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More on the Normalization of Syllable Prominence Ratings

机译:有关音节突出等级规范化的更多信息

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The perception of syllable prominence depends to a limited extent on the acoustic properties of the speech signal in question. Psychoacoustic factors are involved as well. Thus, research often relies on two types of data: subjective prominence ratings collected in perception experiments and acoustic measures. A problem with the rating data is noise resulting from individual approaches to the rating task. This paper addresses the question of how this noise can be reduced by normalization, evaluating 12 normalization methods. In a perception experiment, prominence ratings concerning German read speech were collected. From the raw rating data 12 different 'mirror' data-sets were computed according to the 12 methods. Each mirror data-set was correlated with the same set of underlying acoustic data. The multiple regression setup included raw syllable duration as well as within-syllable maximum FO and intensity. Adjusted r2-values could be raised considerably with selected methods.
机译:音节突出的感觉在一定程度上取决于所讨论的语音信号的声学特性。心理声学因素也涉及到。因此,研究通常依赖于两种类型的数据:在感知实验中收集的主观突出评分和声学测量。评级数据存在问题,这是由于单独执行评级任务而产生的噪音。本文通过评估12种归一化方法,解决了如何通过归一化降低噪声的问题。在感知实验中,收集了有关德语阅读语音的突出等级。从原始评级数据中,根据12种方法计算出12个不同的“镜像”数据集。每个镜像数据集都与相同的基础声学数据集相关。多元回归设置包括原始音节持续时间以及音节内最大FO和强度。调整后的r2值可以通过某些方法显着提高。

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