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Hierarchical temporal structure in music speech and animal vocalizations: jazz is like a conversation humpbacks sing like hermit thrushes

机译:音乐语音和动物发声中的时间层次结构:爵士乐像对话座头鲸像隐士鹅口疮一样唱歌

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摘要

Humans talk, sing and play music. Some species of birds and whales sing long and complex songs. All these behaviours and sounds exhibit hierarchical structure—syllables and notes are positioned within words and musical phrases, words and motives in sentences and musical phrases, and so on. We developed a new method to measure and compare hierarchical temporal structures in speech, song and music. The method identifies temporal events as peaks in the sound amplitude envelope, and quantifies event clustering across a range of timescales using Allan factor (AF) variance. AF variances were analysed and compared for over 200 different recordings from more than 16 different categories of signals, including recordings of speech in different contexts and languages, musical compositions and performances from different genres. Non-human vocalizations from two bird species and two types of marine mammals were also analysed for comparison. The resulting patterns of AF variance across timescales were distinct to each of four natural categories of complex sound: speech, popular music, classical music and complex animal vocalizations. Comparisons within and across categories indicated that nested clustering in longer timescales was more prominent when prosodic variation was greater, and when sounds came from interactions among individuals, including interactions between speakers, musicians, and even killer whales. Nested clustering also was more prominent for music compared with speech, and reflected beat structure for popular music and self-similarity across timescales for classical music. In summary, hierarchical temporal structures reflect the behavioural and social processes underlying complex vocalizations and musical performances.
机译:人类交谈,唱歌和播放音乐。某些种类的鸟类和鲸类会唱长而复杂的歌曲。所有这些行为和声音都表现出层次结构-音节和注释位于单词和音乐短语内,句子和音乐短语中的单词和动机内,等等。我们开发了一种新的方法来测量和比较语音,歌曲和音乐中的分层时间结构。该方法将时间事件标识为声音幅度包络中的峰值,并使用Allan因子(AF)方差量化整个时间范围内的事件聚类。针对超过16种不同类别信号的200多种不同录音进行了AF方差分析并进行了比较,包括不同背景和语言下的语音录音,不同流派的音乐作品和表演。还比较了两种鸟类和两种海洋哺乳动物的非人类发声情况,以进行比较。 AF跨时间尺度的变化模式与复杂声音的四个自然类别中的每一个截然不同:语音,流行音乐,古典音乐和复杂动物的发声。类别内和类别间的比较表明,当韵律变化更大,并且声音来自人与人之间的相互作用,包括说话者,音乐家甚至是鲸鱼之间的相互作用时,在更长的时间尺度上的嵌套聚类更加突出。与语音相比,嵌套聚类在音乐中也更为突出,反映了流行音乐的节拍结构和古典音乐跨时间尺度的自相似性。总之,分层的时间结构反映了复杂的发声和音乐表演所基于的行为和社会过程。

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