[论文解读] madmom: a new Python Audio and Music Signal Processing Library

Sebastian Böck, Filip Korzeniowski+3 more|arXiv (Cornell University)|May 23, 2016

Music and Audio Processing被引用 17

一句话总结

本文介绍了 madmom，一个用于音频和音乐信号处理的开源 Python 库，该库将低层级特征提取、高层音乐分析以及机器学习技术整合到一个统一且用户友好的框架中。该库专为快速原型设计和可重现的研究而设计，可无缝将原型转化为具有最先进性能的多核、可序列化的处理流水线，适用于音符起始点检测、节拍跟踪、节拍速度估计和钢琴音符转录等任务。

ABSTRACT

In this paper, we present madmom, an open-source audio processing and music information retrieval (MIR) library written in Python. madmom features a concise, NumPy-compatible, object oriented design with simple calling conventions and sensible default values for all parameters, which facilitates fast prototyping of MIR applications. Prototypes can be seamlessly converted into callable processing pipelines through madmom's concept of Processors, callable objects that run transparently on multiple cores. Processors can also be serialised, saved, and re-run to allow results to be easily reproduced anywhere. Apart from low-level audio processing, madmom puts emphasis on musically meaningful high-level features. Many of these incorporate machine learning techniques and madmom provides a module that implements some in MIR commonly used methods such as hidden Markov models and neural networks. Additionally, madmom comes with several state-of-the-art MIR algorithms for onset detection, beat, downbeat and meter tracking, tempo estimation, and piano transcription. These can easily be incorporated into bigger MIR systems or run as stand-alone programs.

研究动机与目标

• 解决音乐信息检索（MIR）领域中缺乏综合性、集成化库的问题，这些库能够整合低层级音频特征、高层音乐分析与机器学习组件。

提出的方法

• 采用面向对象设计，使用继承自 NumPy 的 ndarray 的数据类，以实现高效的数据数组处理与元数据管理。

实验结果

研究问题

• RQ1 如何通过一个统一且可扩展的软件框架，简化 MIR 应用的开发与部署？

主要发现

• madmom 在多个 MIR 任务中表现出最先进性能，包括音符起始点检测（在 MIREX 2013 中排名第一）、节拍跟踪（在 MIREX 2015 中排名第一）以及节拍速度估计（在 MIREX 2015 中排名第一）。