Template-based automatic recognition of birdsong syllables from continuous recordings
Template-based automatic recognition of birdsong syllables from continuous recordings
复制标题
DOI：
10.1121/1.415968
复制
发表时间：
1996-08-01
影响因子：
2.4
通讯作者：
Margoliash, D
中科院分区：
文献类型：
--
作者：
Anderson, SE;Dave, AS;Margoliash, D
评价了动态时间规整(DTW)在动物发声连续录音自动分析中的应用。DTW算法将输入信号与代表调查者选择的类别的一组预定义模板进行比较。它直接比较信号光谱图，并识别成分和成分边界，从而允许识别广泛范围的信号和信号成分。当将该识别器应用于从低杂乱、低噪声环境中收集的蓝斑雀(Passerina Bluea)和斑马雀(Taeniopygia Guttata)的发声时，该识别器识别刻板印象中的歌曲和叫声中的音节时，准确率超过97%。更多变化和更低幅度的青蓝旗帜塑料歌曲的音节被识别出大约84%的准确率。在受限的记录条件下，这项技术显然对各种动物发声的分析具有普遍的适用性，并可以显著减少人工识别发声所花费的时间。(C)1996年美国声学学会。
The application of dynamic time warping (DTW) to the automated analysis of continuous recordings of animal vocalizations is evaluated. The DTW algorithm compares an input signal with a set of predefined templates representative of categories chosen by the investigator. It directly compares signal spectrograms, and identifies constituents and constituent boundaries, thus permitting the identification of a broad range of signals and signal components. When applied to vocalizations of an indigo bunting (Passerina cyanea) and a zebra finch (Taeniopygia guttata) collected from a low-clutter, low-noise environment, the recognizer identifies syllables in stereotyped songs and calls with greater than 97% accuracy. Syllables of the more variable and lower amplitude indigo bunting plastic song are identified with approximately 84% accuracy. Under restricted recording conditions, this technique apparently has general applicability to analysis of a variety of animal vocalizations and can dramatically decrease the amount of time spent on manual identification of vocalizations. (C) 1996 Acoustical Society of America.