Ensemble musicians' synchronization with conductors' gestures: An automated feature-extraction analysis
Ensemble musicians' synchronization with conductors' gestures: An automated feature-extraction analysis
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DOI：
10.1525/mp.2006.24.2.189
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发表时间：
2006-12-01
期刊：
影响因子：
2.3
通讯作者：
Toiviainen, Petri
中科院分区：
文献类型：
--
作者：
Luck, Geoff;Toiviainen, Petri
以前的工作表明，在指挥的手势视觉节拍的感知是与他们所产生的运动的某些物理特性，最显着的负加速度，在垂直轴上的低位置的周期。这些研究结果是基于一些研究，这些研究向参与者展示了一些简单的手势，并且参与者被要求简单地随着节拍敲击。因此，目前尚不清楚这些发现在现实世界的指挥情况下有多普遍，在这种情况下，指挥家使用相当复杂的手势来指挥演奏实际乐器的音乐家合奏。本研究的目的是检查的功能与合奏音乐家同步他们的表现在一个生态有效的设置和开发自动特征提取方法的音频和运动数据的分析指挥的手势。一个光学动作捕捉系统被用来记录一个专家指挥家在20分钟内指挥一个专家音乐家合奏团的手势。还制作了合奏表演的同步音频记录，并与动作捕捉数据同步。四个简短的摘录被选中进行分析，其中两个指挥传达的节拍清晰度很高，两个节拍传达的清晰度很低。从运动数据中计算提取了12个运动变量，并与合奏表演的脉冲进行了交叉相关，后者基于音频信号的频谱通量。分析的结果表明，合奏的性能往往是最高度同步的最大减速沿着轨迹的周期，其次是高垂直速度的周期（一个更高的相关性比减速，但更长的延迟）。
PREVIOUS WORK SUGGESTS THAT THE perception of a visual beat in conductors' gestures is related to certain physical characteristics of the movements they produce, most notably to periods of negative acceleration, and low position in the vertical axis. These findings are based on studies that have presented participants with somewhat simple gestures, and in which participants have been required to simply tap in time with the beat. Thus, it is not clear how generalizable these findings are to real-world conducting situations, in which a conductor uses considerably more complex gestures to direct an ensemble of musicians playing actual instruments. The aims of the present study were to examine the features of conductors' gestures with which ensemble musicians synchronize their performance in an ecologically valid setting and to develop automatic feature extraction methods for the analysis of audio and movement data. An optical motion capture system was used to record the gestures of an expert conductor directing an ensemble of expert musicians over a 20-minute period. A simultaneous audio recording of the performance of the ensemble was also made and synchronized with the motion capture data. Four short excerpts were selected for analysis, two in which the conductor communicated the beat with high clarity, and two in which the beat was communicated with low clarity. Twelve movement variables were computationally extracted from the movement data and cross-correlated with the pulse of the ensemble's performance, the latter based on the spectral flux of the audio signal. Results of the analysis indicated that the ensemble's performance tended to be most highly synchronized with periods of maximal deceleration along the trajectory, followed by periods of high vertical velocity (a higher correlation than deceleration but a longer delay).