Real-Time Automatic Music Transcription (AMT) with Zync FPGA

摘要

A real-time automatic music transcription (AMT) system has a great potential for applications and interactions between people and music, such as the popular devices Amazon Echo and Google Home. This paper thus presents a design on chord recognition with the Zync7000 Field-Programmable Gate Array (FPGA), capable of sampling analog frequency signals through a microphone and, in real time, showing sheet music on a smart phone app that corresponds to the user's playing. We demonstrate the design of audio sampling on programming logic and the implementation of frequency transform and vector building on programming system, which is an embedded ARM core on the Zync FPGA. Experimental results show that the logic design spends 574 slices of look-up-tables (LUTs) and 792 slices of flip-flops. Due to the dynamic power consumption on programming system (1399 mW) being significantly higher than the dynamic power dissipation on programming logic (7 mW), the future work of this platform is to design intelligent property (IP) for algorithms of frequency transform, pitch class profile (PCP), and pattern matching with hardware description language (HDL), making the entire system-on-chip (SoC) able to be taped out as an application-specific design for consumer electronics.