USVSEG: A robust method for segmentation of ultrasonic vocalizations in rodents
USVSEG: A robust method for segmentation of ultrasonic vocalizations in rodents
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DOI：
10.1371/journal.pone.0228907
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发表时间：
2020-02-10
期刊：
影响因子：
3.7
通讯作者：
Okanoya, Kazuo
中科院分区：
文献类型：
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作者：
Tachibana, Ryosuke O.;Kanno, Kouta;Okanoya, Kazuo
啮齿动物的超声发声（usv）为评估其社会行为提供了有用的信息。尽管之前已经对USV音节时频模式的子类别进行了分类，以研究它们的功能相关性，但从连续记录的数据中检测语音元素的方法仍然不够理想。在这里，我们提出了一种新的方法来检测在观察社会行为时记录的包含背景噪声的连续声音数据中的USV片段。所提出的程序利用稳定版本的声谱图和额外的信号处理，通过减少背景噪声的变化来更好地分离声音信号。我们的程序还提供了精确的时间跟踪频谱峰在每个音节。我们证明了该方法可以应用于从几种啮齿动物物种获得的各种usv。性能测试表明，该方法对USV音节的检测比传统检测方法具有更高的准确性。
Rodents' ultrasonic vocalizations (USVs) provide useful information for assessing their social behaviors. Despite previous efforts in classifying subcategories of time-frequency patterns of USV syllables to study their functional relevance, methods for detecting vocal elements from continuously recorded data have remained sub-optimal. Here, we propose a novel procedure for detecting USV segments in continuous sound data containing background noise recorded during the observation of social behavior. The proposed procedure utilizes a stable version of the sound spectrogram and additional signal processing for better separation of vocal signals by reducing the variation of the background noise. Our procedure also provides precise time tracking of spectral peaks within each syllable. We demonstrated that this procedure can be applied to a variety of USVs obtained from several rodent species. Performance tests showed this method had greater accuracy in detecting USV syllables than conventional detection methods.