你太离题了!加速度计数据是否足以测量舞蹈节奏?

Augusto Dias Pereira dos Santos, Lie Ming Tang, L. Loke, Roberto Martínez Maldonado
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引用次数: 6

摘要

节奏是人们学习舞蹈最基本的技能。初学者需要练习,但也需要密切的指导和不断的反馈。然而,在大多数舞蹈课上,老师经常发现很难注意到每个学生。这个问题的一个可能的解决方案是,通过客观地评估学生运动数据的节奏,自动向学生提供反馈。但是,与舞蹈专家相比,完全自动化的方法在评估舞蹈表演方面有多有效呢?我们进行了一项研究,旨在通过从加速度计数据流中“测量”舞蹈节奏,并将算法结果与专家的人类判断进行对比,来探索这一点。我们开发了RiMoDe,这是一种追踪身体节奏技能的算法,并收集了一个数据集,其中包括由专业舞蹈教师对7名舞蹈学生的94个舞蹈练习进行的282个独立评估。我们的发现揭示了纯粹的算法方法与专家如何评估舞蹈节奏之间的主要差距。在评估节奏时,我们确定了6个重要的主题。我们将讨论如何考虑这些主题,并将其纳入旨在支持人们学习舞蹈的未来系统。
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You Are Off The Beat!: Is Accelerometer Data Enough for Measuring Dance Rhythm?
Rhythm is the most basic skill for people learning to dance. Beginners need practice but also close coaching and constant feedback. However, in most dance classes teachers often find challenging to provide attention to each student. A possible solution to this problem would be to automate the provision of feedback to students by objectively assessing rhythm from their movement data. But how effective would a fully automated approach be compared to dance experts in evaluating dance performance? We conducted a study aimed at exploring this by 'measuring' dance rhythm from accelerometer data streams and contrasting the algorithm results with expert human judgement. We developed RiMoDe, an algorithm that tracks bodily rhythmic skills, and gathered a dataset that includes 282 independent evaluations made by expert dance teachers on 94 dance exercises performed by 7 dance students. Our findings revealed major gaps between a purely algorithmic approach and how experts evaluate dance rhythm. We identified 6 themes that are important when assessing rhythm. We discuss how these themes should be considered and incorporated into future systems aimed at supporting people learning to dance.
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