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Improving Drumming Robot Via Attention Transformer Network

arXiv 2310.02565 ↗First posted 4 Oct 2023cs.RO cs.AIcited by 0

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Abstract (arXiv)

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.

Key facts. No citing papers in the map yet (data through 7 Oct 2026). Builds on 23 of its 50 references that are in the map. First posted on arXiv 4 Oct 2023.

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23 of 50 references.

References · 23

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11 more
  1. 2015Multi-Scale Context Aggregation by Dilated Convolutionscited by 1,128
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  10. 2023Improving Video Violence Recognition with Human Interaction Learning on 3D Skeleton Point Cloudscited by 1
  11. 2023AIoT-Based Drum Transcription Robot using Convolutional Neural Networkscited by 1

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