Robotic technology has been widely used in nowadays society, which has made great progress in various fields such as agriculture, manufacturing and entertainment. In this paper, we focus on the topic of drumming robots in entertainment. To this end, we introduce an improving drumming robot that can automatically complete music transcription based on the popular vision transformer network based on the attention mechanism. Equipped with the attention transformer network, our method can efficiently handle the sequential audio embedding input and model their global long-range dependencies. Massive experimental results demonstrate that the improving algorithm can help the drumming robot promote drum classification performance, which can also help the robot to enjoy a variety of smart applications and services.

翻译：机器人技术已在当今社会广泛应用，并在农业、制造和娱乐等领域取得了显著进展。本文聚焦于娱乐领域的鼓手机器人课题，提出一种基于注意力机制的流行视觉变换器网络，实现可自动完成音乐转录的改进型鼓手机器人。通过配备注意力变换网络，该方法能够高效处理连续的音频嵌入输入，并对其全局长程依赖关系进行建模。大量实验结果表明，该改进算法不仅能够提升鼓手机器人的鼓点分类性能，还能帮助机器人实现多种智能应用与服务。