Extracting Bird Vocalizations from a Complex Natural Soundscape in Forests Using Robot Audition Techniques
Extracting Bird Vocalizations from a Complex Natural Soundscape in Forests Using Robot Audition Techniques
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DOI：
10.1109/sii55687.2023.10039198
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发表时间：
2023-01
期刊：
影响因子：
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通讯作者：
Reiji Suzuki;Shinji Sumitani;Zachary Harlow;Shiho Matsubayashi;Takaya Arita;K. Nakadai;H. Okuno
中科院分区：
文献类型：
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作者：
Reiji Suzuki;Shinji Sumitani;Zachary Harlow;Shiho Matsubayashi;Takaya Arita;K. Nakadai;H. Okuno
鸣禽是生物声学和生态声学研究的重要对象。我们提出了一种简单的方法，利用机器人听觉技术从许多局部化和分离的声音中提取鸟类的发声，并将其应用于野外鸟鸣录音。该方法利用基于变分自动编码器的谱图的潜在空间表示和距离度量来提取和分类分离的歌曲。对加州野外录音的初步分析成功地提取了鸟类的发声，包括来自一种相当遥远的鸟类的发声。我们还给出了一个在回放实验中应用该方法对鸟鸣进行2D定位的例子。
Songbirds are important targets of bioacoustic and ecoacoustic research. We propose a simple method to extract bird vocalizations from many localized and separated sounds using robot audition techniques and report its evaluation by applying it to field recordings of birdsongs. The method utilizes latent space representations of the spectrogram based on a variational autoencoder and a distance measure to extract and classify separated songs. A preliminary analysis of field recording in California successfully extracted bird vocalizations, including ones from a considerably distant bird. We also illustrate an example of applying the method to a 2D localization of birdsongs during a playback experiment.