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Wearable Assistance for the Ballroom-Dance Hobbyist - Holistic Rhythm Analysis and Dance-Style Classification

机译：交际舞爱好者的可穿戴协助-整体节奏分析和舞蹈风格分类

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摘要

Automated retrieval of high level information from ballroom dance music is challenging, but has many practical applications. These include, for example, a fully automatic ballroom dance D.J., robots capable of performing ballroom dances, or wearable dance-assistance, as considered herein. It is necessary, for such a system, to retrieve information about the song''s quarter note tempo, meter and beat positions. Further, the system must be able to discriminate between the nine Standard and Latin ballroom dances. In this paper we present a model that combines all these requirements in one holistic approach. The polyphonic input is processed by a simplified psychoacoustic model. Tatum, tempo and meter features are extracted using resonant filters. The filter output is used for beat tracking. The extracted features are used for a ballroom dance- style classification by Support-Vector-Machines. To show the high effectiveness regarding dance-style recognition and beat tracking, test-runs are carried out on a database containing 1.8k titles.
机译：从舞厅舞曲中自动检索高级信息具有挑战性，但具有许多实际应用。这些包括，例如，如本文所考虑的全自动舞厅舞D.J.，能够执行舞厅舞的机器人或可穿戴的舞伴。对于这样的系统，有必要检索有关歌曲的四分音符速度，节拍和节拍位置的信息。此外，系统必须能够区分九种标准舞和拉丁舞。在本文中，我们提出了一个模型，该模型以一种整体方法结合了所有这些要求。复音输入由简化的心理声学模型处理。使用共振滤波器提取基准，速度和仪表特征。滤波器输出用于节拍跟踪。提取的特征用于Support-Vector-Machines的舞厅舞风格分类。为了显示关于舞蹈风格识别和节拍跟踪的高效率，在包含1.8k标题的数据库中进行了测试。

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