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Music information retrieval using Query-by-humming based on the dynamic time warping

机译:基于动态时间翘曲的逐个嗡嗡声检索音乐信息检索

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Query-by-humming (QBH) is a content-based music information retrieval system that use humming as its query. Naturally, human cannot hum or sing perfectly. They may sing in different pitch, key, or tempo thus can affect the retrieval performance of the system. It becomes a challenge to build an effective QBH system despite all of the query imperfection. Many approaches have been proposed to develop QBH systems, such as contour approach, hidden Markov model, and dynamic time warping. One of a simple yet promising method for building a QBH system is the Dynamic Time Warping. In this paper, we describe our works on building a QBH system using the Dynamic Time Warping to search for Indonesian songs stored in the MIDI format. To evaluate the system, we use accuracy rate for humming transcription evaluation and mean reciprocal rank for retrieval evaluation. Most of retrieval results are in the first rank thus shown that the Dynamic Time Warping is effective to be applied on this task.
机译:逐个嗡嗡声(QBH)是一种基于内容的音乐信息检索系统,其使用Humming作为其查询。当然,人类不能完全嗡嗡疾或唱歌。它们可以在不同的音高,键或速度中唱歌,因此可以影响系统的检索性能。尽管所有查询的缺陷,但建立有效的QBH系统就是一个挑战。已经提出了许多方法来开发QBH系统,例如轮廓方法,隐马尔可夫模型和动态时间翘曲。一个简单但有希望的建筑QBH系统的方法之一是动态时间翘曲。在本文中,我们描述了使用动态时间扭曲以搜索存储在MIDI格式的印度尼西亚歌曲的QBH系统的作品。为了评估系统,我们使用嗡嗡声转录评估的准确率和平均互核等级进行检索评估。大多数检索结果都在第一排名中,因此表明动态时间翘曲是有效应用于此任务。

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