PDF(Pubmed)
Abstract：
Musical prosody is characterized by the acoustic variations that make music expressive. However, few systematic and scalable studies exist on the function it serves or on effective tools to carry out such studies. To address this gap, we introduce a novel approach to capturing information about prosodic functions through a citizen science paradigm. In typical bottom-up approaches to studying musical prosody, acoustic properties in performed music and basic musical structures such as accents and phrases are mapped to prosodic functions, namely segmentation and prominence. In contrast, our top-down, human-centered method puts listener annotations of musical prosodic functions first, to analyze the connection between these functions, the underlying musical structures, and acoustic properties. The method is applied primarily to the exploring of segmentation and prominence in performed solo piano music. These prosodic functions are marked by means of four annotation types-boundaries, regions, note groups, and comments-in the CosmoNote web-based citizen science platform, which presents the music signal or MIDI data and related acoustic features in information layers that can be toggled on and off. Various annotation strategies are discussed and appraised: intuitive vs. analytical; real-time vs. retrospective; and, audio-based vs. visual. The end-to-end process of the data collection is described, from the providing of prosodic examples to the structuring and formatting of the annotation data for analysis, to techniques for preventing precision errors. The aim is to obtain reliable and coherent annotations that can be applied to theoretical and data-driven models of musical prosody. The outcomes include a growing library of prosodic examples with the goal of achieving an annotation convention for studying musical prosody in performed music.
摘要：
音乐韵律的特点是使音乐富有表现力的声学变化。然而,关于它所服务的功能或开展此类研究的有效工具，很少有系统和可扩展的研究。为了解决这个差距，我们引入了一种新颖的方法来通过公民科学范式捕获有关韵律功能的信息。在典型的自下而上的方法来研究音乐韵律，演奏音乐中的声学特性和基本音乐结构，如口音和短语，被映射到韵律功能，即分割和突出。相比之下,我们自上而下,以人为本的方法将听众对音乐韵律功能的注释放在第一位，为了分析这些函数之间的联系，底层的音乐结构，和声学特性。该方法主要用于探索演奏钢琴独奏音乐中的分割和突出性。这些韵律函数通过四种注释类型-边界来标记，regions,notegroups,和评论-在基于CosmoNote网络的公民科学平台上，它在可以打开和关闭的信息层中呈现音乐信号或MIDI数据和相关的声学特征。讨论和评价了各种注释策略：直观与分析;实时与回顾性；以及，基于音频的vs.视觉。描述了数据收集的端到端过程，从提供韵律示例到分析注释数据的结构化和格式化，防止精度误差的技术。目的是获得可靠且连贯的注释，这些注释可应用于音乐韵律的理论和数据驱动模型。结果包括越来越多的韵律示例库，目的是实现注释约定以研究演奏音乐中的音乐韵律。
