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首页> 外文期刊>Music & Science >Spectral Pitch Similarity is a Predictor of Perceived Change in Sound- as Well as Note-Based Music
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Spectral Pitch Similarity is a Predictor of Perceived Change in Sound- as Well as Note-Based Music

机译：光谱间距相似性是声音的感知变化的预测因素以及基于音符的音乐

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Spectral pitch similarity (SPS) is a measure of the similarity between spectra of any pair of sounds. It has proved powerful in predicting perceived stability and fit of notes and chords in various tonal and microtonal instrumental contexts, that is, with discrete tones whose spectra are harmonic or close to harmonic. Here we assess the possible contribution of SPS to listeners’ continuous perceptions of change in music with fewer discrete events and with noisy or profoundly inharmonic sounds, such as electroacoustic music. Previous studies have shown that time series of perception of change in a range of music can be reasonably represented by time series models, whose predictors comprise autoregression together with series representing acoustic intensity and, usually, the timbral parameter spectral flatness. Here, we study possible roles for SPS in such models of continuous perceptions of change in a range of both instrumental (note-based) and sound-based music (generally containing more noise and fewer discrete events). In the first analysis, perceived change in three pieces of electroacoustic and one of piano music is modeled, to assess the possible contribution of (de-noised) SPS in cooperation with acoustic intensity and spectral flatness series. In the second analysis, a broad range of nine pieces is studied in relation to the wider range of distinctive spectral predictors useful in previous perceptual work, together with intensity and SPS. The second analysis uses cross-sectional (mixed-effects) time series analysis to take advantage of all the individual response series in the dataset, and to assess the possible generality of a predictive role for SPS. SPS proves to be a useful feature, making a predictive contribution distinct from other spectral parameters. Because SPS is a psychoacoustic “bottom up” feature, it may have wide applicability across both the familiar and the unfamiliar in the music to which we are exposed.
机译：光谱间距相似度（SPS）是任何对声音的光谱之间的相似性的量度。它证明了强大的是预测各种音调和微观乐器背景中的衡量和和弦的感知稳定性和符合和弦，即，具有离散音的离散音，其光谱是谐波或接近谐波的。在这里，我们评估了SP对听众的不断对音乐变化的不断看法，以及较少的离散事件以及嘈杂或深刻的单声道声音，例如电声学音乐。以前的研究表明，一系列音乐的变化的时间序列可以合理地由时间序列模型代表，其预测器包括与表示声学强度的序列一起的自回归，并且通常是Timbral参数光谱平坦度。在这里，我们在这种模型中研究了SPS的可能角色，这些模型在一系列乐器（基于注意事项）和基于基于声音的音乐（通常包含更多噪声和更少的离散事件）。在第一次分析中，建模了三件电声和钢琴音乐之一的感知变化，以评估（发出）SP与声学强度和光谱平坦系列合作的可能贡献。在第二种分析中，研究了广泛的九个片，与在先前的感知工作中有用的更广泛的独特光谱预测因子，以及强度和SPS。第二个分析使用横截面（混合效应）时间序列分析来利用数据集中的所有单独响应系列，并评估SPS的预测角色的可能一般性。 SP被证明是一个有用的特征，使得与其他光谱参数不同的预测贡献。因为SPS是一个精神声声“自下而上”功能，所以它可能对我们所曝光的音乐中的熟悉和不熟悉的广泛适用性。

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