2 引起的。尽管病毒的图像对我们来说很熟悉，但在本研究中，我们试图通过将其蛋白质峰值转化为音频序列来听到冠状病毒的声音。音高、音色、音量和持续时间等音乐特征是根据冠状病毒蛋白质序列绘制的。通过实施 Haar 小波变换，通过它们的听觉病毒序列研究和比较三种不同的病毒流感、埃博拉和冠状病毒。冠状病毒的超声化有利于通过增强隐藏的特征来理解蛋白质结构。此外，与其他病毒相比，它在冠状病毒的表现上有明显的不同，这将有助于与病毒序列相关的各种研究工作。这演变为一种表示传统计算方法的简化和新颖的方式。