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Visualizing Directional Soundscapes of Bird Vocalizations Using Robot Audition Techniques

机译:使用机器人试镜技术可视化鸟发声的定向声音

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A visualisation of the soundscape dynamics is one of the important topics in ecoacousics. However, existing approaches mainly focused on the soundscape in the frequency domain while the soundscape in the directional or spatial domain is also essential to better understand animal vocalizations. This paper proposes and discusses novel applications of robot audition techniques to visualize soundscape dynamics in the directional or spatial domain by using the directional information of sound sources obtained from the robot audition software HARK (Honda Research Institute Japan Audition for Robots with Kyoto University) and the software for birdsong localization HARKBird. First, we create a false-color spectrogram that visualizes directional soundscapes in which the color of the spectrogram reflects the direction of arrival of separated sounds. We also visualize the distribution of directional soundscapes by combining the entropy of the likelihood of sound existence (MUSIC spectrum) and a latent space embedding method (UMAP). We applied these techniques to a 5 min recording with 6 individuals of Zebra Finch in order to show that the extracted visual information can reflect acoustic structures among the group of bird individuals in the directional domain.
机译:Soundscape动态的可视化是生态围类的重要主题之一。然而,现有方法主要集中在频域中的Soundscape,而定向或空间域中的Soundscape也是必不可少的,以更好地了解动物发声。本文提出并讨论了通过使用从机器人试镜软件HARK(HONDA研究所日本试镜为机器人与京都大学的机器人的HONDA研究所日本试镜)的声源的定向信息,讨论机器人试听技术的新颖应用。鸟类本地化哈氏软件。首先,我们创建一个假色谱图,可视化光谱图的颜色反映了分离声音的颜色的定向声音。我们还通过组合声音存在(音乐频谱)的可能性和潜空间嵌入方法(UMAP)的熵来可视化定向SoundScapes的分布。我们将这些技术应用于5分钟记录,其中6个单独的Zebra Finch录制,以表明提取的视觉信息可以反映定向域中的鸟类组中的声结构。

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