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Looking for New, Not Known Music Only: Music Retrieval by Melody Style

机译:寻找新的,不是已知的音乐:音乐通过旋律风格检索

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With the growth of digital music, content-based music retrieval (CBMR) has attracted increasingly attention. For most CBMR systems, the task is to return music objects similar to query in syntactic properties such as pitch and interval contour sequence. These approaches provide users the capability to look for music that has been heard. However, sometimes, listeners are looking, not for music they have been known, but for music that is new to them. Moreover, people sometimes want to retrieve music that "feels like" another music object or a music style. To the best of our knowledge, no published work investigates the content-based music style retrieval. This paper describes an approach for CBMR by melody style. We proposed four types of query specification for melody style query. The output of the melody style query is a music list ranked by the degree of relevance, in terms of music style, to the query. We developed the melody style mining algorithm to obtain the melody style classification rules. The style ranking is determined by the style classification rules. The experiment showed the proposed approach provides a satisfactory way for query by melody style.
机译:随着数字音乐的增长,基于内容的音乐检索(CBMR)引起了越来越关注。对于大多数CBMR系统,任务是返回类似于句法属性的查询的音乐对象,例如音高和间隔轮廓序列。这些方法为用户提供了寻找听到的音乐的能力。但是,有时候,听众正在寻找,不是他们所知的音乐,而是为了对他们来说是新的音乐。此外,人们有时希望检索“感觉像”另一个音乐对象或音乐风格的音乐。据我们所知,没有公布的工作调查基于内容的音乐风格检索。本文介绍了旋律风格CBMR的方法。我们提出了四种类型的旋律样式查询Query规范。旋律样式查询的输出是在查询的音乐风格方面排名的音乐列表。我们开发了旋律风格挖掘算法,以获得旋律样式分类规则。样式排名由风格分类规则决定。实验表明,所提出的方法通过旋律风格提供了令人满意的方式。

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