音频MIR系统、符号MIR系统和音乐定义语言演示系统综述

Hanchao Li, Zhouhemu Tang, Xiang Fei, K. Chao, Ming Yang, Chaobo He
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引用次数: 2

摘要

音乐识别系统最近变得很流行。它们基于音频或符号方法,将用户的查询与现有的音乐数据库进行比较。研究表明,基于音频的方法系统是一种很好的声波存储方法。然而,限制是为了说明音乐的内容。基于符号的方法系统在表示音乐内容方面做得很好,包括识别相似的模式,但在创作音乐方面受到限制,例如电子音乐。我们还在之前的神经网络系统的基础上,使用音乐定义语言(MDL)和音乐操作语言(MML)进行了一些详细的测试。此外,我们用新的旋律查询测试了我们之前的分类系统,看看它如何处理外部音乐片段,这超出了自组织映射的自我测试。结果表明,该系统可以对变奏类型进行分类,包括关键变奏、扩展和缩减,优于现有的音乐信息检索(MIR)系统。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
A Survey of Audio MIR Systems, Symbolic MIR Systems and a Music Definition Language Demo-System
Music Recognition System has becoming popular these days. They are based on either audio or symbolic method, which compares the user's query with the existing music database. The investigation has shown that the audio-based method system is good for storing sound waves. However, the limitation is to illustrate the content of the music. The symbolic-based method system doing well in representing the content of the music, including recognize similar patterns, but limitation in creating the music, e.g., Electronic Music. We also carried some detailed tests based on the previous Neural Network systems, with Music Definition Language (MDL) and Music Manipulation Language (MML). Furthermore, we have tested our previous classification system with new melody query, to see how it can handle with external music pieces, which beyond the self-testing from a self-organising-map. The conclusion is that our system can classify variation type, including key variations, expansion and reduction, which is better than those existing Music Information Retrieval (MIR) systems.
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