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Music Information Retrieval: Recent Developments and Applications

机译:音乐信息检索:最新发展和应用

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We provide a survey of the field of Music Information Retrieval (MIR), in particular paying attention to latest developments, such as semantic auto-tagging and user-centric retrieval and recommendation approaches. We first elaborate on well-established and proven methods for feature extraction and music indexing, from both the audio signal and contextual data sources about music items, such as web pages or collaborative tags. These in turn enable a wide variety of music retrieval tasks, such as semantic music search or music identification ("query by example"). Subsequently, we review current work on user analysis and modeling in the context of music recommendation and retrieval, addressing the recent trend towards user-centric and adaptive approaches and systems. A discussion follows about the important aspect of how various MIR approaches to different problems are evaluated and compared. Eventually, a discussion about the major open challenges concludes the survey.
机译:我们提供了音乐信息检索(MIR)领域的调查,尤其关注最新发展,例如语义自动标记和以用户为中心的检索和推荐方法。我们首先从音频信号和有关音乐项目的上下文数据源(例如网页或协作标签)中,详细阐述成熟的,经过验证的特征提取和音乐索引方法。这些反过来又实现了各种各样的音乐检索任务,例如语义音乐搜索或音乐标识(“示例查询”)。随后,我们在音乐推荐和检索的背景下回顾了有关用户分析和建模的当前工作,以应对近来以用户为中心和自适应方法和系统的趋势。接下来的讨论是关于如何评估和比较针对不同问题的各种MIR方法的重要方面。最终,关于主要的公开挑战的讨论结束了调查。

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