Construction and recognition of acoustic ID of ancient coins based on deep learning of artificial intelligence for audio signals

Abstract

In the field of cultural heritage protection, it is significant to establish a reliable ID (identifier) for valuable cultural and artistic items. At present, the identification of ancient cultural relics is mainly based on image information, such as pictures, 3D (three-dimensional) scanning, X-ray and CT (computed tomography) data. However, in many cases, it is impossible to identify whether slight damage, partial restorations, or ancient cultural relics have been replaced by fakes by using image information. In the era of digital duplication, more reliable identity information is urgently needed. The main technical challenge of an acoustic analysis system for ancient coins based on artificial intelligence technology is to find a non-destructive, fast and accurate identification method for ancient cultural relics. The recognition method includes two main modules: the artificial audio data sampling device and deep learning. In addition, this paper has completed the analysis of the vibration spectrum features of 19 ancient coins and realized the whole process of acoustic ID construction. The open-source platform Easy DL was used to analyze the multidimensional vibration spectrum curve feature extraction and identification. This method enables audio signal signature recognition technology to be applied in the display, preservation, transaction and safety management of ancient coins and other cultural relics.