Predictive Real-Time Beat Tracking from Music for Embedded Application

2018 IEEE Conference on Multimedia Information Processing and Retrieval (MIPR) Pub Date : 2018-04-10 DOI:10.1109/MIPR.2018.00068

Irfan Al-Hussaini, Ahmed Imtiaz Humayun, Samiul Alam, Shariful Islam Foysal, A. A. Masud, Arafat Mahmud, R. Chowdhury, N. Ibtehaz, S. U. Zaman, Rakib Hyder, Sayeed Shafayet Chowdhury, M. A. Haque

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引用次数: 8

Abstract

Beat tracking from music signals has significant importance in multimedia information retrieval systems, especially in cover song detection. A predictive real-time beat tracking system can also be used to assist musicians performing live. In this paper we present a real-time beat tracking algorithm, fast enough to be implemented on an embedded system. The onset of a note is detected using a maximum filter approach that suppresses the effect of vibrato. Beats are predicted a second in advance using a causal variant of Dynamic Programming. We have employed an onset memoization algorithm, to reduce the computational resources required. Raspberry Pi was chosen as our preferred development board. We have demonstrated through experimental results that the proposed approach can satisfactorily estimate beat positions from a music signal in real-time with an average continuity score (AMLt) of 0.67.

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预测实时节拍跟踪从音乐嵌入式应用程序

音乐信号的节拍跟踪在多媒体信息检索系统，特别是翻唱歌曲检测中具有重要的意义。预测实时节拍跟踪系统也可用于协助音乐家现场表演。本文提出了一种实时温度跟踪算法，速度快到可以在嵌入式系统上实现。一个音符的开始是用最大的过滤器方法来检测的，这种方法抑制了颤音的影响。使用动态规划的因果变体提前一秒预测节拍。我们采用了一种起始记忆算法，以减少所需的计算资源。树莓派被选为我们首选的开发板。我们通过实验结果证明，该方法可以令人满意地实时估计音乐信号的拍位，平均连续分数(AMLt)为0.67。

本文章由计算机程序翻译，如有差异，请以英文原文为准。

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2018 IEEE Conference on Multimedia Information Processing and Retrieval (MIPR)

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