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Performance-Based Interpreter Identification in Saxophone Audio Recordings

机译:萨克斯录音中基于性能的口译员识别

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We propose a novel approach to the task of identifying performers from their playing styles. We investigate how skilled musicians (Jazz saxophone players in particular) express and communicate their view of the musical and emotional content of musical pieces and how to use this information in order to automatically identify performers. We study deviations of parameters such as pitch, timing, amplitude and timbre both at an inter-note level and at an intra-note level. Our approach to performer identification consists of establishing a performer dependent mapping of inter-note features (essentially a "score" whether or not the score physically exists) to a repertoire of inflections characterized by intra-note features. We present a successful performer identification case study
机译:我们提出了一种新颖的方法来根据表演者的演奏风格来识别表演者。我们研究熟练的音乐家(尤其是爵士萨克斯风演奏者)如何表达和交流他们对音乐作品的音乐和情感内容的看法,以及如何使用此信息来自动识别表演者。我们研究音符间和音符内两个参数的偏差,例如音高,时序,振幅和音色。我们的演奏者识别方法包括建立音符间特征(无论分数是否存在,基本上是一个“分数”)与以音符内特征为特征的全部曲折的依赖演奏者的映射。我们提出了成功的表演者识别案例研究

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