用户可以建立自己的数据网络使用的脚本语言运行时间。Marsyas提供了一个框架，用于建设应用而不是Marsyas文件的一套应用操作或者在个人声音档或收藏简单文本文件包含soundfiles名单。收藏文件应该包含在soundfiles具有相同的采样率为Marsyas没有执行自动取样44100赫兹之间转换(除了22050赫兹)。特征提取过程的结果都存储在Marsyas作为文本文件可以用来在Weka机器学习的环境。并联Marsyas集一些基本的机器学习的组件。
MIRtoolbox也提供了用一个简单和自适应语法来构建一个接一个复杂计算的可能性。与其相反，MIRtoolbox Marsyas不提供实时的能力。另一方面，其object-based架构使得显著简化语法。MIRtoolbox也可以分析音频文件的文件夹，并能处理不同的采样率文件夹，不需任何转换。MIRtoolbox数据数值可以进一步处理，能够在在Matlab环境下直接的帮助，或者其他工具箱可以出口到文本文件。
5. MIRTOOLBOX的有效性
紧跟着第一个Matlab工具箱的是MIDItoolbox，它致力于分析因音乐的符号表征,而MIRtoolbox是免费提供给研究团体的。它可以从下面的网页下载： http://www.cc.jyu.fi/~lartillo/mirtoolbox
6. 感谢
这份工作得到欧盟委员会的支持(雀巢杯“用音乐来调整大脑”代码028570)。工具箱的发展也从与其他合作伙伴生产合作项目,特别是Eerola Tuomas，何塞。Fornari，马可Fabiani，以及我们部门的学生的合作中得得到了益处。
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